Artificial intelligence and machine learnings are a major part of our lives today. These technologies pan across different industries including the supply chain. In the previous blog we mentioned how AI is reshaping procurement, another domain that AI is having major impact is Logistics. AI allows companies to make optimum use of their resources by preventing errors and reducing wastage of resources. AI allows businesses to forecast opportunities and prepares them for challenges that they may face. Thus, making businesses future proof.
In our article, we will discuss six use cases in logistics and also provide examples of a few companies that are already integrating artificial intelligence and machine learning to achieve greater results.
6 ways artificial intelligence and Machine Learning can impact Logistics and Supply Chain:
Demand forecasting using AI
Striking a balance between the demand and supply is crucial for every business and AI allows companies to make their supply chain more efficient by forecasting the demand for products. From the historical performance, AI is able to provide comprehensive analytics on all aspects that could affect the demand. This insight allows businesses to make the right decision and focus on strategic initiatives. Traditional methods of forecasting have a narrower output since they are using techniques that consider lesser factors that influence demand. Whereas AI and ML allow the business to get a much more robust outcome through integration.
Warehousing Automation using AI
Warehouse operations are being hugely impacted by AI as it is transforming all areas starting from data collection to inventory management. (cite) AI helps make warehousing processes much more streamlined thus making it more profitable. As earlier mentioned since AI can assist in predicting demand for products it allows the shipping of products whose demand has been forecasted to their regional warehouse thus lowering the expense of transportation. Studies show that 30% of the warehousing jobs are going to be fully automated in a few years.
AI in warehouse operations allows repetitive and transactional tasks that consume a lot of time daily to be automated. This allows businesses to make better use of their resources. The main feature of an automated warehouse is the computer vision which can identify and manage the inventory. These newer systems are self-sufficient and businesses can manage quality control without human intervention. Irrespective of the businesses are big or small, whether the company has one warehouse or multiple, AI can connect all the warehouses to find the optimum solutions for the transportation of products.
AI in Logistics and shipping: Autonomous Vehicles
The shipping part of logistics seems the simplest part as the process only needs goods to be delivered to a certain place but it in fact isn’t that simple. Shipping involves many restrictions like the amount of time a driver is allowed to driver without stopping. A driver can only drive a certain number of hours and needs to stop after reaching that number post which he can either halt for a break or be replaced by another driver. The obvious solution would be having two drivers on a truck so they can keep interchanging but this again is quite expensive for businesses but also depending on just one driver and waiting for the driver to take a break and resume driving can significantly delay shipping.
Both these options could have a damaging impact on companies especially in today’s day and age wherein there is extreme competition. Autonomous vehicles aid in fixing this issue and not just saves time but also allows businesses to become more profitable. AI now is developing self-driven vehicles which would immensely reduce transportation costs. These self-driven trucks can work with or without human interactions. Currently, many countries have mandated the use of a driver in a truck but this decision is subject to change in the future.
Waymo was the first company to integrate self-driven cars in commercial cab service. They launched it in 2018 December in Arizona and their next target is self-driven trucking.
Rolls-Royce is also working with Intel to develop self-driven ships since 2010. In 2018 they launch an Intelligence Awareness system that can identify nearby objects in the water, pick the fastest route, and also handle engine conditions. The autonomous ship industry is expected to reach $13.8 billion by 2030.
Integrating driverless trucks would be really advantageous for the logistics domain. These trucks would help businesses reduce their fuel usage, optimize their routes, and also reduce transportation time. In addition, it would also eliminate human errors.
Use of AI in developing Smart Roads
Just like vehicles are getting smarter and thus self-driven, AI can be also making roads smarter. Companies today are working towards making smarter roads and offer solutions depending on regional needs. Hence in certain areas highways are built with solar panels and LED lights. These roads can generate electricity and also utilize the lights to inform and alert drivers about changes in road conditions. Also, as solar panels are heated it would prevent the road from becoming slippery during winter. This would help the logistics domain by avoiding delays caused by weather conditions.
The company Integrated Roadways has created the smart pavement system. Colorado Department of Transportation in 2019 signed a 5-year contract with Integrated Roadways to test their pavement system. This smart pavement system can connect every vehicle to the internet so that drivers can get real-time data on traffic jams, road conditions, weather conditions, accidents, etc. Integrated Roadways claims that it can ‘feel’ the position of every car on the highway and thus it could provide to be an essential aid for navigation.
AI for Route Optimization
To reduce the cost of transportation and increase the shipping process speed AI can help identify the optimum routes. Route optimization is especially needed by bigger companies with a large customer base like Amazon. Quick deliveries always account for better customer experience and lead to a continual relationship with the buyer. AI analyzes the existing route and then provides optimized routes for the trucks. This allows businesses to speed up their processes and earn higher profits.
AI to peak hours at logistics Centers
AI and ML cannot just forecast demand for products they can also forecast external factors that may affect transportation time and cause delays like traffic. AI can identify peak hours so as to avoid them for smoother transportation. This would allow lesser time spent at the centers and in turn lead to a better customer service experience.
Now you are well aware of how AI can reshape the logistics and supply chain domain. Keep reading our blogs to gain more insights into the development of AI and ML in different industries.
If you have any questions please reach out to us and we would love to provide a better understanding of the use of AI and ML in Logistics.
Get in touch with IT Action Group today.
References:
K, V. (2020, January 22). 5 Use Cases of Artificial Intelligence and Machine Learning in Logistics and Supply Chain. Retrieved September 30, 2020, from https://medium.com/@venkat34.k/5-use-cases-of-artificial-intelligence-and-machine-learning-in-logistics-and-supply-chain-f395093b27d3
