Digital twin shop-floor can simulate the plans in virtual space and finds out the potential conflicts before even during the actual manufacturing process.

However, the digital twin shop-floor is a complex and specialized work to be built, especially the models including geometry, rule, behavior, dynamics models. With the help of services, these models do not have to be created by manufacturer themselves.

For physical equipment and pervasive rules, their models which have been established by other manufacturers, can be bought to use in the form of services. Current manufacturer only needs to create the special models, which is only suitable for themselves. Besides, during the operation of the shop-floor, some services, such as data processing, shop-floor management, etc., need to invoke from the services system of digital twin shop-floor.

A main cause of Digital Twin confusion is the variety of focused areas within different disciplines. In order to encourage further contribution in this field of study, the establishment of a common definition is necessary. Additionally reference models, which fulfil the domain specific requirements of the focused areas, must be developed.

A first step towards a common definition of digital twin is based on the differentiation between particular levels of integration. The development of the digital twin is still in early stages, since many of current reports mainly consists of concept papers without concrete case-studies.

However, some applied case-studies already exist – especially at the lower levels of integration. A main focus of recent reports concerning the digital twin in manufacturing is dealing with production planning and control as it is a main data-sink within a production system that ties everything together.

With a mid-level time-horizon, simulation is often used in order to exploit the models at their best. However, the digital twin can also be used in domains with higher time-frequencies as e.g. process control and condition based maintenance, without using time intense simulation, but using other data driven approaches. There is a further research need for case studies industrial environments in order to evaluate the potential applications of digital twins.
 
Digital twin has provided a promising opportunity to implement smart manufacturing and advanced industrial networks by integrating the digital and physical worlds in manufacturing. The service-oriented architecture may expand the functions of digital twin. Digital Twin services can have high potential application in design, manufacturing and product condition assessments.

 Combined with the services and the digital twin, how the various components of digital twin are encapsulated to services and used in the form of services specifies, are specified. At present, reports need much more works to improve and enrich the methods of digital twin modelling and services.
 
With new information technologies developed and applied continuously, developing digital twins to start new paradigm of shopfloor becomes imperative. To support the further convergence in shop-floor, digital twin shop floor model provides evolved models with high fidelity, continuous interactions between physical and virtual spaces and fused data converging those two spaces.

Here we provide a summary of digital twin impacts and a guideline for the future work. The main contributions are concluded as follows: 1) The concept and operation mechanism of digital twin shop floor  are explored. 2) two-way high fidelity connection between physical and virtual spaces, 3) service management and precious service-demand matching,
 
The Digital Twin in its origin describes mirroring a product, while the state of the art allows processes, manufacturing, power generation etc. to be subjects of virtual space reproduction “Twinning” in order to gain the very same benefits.

A central aspect of the digital twin is the ability to provide different information in a consistent format. Digital Twins are more than just pure data, they include algorithms, which describe their real counterpart and decide about action in the production system based on this processed data.

Manufacturing digital twin can be viewed as consisting of a virtual representation of a production system capable of running on different simulation disciplines characterized by links between the virtual and real system. Sensed data and connected smart devices, along with mathematical models and real time data elaboration are also major components of digital twin.

Due to the multiple existing solutions and concepts of digital twin across industries a diverse and incomplete understanding of this concept exist. Considering definitions of a Digital Twin in any context, Digital Twins is identified, as digital counterparts of physical objects.

Within these definitions, the terms Digital Model, Digital Shadow and Digital Twin are often used synonymously. However, the given definitions differ in the level of data integration between the physical and digital counterpart. Some digital representations are modelled manually and are not connected with any physical object in existence, while others are fully integrated with real-time data exchange.
 
Therefore, we could offer classification of Digital Twins into subcategories, according to their level of data integration. Digital Model is a digital representation of an existing or planned physical object that does not use any form of automated data exchange between the physical object and the digital object.

 The digital representation might include a more or less comprehensive description of the physical object to include, but are not limited to simulation models of planned factories, mathematical models of new products, or any other models of a physical object, which do not use any form of automatic data integration.

Digital data of existing physical systems might still be in use for the development of such models, but all data exchange is done in a manual way. A change in state of the physical object has no direct effect on the digital object and vice versa.

Based on the definition of a Digital Model, if there exists an automated one-way data flow between the state of an existing physical object and a digital object, one might refer to such a combination as Digital Shadow. A change in state of the physical object leads to a change of state in the digital object, but not vice versa.

 Digital Twin can be placed in a subcategory where, the data flows between an existing physical object and a digital object are fully integrated in both directions,. In such a combination, The digital object might also act as controlling instance of the physical object. There might also be other objects, physical or digital, which induce changes of state in the digital object. A change in state of the physical object directly leads to a change in state of the digital object and vice versa.
 
Due to its tremendous potential for disruptive development of industry, digital twin is receiving more and more attention from the industry. Digital twin reflects two-way dynamic mapping of physical objects and virtual models.  By building digital twin system that integrates the manufacturing process, the innovation and efficiency from product design, production planning to manufacturing implementation, can be effectively enhanced.
 
 
The application approach of digital twin in factory design is different with the other reported applications. Digital twin should mirror the designed factory that will be physical in the future. Because the uncertainty exists in each design stages, the design changes before it was constructed. In order to offer an elaborate simulation and help the designer to make decision.

Digital twin mirrors not only the final physical factory but also the virtual factory corresponding to each design version. For this reason, another problem arises because digital twin has to change with the change of design, whereby establishing a digital twin model can take a considerable amount of time and a lot of digital twin models will result huge modeling time and workload.

To solve this problem, a modular approach for building flexible digital twin is useful. The modular approach is building reusable and parameterized modules corresponding to physical entities in advance. When physical entities changed, the modules conduct corresponding changes driven by parameters and integrate as a digital twin model of physical factory. Through the modular approach, the modeling time is greatly reduced.

When the factory design changes, the digital twin can conduct the corresponding change highlighting the flexible abilities of digital twin.

The performance degradation of physical equipment is inevitable. When the equipment malfunction, it results in high maintenance costs and postponement of tasks.

Tools are necessary to monitor the equipment condition, predict and diagnose equipment faults and component lifetime. In digital twin driven condition tools, virtual models of physical equipment are linked with the real state of the equipment. The operation status of the equipment, and the condition status of the components, are captured in real time.
​
A high-fidelity digital mirror for the equipment provides access to the equipment even out of physical proximity. Interaction of digital twin can reduce the disturbances from the external environment, improving accuracy. In such a process, the models are accessed through services. Moreover, when the failures occur, repair services are invoked to repair, or replace the broken-down equipment.
 

1. Digital Twin utilization in factory design discovers design flaws, reduces build duration of model improves application to changeable factory design
2. Digital Twin reflects two-way dynamic mapping of physical objects and virtual models to integrate/implement manufacturing process
3. Digital Twin includes consideration of all pieces of equipment and production line on shop floor/factory
4. Digital Twin Fusion data is core driver including data from physical entities, virtual models and services
5. Digital Twin driven design turns expected design product plans into digital representation based on existing physical products
6. Digital Twin is description of component, product, system or process by set of well-aligned, descriptive and executable models
7. Digital Twin is semantically linked collection of digital artifacts include design/operational data and behaviour descriptions
8. Digital Twin changes with real system along the whole life cycle and integrates the currently available and commonly required data
9. Digital Twin creation/deployment of simulation models sets with defined purpose and validity range to add new models for intended/future function
10. Digital Twin provides anchor for all lifecycle phases and support of transformation to the next phase

 

With the development of smart manufacturing, traditional factories are transforming to smart factories. Traditional factory design approaches are not able to insight the dynamic behaviors of designed factory. The emergence of digital twin can effectively solves this problem because of the fidelity to physical factory.

Here is a framework for digital twin’s application including conceptual design, elaborate design and finalized design. According to changes with the potential happen in each design stage, a modular approach is required to build flexible digital twin to save workload and time for developing new digital twin.

Through a case study by using the digital twin in factory design, hidden design flaws are discovered and solutions are proposed. Moreover, it can be concluded from this case that the duration for building digital twin model is greatly reduced by using modular approach, which improves the feasibility for applying digital twin to changeable factory design. Different industries have different characteristics and modules may different in different industry application.

Digital twin offers a practical way to study smart manufacturing by focusing on  building digital twin for smart machine, smart workshop and smart factory. Not much attention has been focused on the application of digital twins to factory design. A lot of work has been done in  production, but less so for layout and equipment configuration applicable to factory design.

Design frequently changes from initial version to final version. These characteristics carry challenges to digital twin introduced to factory design. Traditional factories are increasingly transforming into smart factories, and the demand for design new factories is increasing simultaneously
 
The concept of digital twin shop-floor has been introduced into the production floor, opening up the bottleneck between the physical and information worlds through a combination of physical and virtual models Operational control of Automated Guided Vehicles  inside the shop floor can take advantage of digital twins to increase operating efficiency.
 
Smart assembly equipment and shop floor production lines can also increase effectiveness by using digital twin technology. There has been investigation into connections between people and digital twin in production area. This includes interactions between large amounts of data and information in production and the substitution of manual methods for a digital twin to improve planning and management in industrial production.

Digital twins also have a wide range of applications during the machining environment. Traditionally, the design of a factory is considered to be an optimization algorithm design problem with the capacity as the final optimization goal and the equipment or the area as the restrictions.

However, in a very dynamic real production environment, the traditional algorithm cannot effectively solve the optimization scheme. Therefore, more complex algorithms have been designed, but in a practical factory, the dynamic behavior of the manufacture system is difficult to be predicted in mathematic equations.

For this reason, the optimization is valuable only when the manufacture system is constrained by some assumptions. Consequently, these algorithms can solve simple dynamic problems, but are not very good at modelling complex problems.

Because of the complexity, there are studies of factory design using discrete event system simulation like integrated simulation model to predict the life span of individual parts or a simulation-based approach to integrate mathematical algorithms to balance the operation performance and planning cost.

Investigations have been applied to simulate the factory layout and help the designer to experience the designed virtual factory. However, factory layout is not the only issue of factory design. It also includes detail works such as capacity calculation, machine utilization, number of machines, designing of the logistics and calculation of its efficiency. etc.

These issues are difficult to present with traditional algorithms or just visualized by virtual reality technique. Regarding the design phase of a smart factory, the majority of businesses remain in a relatively undeveloped stage, using inadequate historical data to predict key performance indicator KPI, such as throughput, equipment usage and storage capacity.

Since high dynamic and random features will be carried out in the future production of the designed factory, the KPI prediction can only derived by limited calculation or empirical ways. This traditional factory design approach cannot utilize all historical production data, consequently may leads to design flaws in the design phase and might be huge problems in future production.

Consequently, digital twin might be a suitable solution because of its fidelity to physical world. Big problems may be avoided in early design stage and the performance shown by digital twin should be ideal.

Digital twin can undoubtedly increase the feasibility and quality of a design project. Digital twin forces the designer to design the factory in detail, which includes factory layout, material handling, buffer capacity, worker shift etc., coordinating these factors to make the designed factory efficient and strong.

Typically, factory design includes several main design stages: conceptual design, elaborate design and finalized design. Conceptual design is the first design stage, it focused on the designing the concept of new factory, which includes plant layout, capital investment and throughput predication. In conceptual design phase, digital twin can help the designers and shareholders to verify the design concept, predict throughput and rate of return on investment by simulating the process in a relative rough way.

Elaborate design is the second design stage and further conceptual design, includes machine configuration, process design, production line or production unit configuration, material handling system configuration and work shift configuration. In most of the cases, the objective of elaborate design is to further and validate conceptual design. Consequently, digital twin in elaborate design phase is to help the designers to elaborate design the factory and integrated validation.

Finalized design is the final stage and links to construction. In this stage, the machine and logistics unit control strategy will be designed and the whole manufacturing system needs to be integrated. Because the virtual factory corresponds to the finalized design is the most similarity to physical factory in the future, therefore digital twin has the most fidelity to physical world in this stage.

Digital twin connects with multiple control tools like manufacture execution systems and programmable logic controller. Due to the connection, digital twin emulates the manufacturing and logistics control strategy, and help the designer to debug the control and make decision.

The framework of digital twin’s application on three design stages enables designers to connect with suppliers, shareholders and design documents with considering the simulation results of digital twin. Based on the output of digital twin, designer evaluates the current design and decides whether it can be approved.

In conceptual design stage, digital twin mirrors the design concept and visualized the concept by animation. The animation helps the designer to further the concept in a comprehensive way and clearly states the design to shareholders and suppliers. In elaborate design stage, digital twin mirrors the detail configurations of the factory and validate whether the configurations can carry out plenty of throughput via simulation.

In finalized design stage, digital twin mirrors the final approved design and emulates it as a virtual factory. Due to the emulation, the control strategy and tool design can be confirmed.

Digital twin progresses from conceptual design to finalized design while the fidelity to physical world also moves forward stage by stage. Fidelity of digital twin High fidelity to physical world is one of the most important features of digital twin.

However in factory design, the physical world is vague and different in the three design stages. In conceptual design stage, the physical world is the uncertain concept hidden in awareness of designer concepts. It can be definite when the factory layout is produced. Traditionally, the factory layout is two dimensional diagrams, investment and throughput can only be calculated with basic calculation because of uncertainty.

Digital twin can make the concept solid with three dimensional animation and help the designer to think the concept in a relative detail way. Moreover, investment and throughput can be predicted with algorithms or knowledge based approaches embedded in digital twin.

Consequently, the fidelity of digital twin in this stage is mapping the uncertain design concept. Since most data is uncertain, 3D animation is the most useful feature of digital twin in conceptual stage.

The physical world in elaborate design stage is more definite than conceptual design stage. The factory layout, machine layout, material handling system, working shift, and even equipment efficiency are defined in this stage.

Consequently, the physical world in this stage is the product-making mechanism in the designed future factory. For example, the product can only be processed only if the product is transported to the destined machine. The corresponding machine, fixtures, tools and skilled workers need to be available so that the processing conditions are met. Otherwise the product has to wait in queue and may jam the working flow.

Many design parameters are critical in this stage, such as equipment number, worker number, and buffer capacity. These parameters are difficult to be accurately validated because manufacturing process is featured by mixed up dynamic behavior.

 Embedded with discrete event simulation, digital twin can test different parameter combinations step by step. Consequently, accurate parameters validation can be offered and helps to make decision.
In finalized design stage, the physical world is the physical entity in future factory. The features of physical entities are not only appearance but also internal control strategy so the main connection between virtual model and physical entities is the control.

On the other hand, control is decentralized into different physical entities in smart manufacturing. The fidelity of digital twin in this stage is to emulate decentralized control of physical entities and the integration of them. Based on the emulation, digital twin helps the designer to evaluate control strategies and find the best one to match designed factory. 
 

1. Digital Twin provides links between real/digital world by mapping measured data, and virtual representation
2. Digital Twin functions as element of product itself and delivered with components or as stand-alone service forming business models
3. Digital Twin closes feedback loop back to real system and early lifecycle phases for development of new versions or product generations
4. Digital Twins can be embedded in the component or device and accompany the real twin once manufactured
5. Digital Twin of product combined with production system twins include engineering/virtual tasks and operation of the plant itself
6. Digital Twin utilises sensor data and collected information on product use supports optimized application of product itself
7. Digital Twins valid for multiple instances enhanced by production information collected to generate fleet data for applications and services
8. Digital Twin template specified during the conceptual design phase to describe how different components are linked together and interact
9. Digital Twin functionality identifies  possible root causes of malfunctions in contrast to pure detection
10. Digital Twin connection with operational data offers  wide range of new services from failure detection and diagnosis to faster product improve/develop

 
 
 

Digital twin has provided a promising opportunity to implement smart manufacturing and industrial processes by integrating the digital and physical worlds in manufacturing. The service-oriented architecture may expand the functions of digital twin. Through services, digital twin can have high potential application in design, manufacturing and equipment condition monitor.

The combination of smart manufacturing services and digital twin would radically change product design, manufacturing, usage, maintenance and other processes. Combined with the services, the digital twin will generate more efficient manufacturing planning and precise production control to help achieve smart manufacturing through the two-way connectivity between the virtual and physical worlds of manufacturing.

The advances in new generation information technologies, such as big data, high-performance computing, artificial intelligence etc., and their wide applications, are driving the manufacturing industry toward smart manufacturing

But how to converge the physical and digital worlds of manufacturing is still a major challenge. Digital twin creates high-fidelity virtual models for physical objects in digital way to simulate their behaviours.

In virtue of digital twin, complex manufacturing process can be integrated to achieve the closed-loop optimization of the product design, manufacturing, and smart services, etc.

Service plays an increasingly more important role in manufacturing. More and more manufacturers adopt service logistics for their business to compete and gain more revenues.

Services can shield the resources with differences, which are conducted by different vendors using various standards, and communication protocol/interfaces, and enable the interaction and integration between them.

With the characteristics of on-demand use, reconfiguration, and platform independence, services endow manufacturing with the advancement of large-scale sharing and collaboration.

 In view of the concept of Everything-as-a-Service services could fully release the potential of digital twin. Through services, each component of the digital twin can be shared and used in a convenient “pay-as-you-go” manner,  especially virtual models which are not easy to be created rapidly.

In the working process of digital twin, services are integral part, and a lot of actions require the support of third-party services. For example, multi-source data fusion requires algorithms, computing and storage services.

Due to tremendous potential of digital twin for disruptive development of industry, digital twin is receiving more and more attention from industry.

Because of the frequent use by major industry groups, some explanations and definitions of digital twin have been proposed. The most commonly used definition of digital twin is composed of three parts: physical products, virtual products and the connections between them.

Digital twin reflects two-way dynamic mapping of physical objects and virtual models By building digital twin system that integrates the manufacturing process, the innovation and efficiency from product design, production planning to manufacturing implementation, can be effectively enhanced.

 For smart production, from small as a piece of equipment and a production line, to big as a shop floor or entire factory, all of them can be considered as a digital twin. Therefore, from the perspective of smart production, digital twin can be divided into three levels, i.e., unit level, system level, and system of system level.

The unit level, system level and system of systems level digital twin is a systematic model with rank going forward step by step. The system-level digital twin can be considered as the integration of multiple unit-level digital twin, which cooperate with each other. Multiple unit-level digital twins or multiple system-level digital twins constitute the systems of system-level digital twin, i.e., complex system. The unit-level and system-level digital twin meet  the 3D definition of digital twin, i.e., physical entities, virtual models and the connections between them.
 
The unit level digital twin is the equipment. Equipment is the smallest unit participated in manufacturing activities. The optimization of manufacturing activities is achieved through the adjustment of equipment. With respect to system-level digital twin, a smart production line composed by machine tools, robot arms, etc. is system-level.
 
 For unit-level and system-level digital twin, the virtual models are the ultra-high-fidelity mapping of physical equipment through the digital description from the perspectives of geometric shape, function and operating status of equipment and production line.
 
 The basic attributes, real-time status and other data are transmitted to the virtual models to drive the simulation and prediction. Then, the parameters of the virtual models are fed back to optimize physical entities. In the closed-loop interaction process, the physical entities and virtual models co-develop.

For the system of system level e.g. shop-floor, accurate shop-floor management and reliable operations, which are inseparable from services, are very important for smart manufacturing. To further promote digital twin concepts and technologies, service is added and the role of data is valued. As a result, the three-dimensional structure of digital twin is extended to five-dimension, which are physical entities, virtual models, services, fusion data, and the connections among them.

 Physical entities are the set of objective entities, which have specific functions to complete manufacturing tasks according to inputs and outputs

Virtual models are the digital images of the physical entities, which can completely and truly reflect the lifecycle of the physical entities.

Services integrate various functions such as management, control and optimization, to provide application services according to the requirements.

Fusion data is the core driver of the digital twin, including the data from physical entities, virtual models and service, as well as their fusion data.

The connections among them connect the parts in pairs, ensuring real-time interaction and iterative optimization. Based on the five-dimensional structure of digital twin, the digital twin shop-floor provides a new way to practice smart manufacturing.

Models and data are the cores of the digital twin. However, the creation of virtual models is complex and specialized project, so are the data fusion and analysis. For users who do not have relevant knowledge, it is difficult to build and use the digital twin. Therefore, sometimes models are able to be shared by users and data analysis are outsource.

 Moreover, in the context of the manufacturing behavior, the physical resources involved in manufacturing are geographically distributed. With the characteristics of on-demand use, dynamic reconfiguration, and platform independence, services pave a way for frequently occurring problems.

The first and the most important step of service concept is to establish the information template, which consists of a variety of information For the physical objects, these information includes basic attributes e.g., name, ID, address, etc., time, cost, reliabilities, satisfaction, etc., capacities e.g., precision, size, process, etc., real-time status e.g., overload, idle, in maintenance, etc., as well as input and output.

Digital twin services consist of the equipment services, technology services, test services, data services, knowledge services, algorithms services, models services, simulation services, etc. In addition, there are many auxiliary services, such as financial services, logistics services, training services, equipment repair services and others. The services management includes searching, matching, scheduling, combination, transaction, fault-tolerance, etc.
 
A task is submitted to the management platform. Then, it is decomposed into subtasks that can be accomplished by a single service. The manufacturing service supply/demand matching and scheduling is carried out to select the optimal services. After the service transaction, the selected services are invoked and combined to complete the task collaboratively. Finally, the results are fed back to the users.

The digital twin services can be used in product design, production planning, manufacturing execution, equipment condition monitor, and other applications

In product design, it is the process of back-and-forth interactions between the expected, interpreted, and physical worlds. The digital twin driven design is to turn the expected product in the designer workspace into the digital representation in interpreted world based on the existing physical products.

To innovate products, designers have to study plenty of data to acquire valuable knowledge. However, the data about product is one of the most important assets, which is not easy to access. Besides, the designers also do not have the professional abilities to process massive data.

Service is an answer to these problems. Designers just simply submit their needs to the services management platform. Services managers will match the data services which designers need and the models and algorithms services that are used to process the data.

Combining and operating these services, the results are returned to the designers. As a result, designers acquire what they want in the “pay-as-you-go” manner. Moreover, after the function structure and components of product are designed, the design quality and feasibility need to be tested.

With digital twin, designers can quickly and easily forecast product behavior through verification of virtual products without having to wait until the product prototype is produced. But the virtual verification need the models of manufacturing site e.g., production line or shop-floor, etc., which designers do not have.

Model services can be used through services searching, matching  and scheduling Through services, digital twin can be easy applied in product design, which can make product design more effectively to reduce the inconsistencies of expected behavior and design behavior, and greatly shorten design cycles and reduce costs.

In general, product manufacturing is the whole process from the input of raw materials to the output of finished products, which is executed in shop-floor. To reduce cost, production time, and improve efficiency, production planning to predefine the manufacturing process is necessary.

In the phase of production planning and manufacturing execution, digital twin provides an effective method to draw up the plan and optimize and execution process.

A production task is submitted to services management platform and resource services supply-demand matching and scheduling are carried out to find available resources. Then, based on the real-time status of physical resources e.g., machine tools, robot arms, etc., production plan is drawn up.
 

1. Digital Twin offers a practical way to study smart manufacturing with focus on building digital twin for smart machine, smart workshop and smart factory.
2. Digital Twin is digital mirror of physical world and maps performance of physical world
3. Digital Twin introduces into production floor to open up bottlenecks through a combination of physical and virtual models
4. Digital Twin can increase feasibility/quality of design project to include factory layout, material handling, buffer capacity, worker shift etc.
   
5. Digital Twin helps to coordinate systematic factors and makes condition of designed factory strong.
   
6. Digital Twin mirrors and feeds back physical design simulation stages to connect with suppliers, shareholders and design documents
   
7. Digital Twin output allows designer to evaluate current design and decide if  it can be approved
   
8. Digital Twin replicates detail configurations of factory and validates if configurations can carry out volumes of throughput via simulation
   
9. Digital Twin monitors final stage approved design and replicates it as virtual factory to confirm control of strategy and network design
   
10. Digital Twin maps fidelity of uncertain design concept with 3D features

 

​The Navy’s four shipyards perform depot-level maintenance that involves comprehensive and time-consuming maintenance work, including ship overhauls, alterations, refits, restorations, nuclear refueling, and inactivations—activities crucial to supporting Navy readiness.

This maintenance can include major repair, overhaul, or the complete rebuilding of systems needed for ships to reach their expected service life, and involves complex structural, mechanical, and electrical repairs. The Navy generally schedules these maintenance periods—referred to by the Navy as “availabilities”— every 2 to 3 years for each aircraft carrier and every 4 to 6 years for submarines--
 
The level of complexity of ship repair, maintenance, and modernization can affect the length of a maintenance period, which can range from 6 months to about 3 years for more complex and involved maintenance. The longer, more complex maintenance periods that are performed are designated in the Navy’s Optimized Fleet Response.  The plan is designed to maximize the fleet’s operational availability to combatant commanders while ensuring adequate time for the training of personnel and maintenance of ships.
 
Navy is working to rebuild its readiness while also growing and modernizing its aging fleet of ships. A critical component of rebuilding Navy readiness is implementing sustainable operational schedules, which hinge on completing maintenance on time.

The Navy continues to face persistent and substantial maintenance delays that affect the majority of its maintenance efforts and hinder its attempts to restore readiness. From fiscal year 2014 to the end of fiscal year 2019, Navy ships have spent over 33,700 more days in maintenance than expected. The Navy was unable to complete scheduled ship maintenance on time for about 75 percent of the maintenance periods conducted during fiscal years 2014 through 2019, with more than half of the delays in fiscal year 2019 exceeding 90 days. When maintenance is not completed on time, fewer ships are available for training or operations, which can hinder readiness.

This Report provides the foundation for future estimates of activities on maintenance-resource requirements, availability, and annual operating costs.

This report is of interest to force planners, maintenance production planners, maintenance policy analysts, system program directors, and logistics and cost analysts.

Planners can use the empirical and analytic results in this report to forecast how workloads and costs may grow in both the near term and long term. 

System program directors can use those results to gain an integrated perspective of the end-to-end resource and budget implications for their weapon systems. 

Logistics and cost analysts will be interested in how this analysis dealt with the wide range of difficult factors that may affect the measurement of age-related workload growth and in the way in which different patterns of growth are exhibited for different designs for different categories of workloads and material consumption.
Job Sites provide maintenance support as part of the planned maintenance cycle that keeps Navy ships ready and responsive, reflecting Naval Sea Systems Command’s commitment to returning ships to the fleet on-time.
 
Critical path work can be completed ahead of schedule, including significant preservation efforts of the gas turbine generator fan room and Vertical Launch System.
 
“The success of this availability was a team effort. All stakeholders were committed to not only completing the work, but also doing so while putting safety at the forefront.”
 
One of job site key missions is to return readiness to the Fleet Commanders for tasking in a challenging and contested environment. The job site also provides contract management oversight, fleet technical assistance, voyage repair and diving and salvage to Forward Deployed Naval Forces.
 
“NAVSEA program management of the shipyards plans for the long-term maintenance of aircraft carriers and submarines”
 
Navy maintenance planning process specifies planning milestones intended to ascertain the ship’s condition, identify the work needed, and plan for its execution. Missing or meeting planning milestones late can contribute to maintenance delays. However, the Navy does not always adhere to its own maintenance planning process due to high operational tempo, scheduling difficulties, or personnel shortages, among other factors, resulting in shipyards discovering the need for additional repairs after maintenance has begun and adding time to the schedule for planning, contracting, or waiting for parts.
 
 This planning focuses on capturing the timing and duration of the maintenance periods, resources needed to perform the maintenance, and the technical requirements for each class of ships. For example, a maintenance plan for a class of ships could identify resource needs for equipment overhauls, propulsion shaft replacement, and corrosion protection.
 
To identify the requirements for specific ships, NAVSEA coordinates the development of a “baseline availability work package,” which represents the technical requirements needed to ensure a ship reaches its expected service life and meets its operational commitments. NAVSEA planners then use these technical requirements as a basis for developing the detailed work package, which describes the types of maintenance needed and the schedule for completion, among other things
 
Due to the finite amount of docks available to perform maintenance at the Navy’s four shipyards, any delays in starting and completing maintenance can lead to a “bow wave effect” because delays in completing one maintenance period may impact the start time of the next scheduled maintenance period. This “bow wave effect,” coupled with ongoing maintenance delays, may lead to continued high rates of idle time for submarines
 
According to NAVSEA officials, shipyard performance can include delays to work progress associated with job- specific material and equipment issues and work stoppages awaiting technical resolution.
 
NAVSEA officials stated that they revised planning factors for ship maintenance to improve estimated workload requirements and cost factors. NAVSEA officials stated they plan to analyze the results from the revised planning factors annually to monitor whether the changes improve estimates and to make adjustments as needed. According to NAVSEA officials, they will not know whether the changes they are making result in improved estimates until work on ship maintenance periods using the revised planning documents and planning factors is complete—a process that may take several years.
 
“Shipyard Capacity and Workload Leveling Challenges Require Stakeholder Attention to Ensure Maintenance and Modernization are Performed with Acceptable Time/Efficiency Targets”
 
Both public and private plans depot maintenance plans specifically focus on three major areas of improvement: dry dock capacity and survivability, facility layout and infrastructures optimization, and capital equipment requirements and modernization. This plan focuses on recovering and modernizing the nation’s current capability and capacity. In this new era of great power competition, a follow-on plan will focus on potential surge requirements resulting from unplanned increases in operational tempo or battle damage.
 
Maintenance and modernization requirements must be fully funded and efficiently executed to reduce deferred maintenance that adds risk to future fleet readiness. Risks to be addressed during the next 30 years include optimizing maintenance and modernization business processes (e.g., availability planning and execution) and adjusting the industrial base capacity and capability as the fleet grows to 355 ships.

Navy must stabilize the vendor base by forecasting future logistics requirements (material availability) required to maintain fleet reliability and reduce the risk to readiness and survivability, facility layout and infrastructures optimization, and capital equipment requirements and modernization.

Achieving and sustaining future battle force ships will require a continuous investment in the public and private industrial capacity and capability. This includes investments in additional infrastructure (e.g., dry docks and piers), training, and manpower.

The Navy employs a modernization program that captures changing modernization requirements with frequent reviews during the availability planning cycle. Technical maturity and certification status are monitored continuously throughout the maintenance cycle through the Modernization Readiness Assessment process.
 
Sustaining the future fleet will require changes to both public and private industrial capability and capacity. Current infrastructure will require update and refurbishment to support modern classes of ships and repair. Likewise, additional dry docks will be needed to address the growing fleet size
 
This includes investments in updating facilities and capital equipment, and as well as providing that workforce training that is both modern and relevant and compensation commensurate with the skill required to repair Navy ships. Finally, we must avoid feast and famine cycles that erode both the repair industrial base and the underlying vendor supply base.
 
Consistent funding matched to steady demand for work will enable the repair base, public and private, to grow to meet the needs of the 355- ship Navy.
 
“Shipyards Need to Contribute to Ramped-up Shipbuilding and Repair Effort to Address Capacity if Called to Respond”
 
A deficit of ship repair capacity and an expected change in the Navy’s needs for large combatants versus smaller ones may force the entire industry to reconsider their roles in construction and maintenance work going forward.
 
Navy acknowledged that more companies would need to get involved in ship repair, and also that more companies getting involved on the construction side could cause hardship from some of the traditional shipbuilders that have spent years optimizing their yards to build large warships.
 
“We’ll see what we do with the fire damage to that ship but that’ll be a massive effort to repair if that’s where the decision goes – We’re talking years most likely. Public and private investment is needed” to grow the ship repair industrial base.
 
Existing repair industrial base is working hard to get more efficient at the work it does, but ultimately that base is too small, especially as the Navy tries to grow its fleet. If large firms showed interest in ship repair means there’s a future to this business model.
 
The shipbuilding industry in recent years has relied primarily on seven yards owned by just four companies to build large warships – but all indications point to a future fleet that relies less on destroyers and large amphibious ships and more on a large number of small amphibs, small combatants and unmanned surface vessels.
 
“If the force structure comes up with the need for a portfolio of lesser large ships and more of the small ships, then the larger yards will have to determine how to flex to that. Their infrastructure is set up to build big ships. Are they capable of building/repairing smaller platforms?
 
There’s a lot of opportunity for smaller yards who already are pretty efficient at building some of those smaller ships. So assuming that the piece of the pie does not grow, there will be a discussion about where the dollars go and where that capability exists.”

1. Providing ships to fleet with defects

2. Optimistic Sustainment assumptions  

3. Extended deployments  

4. Low crew levels

5. Deferred maintenance  

6. Limited dock and workforce capacity  

7. Conditions of facilities and equipment  

8. Spare Parts and Technical data

9. Personnel Shortages  

​10. Planning Process  

The Navy has recognized the factors associated with maintenance delays and has begun focusing on the unplanned work and workforce factors that are contributing to most aircraft carrier and submarine maintenance delays. However, even though the Navy has taken steps, such as attempting to more accurately project the duration and resource requirements for planned maintenance on aircraft carriers and submarines, continuing to routinely and consistently use overtime to meet planned maintenance is untenable.
 
The ability of the Navy’s four shipyards to complete aircraft carrier and submarine maintenance on time directly affects military readiness because maintenance delays reduce the amount of time aircraft carriers and submarines are available to perform their missions and protect our national security. The Navy’s four shipyards have continued to face chronic and substantial delays in over half of aircraft carrier and more than three-quarters of submarine maintenance periods, and the Navy has experienced substantial growth in idle time for submarines awaiting the start of maintenance periods.
 
 
Shipyard Performance to Plan initiative may help NAVSEA and shipyard leadership better understand factors contributing to maintenance delays and inform decisions to address them. However, NAVSEA has not developed over half of its metrics for measuring the impact of the unplanned work and workforce factors or implemented related goals, action plans, milestones, and a monitoring process to improve the timely completion of maintenance.

Set of metrics would help the Navy better address the main causes of maintenance delays, metrics on their own would not resolve those issues. Unless NAVSEA uses the key elements of a results-oriented management approach to address factors contributing to maintenance delays such as unplanned work and workforce issues at the Navy shipyards, delays in maintenance periods and idle time are likely to persist. Completing these actions as soon as possible could increase the overall availability of aircraft carriers and submarines to perform needed training and operations in support of their various missions and improve readiness.
 
“Shipyard Performance to Plan initiative to address both unplanned work and workforce factors to better understand maintenance challenges and future capacity needs”
 
“Performance to Plan”  initiative includes the proposed development of analytically based metrics to measure various aspects of shipyard maintenance that could support the development of potential solutions to address them. Specifically, the initiative includes 25 metrics being developed to improve the Navy’s understanding of the causes of maintenance delays. Nearly all potential metrics—are intended to measure various aspects specific to the unplanned work and workforce factors we found to be the main causes of maintenance delays for aircraft carriers and submarines at the Navy’s four shipyards.
 
According to Navy officials and plans, this effort is intended to help the Navy improve full and timely completion of maintenance, including for aviation, surface ships, and submarines. For example, the effort for surface ship maintenance currently involves a pilot program looking at how to better plan and execute maintenance periods for DDG 51-class destroyers, including examining how to improve the accuracy of forecasted maintenance requirements and duration and better adhere to planning milestones, among other outcomes.
 
Metrics to measure the unplanned work factor: As of February 2020, 10 of the 25 metrics being developed in the initiative focused on addressing various aspects of the unplanned work factor. For example, a forecast and planning efficiency metric is being developed to measure the accuracy of 3-year planning ship maintenance forecasts as compared with actual results. In addition, metrics are being developed to quantify the main causes of ship maintenance planning inaccuracy, such as new work, which have led to schedule delays and cost increases at the shipyards.

Metrics to measure the workforce factor: As of February 2020, 12 of the 25 metrics being developed in the initiative focused on addressing various aspects of the workforce factor. For example, a metric is being developed to measure task duration while another is to measure work throughput. In addition, metrics are being developed to identify whether tasks were started on time, among other things.
 
NAVSEA’s Shipyard Performance to Plan initiative has been underway since the fall of 2018. However, as of February 2020, more than half—13 of 25—of the proposed metrics remained undeveloped. Specifically, each proposed metric included six categories of information: definition of the metric, data owner, data source, status of the data (complete/incomplete), way ahead (next steps), and correlation (to maintenance delays).

Twelve of the proposed metrics appear to be fully developed because they include information in each category. For example, for schedule execution efficiency, a definition of the metric, the data owner, and data source were identified and the status of the data, the way ahead, and the correlation to maintenance delays were all described. However, we found that 13 of the 25 proposed metrics were not fully developed. For example, as of February 2020:
 
Two proposed metrics related to unplanned work intended to measure both discoverable and undiscoverable new work included the identification of a data owner, but the metrics have not been defined, and the data source, status of the data, way ahead, and correlation to delays categories are characterized as “to be determined.”

The proposed metrics for both planned and actual manning included definitions, data owners, data sources, and way ahead, but the status of correlation to maintenance delays is identified as “to be determined.”
The proposed metrics, “start tasks on time” and “workforce experience,” had planned completion dates of October 2019 and these dates were not updated in two subsequent briefings
 
Visual dashboard depots are developing is intended to enable officials to drill down from strategic metrics—such as P2P—to operational or tactical metrics, as needed, to help them better pinpoint the causes of poor performance and therefore to develop solutions. For example, if the P2P metric shows a particular depot as not meeting its goal, then officials will be able to review a related operational metric, such as one called “First Pass Yield,” which identifies whether the depot is experiencing high rates of rework. If needed, officials could obtain more detailed information about the depot’s performance by drilling down further to another operational metric, such as one called “Route Accuracy,”
 
Depot stakeholders reported that they did not know how the depots could incorporate the input that they provided at a workshop intended to discuss data sources of the metrics. Specifically, according to these depot stakeholders, they learned at this workshop that the metrics initiative may result in metrics that are not beneficial for the depots, but they did not know whether officials understood this or would address their concerns.
 
 These depot stakeholders stated that to populate the metrics dashboard the depot may use a set of data that are different from those used by the depots to conduct daily maintenance work. Once metrics dashboard is launched, senior leaders may not fully understand the data and may reach out to the depots with questions about them. If metrics are based on a different set of data from those used by the depots, then the depots may have to devote additional resources to understanding the metrics data and answering related questions
 
 
“Navy Must Explain to Congress What it Needs to Keep Ship Repair Yards Able and Optimized to Maintain Modern Warships”
 
Congress mandated naval shipyard optimization plan is due with a companion plan regarding private shipyard investments also in the works by the service. Plan for the four public naval shipyards would include a “fairly significant investment over the course of about 20 years, $10 billion-plus” that includes upgrades to the drydocks, a redesign of the yards’ layouts to optimize the flow of people and material, and new equipment to maintain and modernize 21st Century warships.
 
Among the Navy’s challenges is that the oldest yard, Portsmouth Naval Shipyard,  originally designed for ship construction; though the Navy has made piecemeal improvements over the decades, there hasn’t been a strategic, concerted effort to overhaul these public shipyards to meet the Navy’s current needs.
 
Some of these upgrades are needed as newer ships come into the fleet – the Virginia-class attack submarine with the Virginia Payload Module will not fit in all the naval shipyards’ drydocks, for example – and if the Navy hopes to sustain a 355-ship fleet it needs to begin making investments to improve the yards’ output now.
 
Though not required by Congress, a hard look at the private repair yards is also necessary to support a 355-ship fleet, which can only be achieved in the near-term through service life extension programs (SLEPs) for many surface ships – work that would likely be done exclusively at private yards.
 
Additionally, as more even-variant Littoral Combat Ships come into the fleet and begin operations out of San Diego, drydocks on the West Coast will be even more in-demand, as those Independence-variant LCSs require a drydock for nearly all their maintenance availabilities.
 
“If you’re going to talk about a meaningful SLEP program we also have to turn our attention to the private sector and say, what does the private sector equivalent look like to this naval shipyard optimization plan? What does the private sector need in terms of drydocks and capacity and productivity improvements to manage the work we would demand out of them if we were going to go keep these ships longer?”

“So there’s a private sector equivalent which we haven’t done as much work on, so NAVSEA will be holding meetings with industry  to inform this private yard plan.
 
“Over the course of decades and decades, we accumulated risk in our infrastructure,”

“We’re now at the point where we’ve gotten a little bit more sophisticated, we’ve culled the data, and NAVSEA’s maintenance and industry operations division has put together a very credible argument on the need to make decisions now and over the foreseeable future, that if we do not make decisions we start to lose the capability to do a type of ship in a drydock in this year, and it just starts to accumulate. So now is the time to articulate that and present that in terms of risk to senior decision-makers.”
 
“Following closely behind that … there’s a private sector piece that has to be a companion and integrated together.”

“So there’s going to be two companion products, and it’s a wide-ranging approach from the operator to communicate with senior leadership what the risks are. Both  routine maintenance as well as upcoming SLEP efforts would put a “relatively significant demand signal on docks” in major fleet concentration areas like Norfolk and San Diego and also in places like the Pacific Northwest and in Florida
 
The private shipyard optimization plan will take into account what we’re doing on the public yard side,” but that a clear takeaway already is that “you can quickly go to, we need more docks.”
 
“Part of that, though, also becomes, what has happened to the docking duration? What’s happened to Navy oversight activity and industry’s activity during the dock duration, and how do we solicit docking-related avails in a more efficient way to allow industry to propose if they could double-dock ships,?

“The private part is different than the public; it doesn’t mean the Navy’s necessarily going to request funds to go buy docks out in the private sector. We might be improving some docks to modify that graving dock to handle a DDG with the sonar dome issues – but we obviously want to get to the incentive and cost-sharing approach that.industry is interested in across the nation.
 
“To do that, we realize the most important thing is probably predictable, forecasted work.”

1. Unplanned Work

Includes new work, growth work, rework, emergent repairs, testing, and late identification of work and requirements

2. Modernizations and Alterations

Includes adding new equipment and systems, providing improvements and changes that permanently change configuration of ship

3. Parts and Materials

Includes not being able to find or use the right spare parts or material, taking parts from one ship and putting them on another, lacking order history and long lead times

4. Facilities and Equipment

Includes not having enough dry dock capacity, poor conditions and old or broken machines and equipment

5. Condition of Ship at Arrival

Includes the condition of ship at arrival being worse than originally anticipated dues to aging fleet, high tempo of operations and extended deployment without regular maintenance

6. Workforce

Includes capacity of having enough people, capability with the right skill sets and prioritization arranging people to address the most important maintenance, experience level, ship’s force, shipyard performance and contractor performance

7. Ships not Arriving as Planned

Includes when ship shows up at a time different than scheduled for maintenance due to operations and may affect other ships’ maintenance schedules

8. Sufficient Technical Data

Includes lacking technical papers for repairs, modernizations, and alterations, not having access due to contractor control of information

9. Effects of Deferred Maintenance

Includes effects of maintenance deferred at different points during a ship’s maintenance cycle

10. Information Technology Infrastructure

​Includes computer programs without predictive capabilities, obsolete systems, lack of processing power, inability for systems to communicate with each other, and not being able to have technology in controlled areas
 

​Developing complete baseline schedule will better assess performance against its planned maintenance work to identify causes and effects of low performance”
 
Depots have not included all its planned work in its baseline schedule for a key performance metric, experienced monthly variability in fiscal year 2019 for a variety of reasons, including parts shortages, lack of asset availability, and changing customer needs, and it is undertaking several initiatives to minimize such changes.
 
Depots are essential to maintaining surge capacity and readiness for DoD, and they play a key role in sustaining weapon systems and equipment in peacetime, as well as during mobilization, contingency, or other emergency. Specifically, depots provide materiel maintenance or repair requiring the overhaul, upgrading, or rebuilding of parts, assemblies, or subassemblies, and the testing and reclamation of equipment as necessary on weapon-system orders placed by the military services.
 
Depot maintenance is an action performed on end-items—such as vehicles, weapon systems, or other equipment, or their components—in the conduct of inspection, repair, overhaul, or modification or rebuilding of these items. Depot maintenance activities range in complexity from system inspection, to rapid removal and replacement of components, to the complete overhaul or rebuilding of a weapon system.

Depot maintenance requires extensive industrial facilities, specialized tools and equipment, and uniquely experienced and trained personnel. Given the wide-ranging variety of items—in terms of type, size, and number—on which the depots conduct maintenance, these services must engage in proactive and accurate planning.

Such planning is intended to ensure the timely availability of welders, mechanics, electricians, engineers, and other specialized personnel; to ensure that facilities are appropriately equipped and configured; and to ensure that the correct spare parts are available to complete the maintenance work.

Depots identify the detailed time frames, parts, and components required for maintenance on the end item. The depot maintenance process across the services generally involves three primary steps—planning, disassembly, and rebuilding:

Planning occurs when the depots begin to plan the maintenance needed by a particular end item.

Disassembly occurs once the depot receives the end item and is ready to begin maintenance on it. During this step, the depot workers inspect the end item and its components to determine, within the scope of work, the type and degree of repair required, or whether any of the parts require replacement. The depot workers may determine that they need to conduct different kinds of repairs based on the time that has passed, or how the warfighter has used the end item, since it last underwent maintenance.

Rebuilding occurs following disassembly, when depot workers rebuild the end item with new and repaired parts. In general, the depot workers follow a sequential process when rebuilding the end item, and this necessitates the timely availability of new and repaired parts to ensure efficient reassembly. Once depot workers rebuild the end item, they also test it and validate its use by a military unit.
 
Modernizations are approved and scheduled based on attributes such as safety and security, survivability, communications and technology, reliability and maintainability, obsolescence, warfighting, cost, and return on investment.

There are several key enablers to efficiently maintain and modernize the Navy’s growing fleet of battle force ships over the next 30 years. In order to achieve the long-range maintenance and modernization requirements in this plan based on the FY 2020 Shipbuilding Plan, the Navy must address industrial base capacity and capability, shipyard level loading, workforce and facilities investments.

For private shipyards, the Navy conducted a market survey for available and potential commercial dry docks and is developing a long-range plan to increase the number of available certified dry docks. The PSI initiatives address industrial base health and workload stability, contracting, change management and availability execution at private shipyards.

For example, Private Sector Initiatives PSI include a change in how growth and new work items are approved. Small value changes historically account for 70 percent of growth and new work, utilizing pre-priced changes will significantly reduce cycle time for approval.

The Navy is committed to working with private industry to provide them a stable and predictable workload in a competitive environment, so they can hire the workforce and make the investments necessary to maintain and modernize the Navy’s growing fleet. This will help ensure the Navy attains  best value.

The Navy continuously works to smooth the workload by addressing identified peaks and valleys in the workload. Like the private shipyards, the public shipyards benefit from a stable and predictable workload enabling them to conduct the work, train the workforce, and maintain their infrastructure.
 
Navy operates large industrial depots to maintain, overhaul, and upgrade numerous weapon systems and equipment. The depots play a key role in sustaining readiness by completing maintenance on time and returning refurbished equipment to warfighting customers. Recommendations include procedures to ensure depot input on metrics, develop guidance for depot customers, and analyze the causes of maintenance changes; and that a complete baseline is developed.
 
Navy is also improving their performance metrics in order to better manage depot maintenance. The initiative to develop a new performance metrics framework shows promise, but depot officials said they have significant concerns about how and who factor in their input when developing the new metrics. It is particularly important to develop procedures to ensure that it will incorporate depot stakeholder input into the new metrics framework for the organic industrial base through iterative and ongoing processes.
 
Doing so will allow Navy to develop maintenance-related metrics that are beneficial for helping officials at all levels to assess and improve depot performance. Moreover, Navy does not yet have a complete baseline to accurately measure the effectiveness of its planning for depot maintenance. Establishing a complete baseline will allow for better assessment how well it has planned its depot maintenance work by comparing this plan against actual performance.
 
Steps have been taken to plan and execute depot maintenance more efficiently and effectively, including several efforts to revise its depot maintenance planning process, and to analyze and address the reasons for changing customer needs. Steps have been taken to link depot planning timelines to better align resources and requirements.
 
However, developing guidance for depot customers to link these timelines would better position depots to make decisions based on the most accurate information possible, as early as possible. Additionally, systematically analyzing the causes of changing customer needs would help identify why depots experience such variability in their workload. This, in turn, would better position the service to identify specific solutions for reducing such unplanned changes.

Two primary factors for the delays were unplanned work arising during the maintenance availability, and workforce challenges such as not having enough people or having too many inexperienced workers.
 
To identify the requirements for specific ships, NAVSEA coordinates the development of a “baseline availability work package,” which represents the technical requirements needed to ensure a ship reaches its expected service life and meets its operational commitments. NAVSEA planners then use these technical requirements as a basis for developing the detailed work package, which describes the types of maintenance needed.
 
 Schedule for completion, among other things planners start developing the detailed work package up to 30 months before the start of a maintenance period. Approximately 2 months prior to the start of work on the ships, these planners finalize the detailed work package and any changes to the detailed work package from that point forward are considered unplanned work.
 
According to the Navy, detailed work packages include a reserve for new work, typically 5 to 10 percent, to account for unplanned work that is expect to materialize after the planning is completed. Further, the actual new work often exceeds this reserve, which contributes to causing maintenance delays.
 
NAVSEA officials stated that accurately planning workload requirements and the cost for maintenance periods to support Navy budgets is difficult because the Navy relies on estimates that are developed as much as 2-½ years prior to the actual beginning of work on the maintenance period. The Navy has reported in its annual risk and internal control assessments its inability to accurately plan for shipyard maintenance.
 
Beginning in 2016, the Navy reported a trend in underestimating the overall cost of ship maintenance in annual risk and internal control assessments. The assessments stated that the Navy’s policies for defining work requirements, developing cost estimates, and executing shipyard maintenance resulted in inaccurate cost and duration estimates.
 
According to NAVSEA officials, shipyard performance can include delays to work progress associated with job- specific material and equipment issues and work stoppages awaiting technical resolution. However, we identified multiple letters that specifically identified parts or materials as the cause of delays rather than shipyard performance.
 
Unplanned work-- any changes made to the detailed work package after it has been finalized prior to the start of a maintenance period, contributes to the most delays in aircraft carrier and submarine maintenance periods.
 
Unplanned work continues to cause maintenance delays and contributes to the Navy’s inability to present accurate estimates for shipyard maintenance in Navy budgets. NAVSEA officials stated that accurately planning workload requirements and the cost for maintenance periods to support Navy budgets is difficult because the Navy often relies on estimates that are developed more than 2 years prior to the actual beginning of work on the maintenance period.
 
The Navy has reported in its annual risk and internal control assessments its inability to accurately plan for shipyard maintenance. Beginning in 2016, the Navy reported a trend in underestimating the overall cost of ship maintenance in annual risk and internal control assessments. The assessments stated that the Navy’s policies for defining work requirements, developing cost estimates, and executing shipyard maintenance resulted in inaccurate cost and duration estimates.
 
Navy risk and internal control assessment indicates that these issues have persisted, stating that shipyards have had longer depot maintenance durations than expected, increased overhead costs, and reduced operational availability of Navy ships.
 
In order to improve ship maintenance planning and better account for unplanned work, the Navy conducted studies during fiscal years 2016 and 2017. In determining the parameters used to forecast ship maintenance requirements, the Navy relied on 1) outdated or inaccurate estimates in planning documents such as the technical foundation papers used to plan maintenance for specific ship classes, and 2) planning factors used to forecast ship maintenance that did not reflect actual shipyard performance.
 
In 2017, NAVSEA hosted a planning summit to discuss potential improvements to accurately planning ship maintenance. According to NAVSEA officials, prior to this summit, planning documents were formally updated on an infrequent basis when substantial changes had been identified. The planning summit revealed the need to revisit planning documents on a more regular basis.
 
Following the summit, NAVSEA established procedures for reviewing and updating planning documents on an annual basis, and immediately began updating planning documents based on the most recent 3 years of historical data to support shipyard maintenance planning and budgeting processes.
.
According to shipyard and fleet officials, aircraft carriers and submarines undergoing maintenance had longer planned durations than similar previous maintenance periods. For example, shipyard officials stated that they recently updated workload requirements estimates to extend the duration of a certain type of planned maintenance for submarines.
 
NAVSEA officials stated that they revised planning factors for ship maintenance to improve estimated workload requirements and cost factors and plan to analyze the results from the revised planning factors annually to monitor whether the changes improve estimates and to make adjustments as needed.
 
According to NAVSEA officials, they will not know whether the changes they are making result in improved estimates until work on ship maintenance periods using the revised planning documents and planning factors is complete—a process that may take several years.
 
1. Having personnel with right skills 

2.  Having the right equipment  

3. Weapon Systems arrive for repair as planned

4. Availability of spare parts  

5. Condition of weapons systems arriving for repair  

6. Having enough personnel  

7. Sufficient engineering support/technical data  

8. Having the right facilities  

9. Collecting metrics to track efficiency

​10. Carrying over unfinished work at end of year  
 
 

Acquisition of new capabilities built by Industrial base must be fielded faster transform the way military fights if it is to prevail. Results have been mixed at best, with acquisition debacles costing tens of billions of dollars and delayed necessary weapon systems for years.
 
While examples abound in each military service, we are particularly concerned with Navy shipbuilding. We believe there is a better way to develop new first-of-class ships to meet expectations.
 
Initial cost estimates were required to construct these ships, each lead ship experienced cost growth of at least 10 percent, and three lead ships exceeded their initial budgets by 80 percent or more. Further, each lead ship was delivered to the fleet at least six months late—five were more than two years late—and most lead ships had dozens of uncorrected deficiencies when the Navy accepted them.
 
A key step in successful shipbuilding programs is technology development—the maturation of key technologies into subsystem prototypes and demonstration of those subsystem prototypes in a realistic environment prior to the detailed design of the lead ship.
 
Navy must take a methodical, knowledge-based, subsystem-focused approach to guide industry to execute programs by focusing on maturing subsystems based on the mantra of “Build a Little, Test a Little, Learn a Lot.” The Aegis Combat System and SPY radar have been incrementally upgraded ever since and continue to serve as the backbone of the Navy and multiple allied surface combatant fleets.
 
 
Achieving the aims of the National Defense Strategy is a long game, so we must take the long view, and with a number of new ship classes on the horizon, now is the time to return to the methodical, knowledge-based, subsystem-focused approach that worked in the past for fielding first-of-class ships.
 
Defense leaders have called for developing and procuring the first Large Surface Combatant, Large Unmanned Surface Vehicle, Future Small Auxiliary, Future Large Auxiliary, and Light Amphibious Warship in the coming years. In addition, large and extra-large unmanned undersea vehicles will transition from research and development to procurement in the next decade.
 
Congress believes this is a critical juncture and opportunity for all of us to do better on lead ships—and with this year’s National Defense Authorization Act— are signaling their intent return to an Aegis-type development model in which critical subsystems are matured before the Navy procures the lead ship of a new class.
 
Department of Defense and Navy leaders should lead on defining the future force architecture and, just as important, personally sign off on realistic system- and subsystem-level plans. Concept development and wargaming too often ignore the technical difficulty of new capabilities and platforms, including ships.
 
Future force planning must detail requirements and notional acquisition strategies constrained by conditions-based technical development roadmaps for developing new critical subsystems and for modifying existing critical subsystems. If a subsystem is essential to the mission or mechanical or electrical performance of a platform, then we consider it critical.
 
New critical subsystems should be proven before building a full-scale platform. If a critical subsystem has not been demonstrated in the envisioned form, fit, and function, it needs to be prototyped on land or at sea as a subsystem and proven to meet at least minimum requirements.
 
Then, it needs to be prototyped with other critical subsystems with which it will interface in vessel-representative form to ensure sufficient technical and technological maturity of the system of systems. This type of process has worked in the past and is working today.
 
Some recent examples of successful DoD- and contractor-led critical subsystem prototypes that continue to provide significant benefits to both DoD and industry include: the land-based engineering site for key electrical and propulsion subsystems including control software, the land-based engineering site for the Aegis Weapons System at a contractor facility, and the full-scale prototype testing of the SPY-6 Air and Missile Defense Radar at a contractor facility.
 
Contracting for a full-scale platform prototype should occur only after all critical subsystems have been proven and should focus on system integration. Having prototyped critical subsystems and demonstrated they are fully developed and technically sound, the Navy can focus full-scale platform prototypes on subsystem integration, rather than technology development.
 
As platform integration issues arise, having subsystem prototyping already completed should enable faster root-cause analyses and corrective actions. If a critical subsystem cannot meet minimum requirements, the Navy should not proceed to prototyping a full-scale platform.
 
Keep the focus on proving all critical subsystems first. For example, until the vessel-representative engine and generator including ancillary equipment have run continuously for 30 days on a test stand, the Navy should not contract for a large unmanned surface vehicle full-scale prototype, the minimum requirement for which is operating unattended for 30 days. Without an engine that meets the minimum specifications, the ship cannot meet the minimum requirements.
 
The objective of subsystem and full-scale platform prototyping is to close DoD technical knowledge gaps. Some observers believe DoD involvement in technology development slows down innovation. Rather than slowing down innovation, the DoD technical community is key to speeding up the  adoption of innovative capabilities and, just as critically, sustaining these systems once fielded.
 
In areas where DoD expertise strains to keep up with industry advances, leaders must ensure DoD technical experts receive adequate resources to keep pace. The standard must be for DoD to maintain a cadre of technical experts as knowledgeable as any outside expert in the application of a given technology to a DoD weapon system, particularly critical subsystems. The technical support community for Navy submarines exemplifies this standard of expertise.
 
In creating the National Defense Authorization Act (NDAA) for Fiscal Year 2020, Congress contained provisions that would support this alternative approach, including: requiring the results of test programs of subsystem prototypes, as well as design changes identified during the operational test periods of the first Arleigh Burke–class destroyer in the Flight III configuration, be incorporated prior to program initiation of the next new class of Navy large surface combatants.
 
The NDAA also established a Senior Technical Authority (STA) for each class of naval vessels. Each STA is responsible for establishing, monitoring, and approving technical standards, tools, and processes for the class of naval vessels. The STA must certify the systems engineering and subsystem prototyping plans prior to program initiation of a lead ship in a new class.
 
Congress is now requiring the qualification of main engines and electrical generators capable of meeting requirements prior to program initiation for medium and large unmanned surface vessels; and a certification from senior leaders on subsystem prototyping and maturity prior to the DoD contracting with industry for certain unmanned vessels.
 
The case is clear and compelling that successful prototyping of individual critical subsystems is essential to achieving a solid technical foundation for new platforms, particularly in shipbuilding. Rather than delaying new programs, we believe this approach will enable the delivery of capable, reliable, and sustainable platforms that meet the needs of military commanders faster than would otherwise occur.
 
Leaders in the Pentagon, Capitol Hill, and industry must recognize that speeding up innovative research and development, acquiring new capabilities faster, and transforming the way the U.S. military fights will require the disciplined demonstration of critical subsystems first.
 
The stakes are real, and we have no time to waste.
 
To 10 Impacts of Reliability Criteria Influence Warfigthers Time to Field System is Available to Execute Mission

1. Reliability can significantly influence a weapon system’s operating and support costs, accounting for approximately 70 percent of a weapon system’s total life-cycle cost

2. Operating and support costs are a reflection of how programs achieve operational availability for weapon systems.

3. Programs can achieve operational availability by building highly reliable weapon systems 

4. Support with an extensive logistics system that can ensure spare parts and other support items are available when needed.

5. Deficiencies weapon systems—such as high failure rates and an inability to make significant improvements in reliability— limiting program performance and increased operating and support costs.

6. Manufacturer carries most of the risks that would result from developing a product with poor reliability.

7. More reliable products cost less because they do not have to dedicate as many resources to fixing systems that fail

8. Instead of addressing the design risk during development effectively, a standard cycle test was done to prove or disprove the risk but did not apply the stress necessary to cause the failure.

9. Product was released to the market based on inadequate test.

10. In the field, the components failed, and had to remove product from the market. This damaged the company’s reputation and sales.
 
Top 10 Design Tools Meet Development Requirements Increase Reliability Prior to Testing Identify How Long Part/Component will Function

1. Identify design flaws and enable predictions of reliability under normal use conditions

2. Use principles of statistics to plan, conduct, and analyze reliability tests in order to get the most information out of each test event

3. Use information to optimize reliability and identify a robust design well suited for a range of use environments 

4. Failure modes and effects analysis Identifies potential failures and  impact on system reliability to prioritize failures

5. Take actions based on how serious the consequences are, how frequently they occur, and how easily they can be detected 

6. Identifies and captures information about failures, which can be used to prioritize corrective and preventative actions

7. Avoid recurrence of failures in future designs, and provide a centralized location for failure data that can be used for reliability analysis 

8. Design reliability into product, perform reliability assessments, and focus reliability tests where they will be most effective 

9. Use reliability blocks to represent individual items to identify critical components and how the failure of a component or subsystem can impact reliability of the overall system

10. Reliability growth curves depicts strategy to increase reliability, useful to determine appropriate test time and number of test units for reliability targets
 
Top 10 Policy Recommendations Emphasizing Reliability Practices for Plan/Execute Acquisition Programs

1. Leveraging reliability engineers early and often

2. Establishing realistic reliability requirements

3. Employ reliability activities to improve system’s design throughout development

4. Deferred key reliability engineering activities until later in development

5. Initially pursued unrealistic operational requirements for reliability

6. Did not effectively emphasize reliability with suppliers

7. Reliability requirements must be realistic

8.  Actions based on proven technologies

9. Reflect customer usage and the operating environment

10. Cost/Schedule Constraints Negatively Influence Reliability Testing

Top 10 Plans Identify Constraints Decide on Requirements Change Criteria Return to  Reliability Planning System

1. Design Strategy must obtain economies of scale in customised productions so standard components of products have become very popular in manufacturing industry

2. In mixed prototyping concept standard parts must normally be real components since they can be found easily in stocks.

3. For some fixed designs that do not need to be changed much, can use real components through conventional rapid prototype technologies.

4. Customised parts must be evaluated and revised many times, virtual prototypes are used since flexible for modification.

5. During an assembly process impossible to connect two real components using a virtual component to obtain realistic feedback-- cannot stack a real component on a virtual component.

6. Using the largest component of an assembly as a virtual part is not ideal if several other real and virtual parts are connected to it.

7. Parts where several components are to be assembled, such as the base part, would serve better if they are real.

8. Some workspace and assembly parts cannot be completely defined and simulation is so must use real components as much as possible.

9. If prototyping cost of some components is very high, try to use virtual prototypes even though designs are already fixed.

10. Users can obtain more realistic assembly parts sensory feedback based on real components as compared to virtual component

 Top 10 Mission to Deliver Combat Power to Fleet with Enterprise Digital Capabilities/Infrastructure for Secure Work/Innovation to Enhance Users Experience

1. Avoid business disruption and take a proactive approach to promote solid digital enterprise design

2. Implement digital certificates used to the benefit of network users and the security of their communications

3. Promote workforce skills set continuity and keeping core network systems function

4. Find approaches to maximize resilience, combine across sources, locations to deliver agile response and recovery

5. Build block capabilities designed to accelerate growth/innovation and sustain multiple digital enterprises

6. Ensure integrity, security, quality and resilience of supply chain products/services

7. Identify systems/components most vulnerable with potential for greatest organizational impact if compromised

8. Support digital transformation bring about change, agility, speed, connectivity, real-time economy, customer expectations

9. Enable Practitioner to make decisions so enterprise can handle, analyze, and securely store all types of data

10. Develop digital engineering architecture using computer modeling, programming and imaging to create both virtual forms and physical structures
​

The Army is expected to release a draft request for proposals leading to competitive development of a next-generation infantry fighting vehicle. The solicitation will probably be secret, because the Army isn’t eager to alert enemies to what threats worry it most and how it plans to fight them.
 
The new vehicle, officially known as the Optionally Manned Fighting Vehicle (OMFV), will provide a successor to the Bradley infantry fighting vehicle, an armored combat system designed to safely carry a squad of six soldiers to the place in a battle zone where they dismount.
 
Bradley has been repeatedly upgraded since it first joined the force and the Army plans to continue buying the latest version until OMFV is ready for production. But land warfare has become a lot more lethal since its introduction, thanks to the appearance of everything from smart weapons to unmanned drones, so finding a successor is an urgent priority.
 
In fact, the sense of urgency was so strong that the Army tried too hard in its first effort to get a competition started. It now concedes it was overly aggressive in the capabilities and timeline it was seeking. So at the beginning of 2020, it started over.

The new approach is a break from tradition, relying heavily on digital tools to avoid the expense of prototyping until the Army is confident it has a design that meets its needs—with growth potential to cope with a constantly evolving threat.
 
The “cross functional team” pursuing a next-gen combat vehicle values as its top priority, bar none, survivability. Modern battlefields are so dangerous that none of the vehicle’s other capabilities matter much if you can’t first provide soldiers on board with the protection needed to stay alive.
 
The number-two priority is mobility, which is why the vehicle will be tracked. It has to be able to maneuver quickly in any type of terrain from desert sands to deep mud. Mobility contributes to survivability, so it isn’t hard to see why those are the top performance priorities.
 
The number-three priority is growth, meaning the ability to be upgraded as threats evolve. Bradley has been adapted over time to threats as diverse as antitank weapons and improvised explosive devices, but sometimes the response to one danger impedes effectiveness against other dangers.
 
The remaining priorities, in descending order of importance, are lethality, weight, logistics, transportability, manning and training. The Army hasn’t disclosed how it will address each performance feature in the solicitation, but in the course of engineering key objectives will need to be reconciled to arrive at an optimum mix of capabilities.
 
This is where past efforts to replace Bradley have tended to break down. The more armor you have the better the protection; but the weight of armor impinges on mobility and transportability to the battle zone, and it also impacts logistics because heavier vehicles need more fuel.
 
New tools are appearing constantly that can model and simulate how different approaches to the vehicle’s design would perform in an operational setting.
 
Vendors break out into two basic groups. One group favors the application of new ideas to traditional combat vehicle concepts. The other, non-traditional, group is thinking more expansively about how the challenge of moving soldiers across the battlefield might be accomplished.
 
New design shops are more interested in conceptualizing the future fighting vehicle than actually building it, so the iterative process the teams have laid out to get to a winner provides considerable latitude for assimilating new ideas.
 
Having largely completed the initial market research phase, it is now moving into a design phase in which up to five vendors will be funded to generate “rough” digital designs of what the future vehicle might look like. Three of those five will then be selected to generate detailed digital designs that can be precisely modeled to evaluate performance.
 
It is only after that third phase and the selection of a favored design that the Army will spend money to develop hardware prototypes in the fourth phase—prototypes that will transition into low-rate production when their merits are demonstrated.
 
This isn’t the way things are usually done. It has been an article of faith for years that early prototyping can unlock valuable insights when developing combat systems. However, prototyping is expensive, and digital engineering has now advanced to a point where the real-world performance of designs can be modeled and simulated with great fidelity.
 
That is the path the Army has chosen to follow. In contrast to buying small lots of new combat systems and sending them into operational environments to see how they fare, team is more interested in finding the one optimal solution for service’s future needs.
 
The team believes the most promising way to get to that outcome is by opening the aperture wide for novel ideas, and then see what verdict the modeling and simulation process renders with regard to their virtues. Soldiers will figure prominently in testing the new ideas, because people are what OMFV is all about. They need to have a say in how they will go to war.
 
Instead of a traditional three-man crew, team is looking at potential designs were, “you have two humans with a virtual crew member, sharing the functions of gunning, driving, and commanding.”
 
Field tests and computer models have convinced the Army that future armored vehicles can fight with just two human crew, assisted by automation, instead of the traditional three or more,
 
The OMFV is scheduled to enter service in 2028 to replace the M2 Bradley, which has the traditional trio of commander, gunner, and driver. Both vehicles can also carry infantry as passengers, and the Army envisions the OMFV being operated by remote control in some situations.
The Army has already field-tested Bradleys modified to operate with a two-soldier crew instead of the usual three and “we’ve got those Mission-Enabling Technology Demonstrators, or MET-D, actually maneuvering as part of the Robotic Combat Vehicle test.”
 
With the benefit of modern automation, those two-soldier crews have proven able to maneuver around obstacles, look out for threats, and engage targets — without being overwhelmed by too many simultaneous demands. “They’re doing that both in simulation and real world.
 
“You have two humans with a virtual crewmember that will remove cognitive load from the humans and allow the functions of gunning, and driving, and commanding the vehicle to be shared between humans and machines.”
 
“We think that the technology has matured to the point where this third virtual crewmember will provide the situational awareness to allow our soldiers to fight effectively.”
 
The defense contractors who would have to build the vehicle – even if a DoD team designs it – aren’t so sure. Some industry participants maintain “A two-man crew will be overwhelmed with decision making, no matter how much AI is added”
 
For at least eight decades, combat vehicle designers have faced a di-lemma. A smaller crew allows a smaller vehicle, one that’s cheaper, lighter, and harder to hit – and if it is hit, puts fewer lives at risk.
 
But battlefield experience for decades has shown that smaller crews are easily overwhelmed by the chaos of combat. Historically, an effective fighting vehicle required a driver solely focused on the path ahead, a gunner solely focused on hitting the current target, and a commander looking in all directions for the next target to attack, threat to avoid, or path to take. Many vehicles added a dedicated ammunition handler and/or radio operator as well.
 
A “virtual crewmember” could solve this dilemma — but will the technology truly be ready by the late 2020s?
Army started experimenting with Robotic Combat Vehicles that had no human crew aboard at all. The long-term goal is to have a single soldier oversee a whole wolfpack of RCVs, but the current early prototypes are operated by remote control, with a crew of two: a gunner/sensor operator and a driver.
 
The Army has been impressed by how well these teleoperated RCVs have performed in field trials. If two soldiers can effectively operate a vehicle they’re not even in, might two be enough to operate a manned vehicle as well?
 
The other piece of the experimental RCV unit is the mothership, an M2 Bradley with its passenger cabin converted to hold the teleoperators and their workstations. These modified M2s, called MET-Ds, also operate with just two crewmembers, a gunner and a driver – without a separate commander, and they have done so successfully in combat scenarios.
 
The Army is not just adding automation to individual vehicles. It’s seeking to create combined units of manned and unmanned war machines that share data on threats and targets over a battlefield network, allowing them to work together as a seamless tactical unit that’s far more than the sum of its parts.
 
“This vehicle will not fight alone, but as part of a platoon, a company, a battalion. “The shared situational awareness across that formation will transform the way we fight.”
 
The M2 Bradley has been repeatedly upgraded since its introduction, but after 40 years in service, the vehicle is reaching its limits.
 
These ongoing experiments are the latest in a long series. “As far back as 1991, the Army was looking at reducing the number of crew members. “Back then, the tech had not matured to the point that it would allow a two-person crew.”
 
But that was then, Three decades later, with the rise of the iPhone, Google Maps, and a booming business in artificial intelligence, the times and the technology have changed.
 
“Since then, our 360-degree situational awareness has vastly improved,” Instead of peering through periscopes, gun-sights, and slit-like bulletproof windows – or just sticking their head out the hatch and hoping there’re no snipers around – crews can look at wide-screen displays fed by multiple cameras and other sensors mounted all around their vehicle.
 
Automated target recognition systems can analyze the sensor feeds in real time, identify potential threats and targets, alert the crew to their presence, and even automatically bring the main gun to bear, but the Army still requires a human decision to fire.
 
Waypoint navigation algorithms, obstacle sensors, and automated collision avoidance routines can ease the task of maneuvering 40-plus-tons of metal around the battlefield.
 
Could all this technology unburden the human crew, allowing just two soldiers to operate a combat vehicle, instead of needing one solely focused on driving, a second solely focused on shooting, and a third giv-ing direction to the other two? The Army now thinks so.
 
That said, the newly released Request for Proposal is a draft, being circulated specifically to get feedback on what’s feasible. If too many companies say the two-person crew won’t work, the Army can still change that requirement before the final RFP comes out.
 
Vendors are learning, through their experimentation, that it’s a high-risk requirement.”But like anything else involving technology: Given time — and money — it’s achievable.”

Industry sources say the Army shouldn’t enter its own in-house design team in the race to replace the M2 Bradley, but top Army officials are confident the team would stimulate, not stifle, much-needed innovation and competition
 
After three failed attempts to replace the M2 Bradley troop carrier with better tech for modern warfare, the Army has a bold new strategy – one that could include a DoD design team competing head-to-head against contractors.
 
But why bother jumping through all these administrative hoops to get the DoD team in the mix, when other top-priority programs, from high-speed helicopters to precision-guided rifles, rely entirely on industry?
There isn’t much precedent to cite a direct example of something similar occurring.  But armored combat vehicles are a uniquely military design problem with few equivalents in the commercial world.
 
“If you look at small arms, while we do have expertise in-house, there’s a commercial industry that is very, very similar to the small arms that we’re procuring for the military.
 
“If you look at aviation, while there’s obviously some very important differences with military aircraft versus civilian ones, there’s an awful lot of similarities.”
 
“On the combat vehicle side, they’re aren’t as many similarities. “The engines that we use in commercial trucking can’t survive under armor without cooling…. Our suspension systems are not unlike some commercial construction equipment, but we drive our vehicles at much higher speeds and are generally much heavier.”
 
Army scientists and engineers have spent decades studying everything from engines to armaments, from automated targeting systems to complete concepts for new vehicles. “We’ve got DoD folks that are really experts on combat vehicles and have good ideas.  “This phase primarily is generating ideas… potentially some innovation from inside our own halls.”
 
A DoD team might compete in later phases of the program – not just in developing “preliminary digital designs,” the subject of the draft RFP, but potentially in building a physical prototype vehicle as well. Actual mass production, however, would definitely be up to the private sector.
 
DoD has got the ability to build prototypes. “The challenge would be the transition from an EMD [Engineering & Manufacturing Development]-like prototype into a production asset. That’s something, typically, DoD has not done.
 
So the DoD team might need help crafting a sufficiently detailed design that a contractor could actually build a working vehicle from it. Conversely, the manufacturer would have to set up their supply chain and production line without the benefit of having done a prototype beforehand.
 
With the new mandate for a two-man crew and the proposal for a DoD design team industry is saying “just when the Army has finally asked industry to come up with a solution rather than dictate it to them, it seems they have signaled what they really want to do is dictate the solution.”
 
Some in industry are not in agreement with the Army on the acquisition strategy. They maintain DoD thinks there are companies that would welcome the DoD business to mass-produce a DoD design, and they are  skeptical of a build-to-print proposal when the company doing the production has little invested in the design.
 
But Army officials have argued that they’ve set the competition up to let industry participate at minimal risk. Industry would submit a proposal, and then DoD is paying them for their initial design.
 
But what if a company feels it’s not competitive without investing its own Independent Research and Development (IRAD). That’s a question for industry, but that is not the intent of the program. “We’re trying to reduce risk for industry.”
 
The Army wants a wide range of competitors – definitely from industry, but perhaps in-house as well – to offer the widest possible range of ideas. OMFV could resemble a Bradley rebuilt with the best available 21st century tech, or it could look nothing like a 20th century Infantry Fighting Vehicle at all.
 
Army says industry has a choice. “Industry can use a traditional IFV model… or industry can provide a different manner in which we will transport our infantrymen on the battlefield.
 
We are probably going to see a lot of unique solutions to the problem.”
 
The biggest technological innovation the Army’s seeking: replacing the three-man crew used in the Bradley – and almost every comparable IFV worldwide – with just two crew members assisted by AI. Why the Army thinks that’s achievable, and why some are skeptical is going to be a drama.
 
The full order of the priorities for the OMFV characteristics is as follows:

1. Survivability
   
2. Mobility
   
3. Growth  
4. Lethality
   
5. Weight  
6. Logistics
   
7. Transportability
   
8. Manning
   
9. Training
   
10.  Digital

 

“We have to stop using industrial age measures when using information age capabilities. Assessment tools have to keep pace, especially considering the advent of joint all domain operations.
 
Under the concept of all-domain warfare, “platforms don’t exist as a single entity.  “A weapons system can be used, for example, as a node to relay information or provide lethal effects on the battlefield.”
 
Pentagon should not judge weapon systems on “overly simplistic metrics” but adopt a more holistic evaluation that weighs a weapon’s cost and capabilities against the total costs of achieving the mission.
 
“All we ever hear is, that the F-22 and the F-35 are expensive. But is that really the case if a handful of them can accomplish what it otherwise take dozens of less capable aircraft to achieve?”
 
When we think about costs our goal should be to use the least amount of force to yield the greatest result. A new approach dubbed “cost-per-effect,” has been proposed for determining a value for high-end weapon systems, in particular fifth-generation and future combat aircraft.

Services should consider including harnessing cost-per-effect assessments as a key performance parameter within the Department of Defense’s Joint Capabilities Integration and Development System (JCIDS) requirements process.”
 
“A cost-per-effect assessment measures the sum of what it takes to net a desired mission result, not just a single system’s acquisition and support costs without necessary context surrounding the capability’s actual use.”
 
The Case for Cost-Per-Effect Analysis,” argues that the current evaluation process especially short-changes highly effective fifth-generation aircraft.
 
“Current measures favor lowest up-front per-unit cost (an ‘input’ measure) for a piece of equipment that may only address one facet of the kill chain without taking into consideration the mission-effectiveness of the particular system (an ‘output’ measure).
 
Applying a cost-per-effect assessment would help DoD make better choices when considering how to resource different service programs aimed at achieving similar effects like beyond-line-of-sight targeting.
 
The goal is to reset the baseline by which modern combat aircraft are judged as worthy in annual DoD budget battles.
 
The fifth-gen F-35 fighter, for example, currently is estimated to cost a whopping $35,000 per hour to operate; and each of the planes priced out at $77.9 million at the end of last year after years of much higher costs per unit.
 
DoD asked Congress for $11.4 billion for 79 of the Joint Strike Fighter variants, but Congress is fighting over whether to cut the program or pump it up.
 
Air Force should “prioritize solutions that yield maximum mission value and not rely on overly simplistic metrics, like cheapest per-unit acquisition cost or individual cost-per flying hour, as these may actually drive more expensive, less capable solutions.”
 
“Cost-per-effect” is defined as: “The total cost involved with achieving a specific mission outcome. This includes mission aircraft to execute the actual task, as well as direct support assets. These include aerial refueling tankers, electronic jamming platforms, and surface-to-air missile suppression efforts. It also includes aircrews and requisite infrastructure like basing and related maintenance support.”
 
“Strengthening Understanding of Industrial Base Capacity to Supply Product Provides Ability to Plan for More Realistic Estimates of Weapons Systems Utility/Effect in Future Missions”

New facility to expand the production of long-range standoff missiles, including the Joint Air-to-Surface Standoff Missile-Extended Range. This site is intended to help meet the demand for “large ongoing and expected orders” of air- or sea-launched standoff missiles.
 
For the site to meet expectations, the Pentagon needs to increase visibility into the supply chain supporting the production of these key munitions. Investments like the new site are a first step. But DoD needs to ensure the underlying industrial base can support the surge production of not just one munition, but multiple munitions systems simultaneously.
 
The knowledge and insight to properly assess industrial base capabilities requires not only data collection and curation, but the development and deployment of analytical capabilities designed to identify potential bottlenecks and offer strategies for mitigating such risks.
 
Inadequate inventories of long-range missiles have proven to be a contributor to unfavorable outcomes in recent wargames. In those simulations, we “run out of munitions fast,” hindering their ability to prevail in some scenarios.
 
Some experts warn that under current readiness conditions “U.S. could face a decisive military defeat.” The situation becomes more dire when considering a protracted conventional war, requiring a sustained surge across a number of munitions systems that rely on highly consolidated, and often fragile, supply chains. This is not a problem limited to munitions, as “America’s defense industrial base is designed for peacetime efficiency, not mass wartime production.”
 
The Defense Department needs more standoff munitions. But just as important, it needs the capability to recover quickly if its munitions reserves are rapidly depleted. Prohibitively long production lead-times of most key precision-guided munitions makes this proposition extremely difficult. The military requires an industrial base capable of maximizing production of a number of munitions simultaneously.

Currently, the Pentagon doesn’t have a department-wide understanding of the surge capacities and constraints in the defense industrial base. While individual program managers may understand the individual systems for which they are responsible, they are rarely aware of potentially competing demands.
 
The lack of leadership could create bottlenecks if a number of systems, some built on shared production lines, need to surge simultaneously. Military readiness plans should systematically account for industrial base realities that dramatically affect surge. Specifically, planners should consider risk factors like shared and limited production of select systems and components, sole sources, and foreign dependencies.
 
Without an enterprise-wide view of munitions challenges and possibilities, senior decision-makers will almost certainly be misinformed about the readiness and recovery risks facing the country.
 
The need to better plan for an unexpected disruption in the munitions supply chain is not new. As the past demonstrates, mobilization takes much longer than expected. Whether it’s unintentional e.g., industrial accident or deliberate e.g., kinetic attack, coercion, decisions not to export high-demand items, the United States cannot count upon having much time to prepare for an urgent threat. Rather, it needs to invest ahead of time to be able to surge production of different items at the same time.
 
For many items, and munitions in particular, investing in additional system integrator-level production may not be enough. System integrator facilities bring together all of the component and sub-component systems required for final missile assembly. They require sufficient inputs of components — inputs received on time and of requisite quality — from their suppliers in order to take full advantage of final assembly at maximum production rates.
 
The problem of not receiving all the needed components is often exacerbated at lower tiers of the supply chain as components become more specialized, often provided by very few, or perhaps, by one producer — a single point of failure.
 
Military planners frequently underestimate the time needed to achieve readiness. One reason is that they don’t take a realistic account of lower-tier capacity constraints and the competing demands for shared components. Additionally, unanticipated supply disruptions, like not being independent on components and materials, can make matters worse.
 
Several years ago, the Army’s expanded budget request for precision-guided munitions successfully stimulated a staffing and facility expansion where solid rocket motors are used in different precision-guided munitions.
 
This essential missile component has been a source of concern for the Pentagon. There are currently only two domestic suppliers of solid rocket motors used in the majority of the military’s missile systems, with foreign suppliers making up the balance for a small number of systems.
 
Surging the production of multiple systems at once may not be possible if an essential system component is provided by a single supplier. The inability to fully produce all munitions at maximum capacity could lead to internal conflicts within the Defense Department regarding which missile system takes priority. Understandably, warfighters want the munitions called for in operational plans, not simply the one that’s ready at the moment.
 
Supplying field-level troops with weapons requires a fundamental restructuring of industrial base planning and preparation practices. The Pentagon needs to build and aggressively maintain an enterprise-wide common operating picture of high-priority, precision-guided munitions supply chains. A continuously refreshed picture of these supply chains will help the military understand competing demands, bottlenecks, and potential supply disruptions at the lower tiers.
 
Today, individual munitions program managers do not systematically provide information to a central office in the Pentagon that can compare current and planned usage with the capacities of system integrators and component producers. The appropriate office to collect data on usage and capacities, especially among lower tier producers, is likely the deputy assistant secretary of defense for industrial policy.
 
Doing so would allow such information to be integrated and assessed continuously. It would also provide DoD planners and senior decision-makers with a more comprehensive picture of munitions readiness and how it is affected by competing demands and capacity constraints. According to the current National Defense Strategy, this is an increasingly important picture for the military to have in order to be able to act at the “speed of relevance.”
 
To construct a comprehensive picture of munitions readiness, the Defense Department needs to collect sufficient industrial base data and deploy advanced analytical tools to process the data. Using data and tools in tandem is the key to enabling analyses that identify supply chain bottlenecks, model outcomes of potential surge scenarios, and offer mitigation options.
 
While the Pentagon already has quite a bit of data, these data are not yet integrated to enable a department-wide view of supply chain capabilities, constraints, and cost-effective mitigation actions. Nor are the data structured in consistent ways for such purposes.
 
DoD already has several types of integrating analytic software available that can serve as the foundation for timely evidence-based assessments and investments of the sort decision-makers need. However, leveraging existing analytic tools requires institution-wide support and an overarching framework to collect and curate industrial base data and generate key outputs, especially realistic estimates of the time and actions needed to achieve readiness, on a continuous basis.
 
Developing and using a common operating picture for the Pentagon’s munitions data will be difficult. However, this kind of innovation could have several tangible benefits by generating a better understanding of supply disruption problems; identifying surge opportunities and limitations in mobilization and recovery scenarios; encouraging innovation to maintain and expand production capacity; targeting lower-tier suppliers that need investment to alleviate bottlenecks and maximize production; and offering realistic estimates of the time needed to achieve readiness targets.
 
Realistic estimates are a critical metric for war planners, particularly if supplies are disrupted. These forecasts will help inform back-up plans that may be needed in the event of munitions shortfalls.
 
Tasking warfighters with revising operational plans may be met with some resistance, but it’s one of many possible decisions that could be made to minimize the risk associated with insufficient inventories and to prevent the conflict from escalating beyond conventional weapons.
 
Such decisions might require the substitution of one missile for another when realistic estimates of the number of munitions actually available during a conflict indicate supplies are limited.
 
The Defense Department should develop an integrated department-wide issue paper for precision-guided munitions to inform the future years defense program development process. This type of directive paper would give decision-makers realistic assessments of the industrial base by integrating demands, supplies, and constraints for a portfolio of munitions, rather than a collection of missile-by-missile assessments.
 
DoD should also consider requiring system integrators to provide key capacity and component supplier data to the Pentagon as a condition of their future contracts.
 
The military should also base operational plans on realistic estimates of inventories for critical munitions. In this arena, the combatant commanders need to know how quickly they can expect to obtain more priority munitions in a crisis or major surge scenario.
 
Specifically, they need to be sure that estimates take account of competing demands at the lower tiers. Furthermore, combatant commanders should be made aware of foreign reliance for key components and materials at the lower tiers, particularly if that reliance is linked to likely adversaries in the crisis, and whether or not they are accounted for in estimates of time to readiness.
 
Realistic estimates are needed to properly configure war plans, including plans that account for potential munitions inventory rebuilds in a post-conflict environment.
 
DoD planners need a practical action plan to collect, integrate, and analyze the right kinds of data to develop the budget. The military would be better positioned to meet key readiness, mobilization, and recovery challenges in this new era of strategic competition if it develops and maintains a common operating picture of key precision-guided munitions and their underlying supply chains.
 
Taking this type of enterprise-wide approach will ensure that new manufacturing sites meet expectations to help the United States prepare for and recover from potential future conflicts. And, if done right, this approach could serve as a model for a more integrated treatment of supply chains in other key parts of the defense industrial base.
 
Several factors should be taken into account by the Air Force in developing such an assessment. First, and foremost, the overarching focus of all missions for “future high-end capabilities” should be on peer conflict.
 
Other factors include:

1. Precision effectors, both kinetic and non-kinetic 
2. Survivability
3. Stealth     
4.  Electronic warfare  
5. Sensors  
​6.  Processing power  
7. Communication links  
8. Fusion engines  
9. Real-time command and control (C2)  
10. Aircraft range and payload