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From a factory floor to the shop door, a product traverses the world to get to the end customer. It’s easy to narrate, but quite sophisticated to execute. Logistics management has always been a predicament for managers; the conventional methods are mostly inefficient and as the scale of the organization increases, the likelihood for the resources to be mismanaged becomes higher. This means inefficient operations which lead to increased production cost which in turn translates to the higher price that a customer will have to pay. What’s the solution, you ask? The advent of the Fourth Industrial Revolution brought with it a solution; Artificial Intelligence (AI) and the Internet of Things (IoT).
IoT is essentially a network comprising of electronic objects embedded with sensors and actuators. With the support of technologies like Light Fidelity (LiFi), Near-Field Communication (NFC), Radio-Frequency Identification (RFID), Bluetooth Low Energy (BLE), Low-power wide-area networking (LPWAN), LTE-Advanced, and Real-Time Location System (RTLS), organizations can enable IoT to enhance their operations.
In logistics management, IoT enables detection of each product in a warehouse, its exact location and physical attributes. These features of IoT help a manager in optimizing the resource usage in a factory. AI enabled IoT will enhance your logistics in planning, employing and allocating resources through machine learning, predictive analysis and self-training algorithms. Imagine that you are a manufacturer of dairy products. You receive the raw materials from your dairy farm which is then brought to the plant for processing. Once the products are ready, they are sent to the packaging unit and from there it is shipped to suppliers all over the world. So, how can this process be improved? In the first step, IoT can keep track of all the raw material in storage in terms of where it is, what quantity is available and how long it’s been there. Then, AI can make a note of all the available data and predict strategies for improving the inventory management, resource planning etc.
Let’s look at how logistics management can be improved with the help of AI enabled IoT.
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From the moment an inventory order is placed, there needs to be a continuous monitor on the raw materials that are to be relocated from the vendor to the manufacturer. This can be enabled and surveilled using an IoT system powered by AI.
Each pallet of your raw materials is tracked with a Real-Time Location System (RTLS) from all vendors. This way everything that arrives at the production house can be tracked. AI will account the insights of each pallet based on its location, quantity and quality so as to make a detailed analysis that will benefit the user. By enabling AI in this system, you’ll know the number of pallets being transported to the warehouse in advance and so in case of any delay, a Plan B can be strategized automatically to save time.
RTLS locates and monitors the product that arrives at the facility and prevents it from being misplaced and misused. At times, accidentally your driver or another employee can mess up the inventory at the time of delivery. Each of these incidents will be recorded by the AI to make a detailed analytics that will predict and alert the user about an incident based on the past data of mismanagement. Machine learning also offers data analysis to learn which carriers have moved what freight in the past at what cost and service level. This way an automated system could account for any such human errors and ensure that the right resource goes in the right place at optimum cost.
The laborers within the production plant will be notified about the product that has to be produced based on the demand analysis done by Artificial Intelligence. Using IoT, each material can be tracked and be put into use without any wastage of time. The then properly placed products will be monitored by AI for collecting data regarding the material usage of each product which will be notified to the logistics manager. Any excess resources will be recognized by AI and each data will be recorded for preparing analytics that will be implemented in preparation of a better inventory control process. This enhances the prime utilization of resources.
The actual job of a logistics manager begins once the end product is ready. Machine learning serves solution in unraveling the hardships of managing a final product. When this intelligence is combined with IoT, the system will be semi-automated which will reduce the workload by a significant margin. Imagine a situation where a package of fragile products is packed, but accidentally one carton flipped on its way to the truck, in this case, a computer vision enabled IoT system can ensure the alignments of the package. Moreover, AI algorithms such as Genetic Algorithm can guide you optimize your resources
Materials after production, when moved inside the facility for assembly, can face issues of mismanagement before packaging. Since each product cannot manually be monitored all the time, there can happen an incident of inefficient management. An IoT locates and monitors the movement of finished goods inside the facility with RTLS, and AI guides each unit until the packaging is complete. With the right amount of technical resources including supercomputers and smart chips, a rapid AI system can be implemented which will give an update on each unit of the product. Each pallet of the product will be routed safely to the packaging unit and every related employee will be instructed about the packaging requirements and its associated processes.
An IoT enabled tracking system will help you evaluate the temperature, humidity and other physical conditions of the location where your product is placed and AI will provide a solution if there is any pertinent issue. Safety and security of the product will be ensured by implementing automatic door locking and theft detection. AI will run a diagnostics test on the products that are packed which will remove any damaged units from the entire stocks. Machine Learning will enable a contact between the resources that are packaged with the transport facility where they are to be loaded using NFC, LPWAN and LTE-Advanced technology. Once all the shipment process are formulated by AI, the employees in the organization will be alerted about filling the shipment in the best possible sequence.
When you are engaged in transporting finished products from point A to point B, you should be aware of the precise location of your vehicles for security and compliance reasons. With RTLS, AI will account for the traffic in the route of the shipment and it will plan routes based on peak traffic hours, maintenance, and construction. This algorithm in machine learning will predict, analyze and schedule a system that will minimize the load cost for all parties involved in the consignment. The person transporting the shipment, their immediate associate and other employees involved will all be connected to the system. This hence will enable a systematic tracking of the shipment. Misplacement or confusion in the delivery will easily be eradicated with this process.
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Even if the logistics management is fast in an organization, it is never optimized. The conventional procedure’s miscalculation of resources is simply the reason for this issue. But an IoT enhanced by AI can simply unravel the shortcomings of this system and optimize its processes. With the application of strong analytics, optimized traffic and perfect warehouse management logistics can be controlled and routed perfectly. Using advanced technologies of positioning, transmitting and rendering, machine learning can help in implementing a system that reduces the human efforts in compiling and interpreting various aspects of logistics management. When implemented across the entire logistics unit, this can simplify every process associated with logistics management.
