Automation has allowed supply chain operations within companies to perform tasks with minimal human intervention or interaction. Automation methods vary significantly in size, functionality, dexterity, intelligence and cost, from robotic process automation to flying vehicles with artificial intelligence.
Traditionally, automation and robots have been deployed for executing routine and repetitive tasks, requiring complex programming for implementation, while lacking the agility to easily adjust operations. As the automation technologies have become more sophisticated, set up times are decreasing, requiring less supervision and are allowing for the smooth integration and transformation of legacy supply chain systems.
The phases within traditional supply chain systems all acted as autonomous phases that had minimal visibility into the other segments of the chain, whereas, with automation, the supply chain is streamlined from end-to-end, enabling all different piece of the chain to be managed in tandem.
“As supply chain operations continue to shift focus to direct customer needs, autonomous robots can serve the end consumer with better service and faster response times. Emerging advancements in technology such as autonomous trucks, 3D printing and warehouse automation will foster changes in how shippers, retailers and manufacturers configure their supply chains and distribution strategies. The advancements will encourage industrial users to embrace and modernise their materials handling capabilities to meet the growing market demands.
The time for companies to assess their supply chains for piloting autonomous robots is now. Depending on needs and existing capabilities within the supply chain, implementing autonomous robots—from robotic process automation to self-guiding vehicles with artificial intelligence—can provide significant improvements in productivity and efficiency, while reducing labor costs and improving customer satisfaction.
While automating tasks is a much more convenient and efficient way to manage a supply chain and does provide immense benefits, managers and leaders within an organisation may prefer to be able to track specific actions and outputs. For that reason, many automation solutions provide a comprehensive & customised dashboards that give leaders visibility into all the necessary data and processes.
Even while most industries got on board years ago, logistics has been a bit slower to implement and reap the rewards of big data. Granted, the industry already leverages big data in a multitude of ways, but it is unquestionable that it could be better utilised to advance the industry even further. It’s necessary to have the right data in the right format at the right time available for all stakeholders. Establishing metrics facilitates this process by providing the vital data cleansing and predictive optimisation that logistics companies need to succeed.
Forecasting every aspect of the supply chain surely isn’t the easiest task, so more, accurate data, along with a platform that visualized that data, would be useful for better executing supply chain strategy. Recording data on every aspect of the business is the number one opportunity when we think about big data in terms of supply chain management. Exploiting every piece of data from every single step of the supply chain can bring immense value to businesses. It will ensure end-to-end visibility for all parties, greater efficiency, and optimis ed digital processes.
One way to acquire digital intelligence is by having data available from all aspects of the supply chain including manufacturing, e-commerce and retail data too will make it easier to improve processes and better plan for the future. However, the raw data itself is not enough, you have to transform the raw data into actionable insights which can be shared with all relevant stakeholders across the supply chain in a timely manner.
You need to find platform tools to make sense of the data – and you might want to be able to integrate it into your own systems to see all the information in one place. You also need to ensure that all your systems and devices are transferring data to you in your preferred format.
The insights that you gather may not only be useful for you, but also for your partners. At the end of the day, this type of data sharing in logistics can help to improve operational efficiency by capturing fluctuating customer demand, external factors, and the operations of your partners. It will improve transparency and help all stakeholders to streamline their processes, ultimately improving the quality of your processes, and the overall performance of your business as well.
As you gain more control over every aspect of your business, from optimising resource consumption to improving delivery routes, the increased efficiency will allow you to speed up your operations improve customer retention, and increase resolution of objectives. However, you certainly need to evaluate what data you can and want to share with your partners. Only some data will result in a win-win situation where the processes and solutions of both parties benefit. Tools already exist to foster business collaboration through this type of data sharing solution.
Clearly, big data itself is not enough. When you receive raw data in bulk, it’s not very useful. You must also have data processes in place to ensure the adequate storage of the data, comply with all the regulations and security, and ensure that the quality of the data is flawless, so you can validate and enrich it.
Once the data is validated you can create actionable insights for any number of purposes: improving partnerships and cooperation, managing external factors and risks, optimising routes, schedules, and deliveries, making sure you deliver everything on-time and boost customer satisfaction, and, ultimately, improving operational efficiency and becoming more profitable.
You can implement quick connections and message translations between supply chain partners and customers. Integrating with carriers, shippers, and the systems that they use to increase speed and agility. This seamless real-time flow of 100% accurate data, provides organisations the ability to analyze and optimize all supply chain processes.
It has been a long time since the supply chain has simply been a way to produce and deliver a product. It’s probably the primary source of competitive advantage within vehicle industries. The intelligent and connected supply chain builds upon network connectivity to integrate the latest digital technologies in a way that can transform every element of your business.
Connected supply chains enable growth through an extended digital world that unites employees, trading partners systems and things. You can boost your competitive edge with machine learning-based advanced analytics to predict outcomes, optimise and automate business operations, and take informed decisions.
Predictive maintenance is one example: Being able to predict when a part of sub-system of a serviceable product is likely to fail is a key investment area for the supply chain. Whether that part is within the production process, within the warehousing environment or part of a connected vehicle, an intelligent and connected supply chain can automatically monitor and analyze performance to boost operating capacity and lifespan. This system can intelligently decide whether the part needs to be replaced or repaired and can automatically trigger the correct process.
Another example is Proactive Replenishment. Reducing inventory levels while improving customer experience requires the ability to automate much of the replenishment process to continuously monitoring stock levels and re-stock as levels drop or demand grows. The connected supply chain provides real-time inventory visibility. As well as stock levels, it can indicate the condition of each item to ensure the quality of items. You can automate the replenishment of parts from the supplier before they are needed in the production process.
Supply chain visibility is key. Knowing where exactly an item is, what condition it is in and when it is going to be delivered is of vital importance to all supply chain operations. While the previous generation of tags and sensors could provide some information on location and condition, it was very limited. The connected supply chain provides improved end-to-end visibility of shipments ‘from floor to store’. It enables the continuous flow of data from highly connected supply chain ‘assets’ at every stage of the process. This includes tracking and monitoring improvements in ‘last mile’ delivery.
The concept of autonomously delivering products is slowly starting to become a reality. While there are many hurdles to overcome before the point is reached where there's no human intervention in the supply chain, there are many industrial examples that indicate it's feasible and practical.
An autonomous supply chain has the capability to process a request to grab a component from its location and to autonomously deliver this component to a specified delivery point, all without human intervention.
Key elements of such a system include the ability to: Interpret the request, Find the part's location, Load the part onto a transportation system, Identify the delivery point, Transport to the delivery point, Off load the part and provide feedback to the supply system. If all steps are automated and do not require human intervention, then the supply system is autonomous.
Is an Autonomous Supply Chain Feasible? In a real-life situation, an autonomous supply chain needs to be able to process thousands of requests, often in a very short period of time. It also has to have the ability to find different components and transport them automatically to multiple delivery points.
From this definition, it's clear there has to be a high degree of order and standardisation. Additionally, the entire process needs to be supervised by incorporating a comprehensive database that knows the location of every part and delivery point. It has to be able to compute the best route to the delivery point and to avoid congestion.
Provided these conditions can be met, an autonomous supply chain is feasible. There are many examples where such systems can be found. What is still far from feasible is an autonomous delivery system that's able to work outside of a rigidly controlled environment.
Manufacturers have been taking steps to organise and control their manufacturing processes for a long time. These systems possess the raw intelligence needed to identify the parts required to assemble a complete article, such as a motor vehicle. In fact, most systems are sophisticated enough to allow different products to be manufactured, in any sequence, on a single line. It was a relatively small step for manufacturers to organize automated and semi-automated delivery of components from the incoming goods warehouse to the production line, as and when required and in the correct sequence.
Tools used by such systems include Part identification: Machine-readable sensors and barcodes to physically identify components, Robotic picking: Automated forklifts to locate and fetch items, Intelligent transportation: The use of autonomous vehicles as well as transportation conveyors to deliver parts to specific locations, Feedback: As components are used, automated orders raised for new components.
Most of the interest at present is on the autonomous delivery of goods from suppliers to customers. This is things like drones dropping parcels off to mobile ground troops and platoons of trucks driving autonomously on highways.
Currently, all such systems are still in development, especially in terms of mass deployment. Still, many exciting ideas are being evaluated. A drone linked to a delivery truck that flew autonomously from the delivery truck to drop off a parcel and return while the truck continued on its route was tested. Other exciting concepts include autonomous ships sailing the oceans and the use of autonomous delivery robots.
Artificial intelligence is taking up the pace when it comes to global logistics and supply chain management. As per a number of executives from the transportation industry, these fields are expected to go through a more significant transformation. The on-going developments in the areas of technologies like artificial intelligence, machine learning, and similar new technologies have the potential to bring innovation to these industries.
Artificial intelligence comes with computing techniques which helps to select large quantities of data that is collected from logistics and supply chain. You can put such methods to use, and they can be analyzed to get results which can initiate processes and complex functions.
The efficiencies of the company in the areas of network planning and predictive demand are getting improved with AI capabilities. Companies get to become more proactive by having a tool which can help with capacity planning and accurate demand forecasting. When they know what the market expects, they can quickly move the vehicles to the areas with more demand and thereby bring down the operational costs.
To avoid risks, anticipate events and come up with solutions, now techs are using data. The data helps companies to use their resources in the right way for maximum benefits, and artificial intelligence helps them with it more accurate and faster manner.
You can’t talk about artificial intelligence without mentioning robotics. Even though robotics is considered as a futuristic technology concept, the supply chain already makes use of it. They are used to track, locate and move inventory within the warehouses. Such robots come with deep learning algorithms which helps the robots make autonomous decisions regarding the different processes that are performed in the warehouse.
Apart from robots, artificial intelligence is also about big data. For the logistics companies, Big Data helps to optimise future performance and forecast accurate outlooks better than ever. When the insights of Big Data are used along with artificial intelligence, it helps to improve different areas of supply chain like transparency and route optimisation.
For AI in the logistics industry, coming up with clean data is a huge step, and they cannot implement without having such usable figures. It is not easy to measure efficiency because data comes from different sources. At the source level it is not possible to improve such data, and so algorithms are used to analyze data, enhance the quality of data, identify issues to attain transparency which can be used for business benefits.
When you are moving cargo across the world, it is always good to have a pair of eyes to monitor, and it can be best when it comes with state-of-the-art technology. Now you can see things in a new way by using computer vision which is based on artificial intelligence for the logistics.
Autonomous vehicles are the next big thing that artificial intelligence offers the supply chain. Having driverless trucks can take a while, but the logistics industry is now making use of high-tech driving to increase efficiency and safety. The significant change is expected in this industry in terms of assisted braking, lane-assist, and highway autopilot.
AI provides the supply chain with contextual intelligence which can be used by them to reduce the operating costs and manage inventory. The contextual information helps them to get back to the clients quickly.
Companies make use of AI along with machine learning to get new insights into different areas which include warehouse management, logistics and supply chain management. Some of the technologies used in these areas are AI-powered Visual Inspection to identify damage and carry out needed correction by taking photos of the cargo by using special cameras and Intelligent Robotic Sorting to sort palletized shipments, parcels and letters.
The opportunities to integrate autonomous drone logistics exist at every stage of the supply chain, where improved efficiencies, lower costs, safer work environments, and higher productivity levels are just a few of the returns organisations are seeing from their logistics drone investments.
Either your organisation prefers highly automated rules-based system to get supply chain work order request into hands of a technician virtually automatically, or a more manual system where Help Desk Dispatchers make decisions about when and who handles a particular work order.
1. Create, receive and route application-based work requests: Work request is basic communication tool for reporting supply chain problem so action can be initiated to get it fixed.
2. Obtain approvals as part of workflow if necessary: Generate workflows to mirror organisation processes for getting supply chain work done.
3. Receive supply chain alerts on critical issues in workflow: Allow for prioritising work must to be done and ability to work orders.
4. View comprehensive list of work orders in process: Provide supply chain activity feeds, grids and reporting capability to see what work has yet to be completed and how long work in backlog.
5. Highlight overdue work, or sort work orders on place, space, asset or technician basis: Offers supply chain tools and reports so available information to keep the operations running smoothly.
6. Link related work orders: Being able to group work orders allows for more efficient assignment of supply chain work to be done.
7. Attach drawings and specs, etc.: See drawings, pages of repair manuals and other documents to speed up supply chain and maintenance process.
8. Define supply chain schedule: Schedule work to be done so field-levels can submit work requests or query requests to see when it will be done.
9. Create and update supply chain Task Schedule of pending work orders: Use task schedules to keep track of what work is being done and when.
10. Schedule proactive supply chain Jobs: Any work request can be made repetitive by filling out additional checks defining dates, times and frequency; add reminders
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