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5 Use Cases of AI in Logistics

  • Manisha Sahu
  • Sep 04, 2021
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There is no other way of describing it: the logistics industry is being revolutionized by artificial intelligence (AI). It might sound like a cliché, hype, or buzz, but it's true. Logistics have had a significant impact on AI, and progress throughout this period can lead to a higher quality of service.


It gives the logistics companies from self-employed machinery to predictive analysis a wide range of possibilities. Mckinsey forecasts a $1.3 - $2 trillion worth of economic value will be generated annually by logistics industries through AI.



Why should we get an AI-powered Logistics System?


When we talk about the logistics reasons for AI, we can never fail to find reasonable arguments regarding how best to accomplish so. Let us look at some reasons for keeping a logistics system based on artificial intelligence.


Supply Chain Optimization

The promotion of optimization of the supply chain is a major advantage of artificial intelligence. However, each sector component of the supply chain must be optimized to take advantage of this. Everything in-between must be optimized for maximum performance from automated warehousing to automated cars.


This results in little waste and full resource use. It also reduces waste expenditure and promotes customer satisfaction by reducing the odds of the unavailability of a particular product.


( Recommended blog: Supply Chain Management )


Demand Prediction

Artificial logistical intelligence minimizes most of the effort needed to estimate market demand accurately. The utilization of real-time data made it even more accurate and easier to estimate demand. It is worth highlighting the reduction of errors from standard methods of prediction, such as ARIMA, AutoRegressive Integrated Moving Average, and Exponential Smoothing.


By increasing their human resources planning, AI-enabled manufacturers minimize their operating costs. The number of automobiles sent to local warehouses can be optimized and regional warehouses or dealers can help minimize their cost. This anticipated demand projection can keep the commodity from being invested elsewhere.


The image depicts reasons to have an AI-powered logistic system. They're - supply chain optimization - demand prediction - planning and resource management - real-time route optimization

Reasons to have an AI-Powered Logistic System

Planning and Resource Management

Efficient management of the resources and planning is an important part of the management of a rising industry. Efficient planning plays an important part in cost reduction and increased customer satisfaction and the overall increase in the governance of the system. The scenarios and numbers necessary for planning may be significantly analyzed by Artificial Intelligence and Machine learning.


It is vital because it contributes to the proper management of resources, which helps the business to decrease expenses and to achieve sufficient financial resources later. Supply planning in real-time is important according to market demands. The flow of items in the supply chain can be dynamically optimized.



Real-Time Route Optimization


Artificial logistical intelligence allows route optimization in real-time and reduces waste and enhances delivery efficiency. Industries have begun to employ autonomous delivery systems that optimize the route in real-time for a speedy delivery without human work.


The efficient planning of cargo management systems for logistics trucks is expected to be much easier by artificial intelligence and graphical analysis. The cost of shipping is reduced and the shipping procedure is increased.


( You can also sneak a peek at our blog on IoT in Fleet Management )



Artificial Intelligence Use Cases in Logistics


Tech profoundly changes packages from predictive analysis to autonomous vehicles and robots worldwide. Here are the top five ways in which the logistic business is transformed by artificial intelligence as we know it.


  1. Automated Warehousing


AI now tends to revolutionize warehouse tasks such as information collection and analysis or inventory processing. As a consequence, AI helps improve productivity and profitability. How does it work?  For the prediction of demand for certain products, artificial intelligence is applied. The corporation then supplies the regional warehouses with demanding commodities which reduce the shipping expenses.


According to Vero Solutions, 30% of the warehouse tasks in the coming years can be automated by enterprises. In addition, the system may manage the work and do numerous everyday activities using AI. An example of a corporation that has AI in the storage system and has a little profit has been prepared.


For example, Ocado is an online grocery store in the United Kingdom. This company has created a warehouse for automation. There is a "hive-grid-machine" robot that carries the orders much quicker than the workers. The figures are crazy. Over one week, the 'hive-grid-machine' can place 65,000 orders or 3.5 million foodstuffs. These robots help you to move, lift and sort. The employees at Ocado packed and sent orders afterward. This reduces the time necessary for sending an order.


Computer vision is often used in automatic warehouses. This technology enables objects to be recognized and organized. Computer vision will also help in the future, without supervision, to manage quality control. When numerous warehouses are located inside the chain, AI systems can connect them, so that the optimum way to transfer the merchandise is found.



  1. Autonomous Vehicles


For transportation, AI is useful. Automobile vehicles modify the supply chain and contribute to reducing logistics expenses. Naturally, we know about automobiles without drivers, but AI allows more cars to automate. To carry goods, you can, for example, also automate transport modes such as trucks, carriers, or buses.


Such vehicles can either work by themselves or work with a person. However, the government believes that drivers must be in the car to completely control the situation on the road and examine potential threats in many countries. Naturally in the future, this declaration could be amended.


Examples : 


Waymo was the first startup to integrate a business taxi service with self-driving vehicles. This startup built a taxi service using self-driving automobiles in December 2018. The service operates in the Phoenix, Arizona suburbs. Waymo now tries to construct trucks without drivers. Trucking is safer for the company. By 2030, the company's revenues are predicted to reach $114 billion.


Rolls-Royce is developing self-driving yachts with Intel. Since the 2010s, Rolls-Royce has developed this technology. In 2018, thus, awareness of intelligence has been released. This tool has several fascinating functions. For example, they can identify and define water objects, track engine status and select ideal routes. Consequently, the speed of delivery is increased.


Driverless technology can bring many advantages to logistics. For instance, by using cars that drive themselves, individuals have the chance to cut fuel consumption, optimize routes and avoid human blunders.


( Recommended blog: IoT in Warehouse Management )



  1. Smart Roads


There is another case of logistics AI in addition to driverless autos. Several enterprises are creating intelligent roadways. These firms prefer to develop different solutions to meet regional needs. For instance, roadways with solar panels and LED lights are being created. How might the logistics sector benefit?


Such roads can generate electricity or use colorful lights to pay attention to changing road conditions. The capacity to heat solar panels is another advantage. The roads in the winter are therefore not slippery.


All the above advantages led to the conclusion that smart roads are valuable in the sector of logistics. Due to unfavorable weather conditions, there are no delivery delays in the supply chain.


For example, Integrated Roadways developed the  Smart Pavement System . In 2018, the Transportation Department of Colorado began an active test of the system. It can connect the vehicles and give the drivers real-time information on accidents, jams, etc. The inventors also think that their system can "sense" the position of each car and provide detailed navigation to drivers.


( Recommended blog: How do Google Maps work? )


First of all, on the road to the Internet, it can connect the cars. Drivers can therefore get real-life information on road jams, accidents, and so forth. In addition, inventors consider that their technology can 'feel' each car and allow drivers to navigate in detail.

The image depicts AI use cases in the logistics industry. They're - Automated warehouse eg: Ocado - Autonomous vehicles eg:waymo and rolls Royce - smart roads eg: integrated roadways - Back office operations eg: UI path and Leverton - AI to forecast demand and enhance customer experience eg: DHL

AI Use cases in the Logistics Industry

  1. Back Office Operations


For the logistics business, back-office activities are crucial. Technologies, such as AI and RPA, allow people to accelerate their job processes. Some data-related jobs, for example, are repeated every day. You can automate them. Back-office automation allows businesses with supply chains to save time and money.


The combination of AI and RPA has generated cognitive automation technology. As a consequence, firms can save time, improve productivity and increase accuracy. This technology is primarily intended to replace certain classes of staff such as accountants, personnel, etc. This substitution will reduce the frequency of human mistakes.


For instance, UIPath works on the equipment for robotics. The proprietors say 99% of the tasks can be performed by robots if requested by the employee. This is because the robots of UiPath can 'see" the elements of the screen. ARR has reached over $200 million.


And Leverton was founded in 2012 by a group of scientists who seek to push the limits based on semantic analysis of artificial intelligence. It is developing software powered by AI. This is a software for contract analytics, which can perform a range of tasks, for instance, administer contracts and support around 30 languages. In addition, this tool can be taught to collect information from papers. Leverton argues that this method enables savings in time from 30 to 50%.



  1. Predict Demand and Improve Customer Experience


In the logistics business, artificial intelligence has a pretty evident example of usage. This technique can help predict demand. Of course, to speed up delivery, enterprises must forecast the approximate number of goods. In another scenario, if the supply of items is restricted, but the demand is large, the company will lose some money.


Algorithms can predict trends. They are available. Recent research has shown that AI-based instruments are more predictable than human experts. Artificial intelligence enables us to monitor the components needed to enhance the exact prediction of demand. This information can then facilitate warehouse management.


AI also improves the experience of its customers. With the application of this technology, customers can gain a more personalized experience and hence have more confidence in the brand.


For example, DHL is the world’s leading logistics company. Every single day more than 400,000 people operate across borders, reaching new markets, and growing their business in over 220 nations and territories.


The agreement was inked by Amazon and DHL Parcel. They work together to enrich the experience of the customers. Amazon hence has launched an Alexa voice service. Questions about parcels, e.g. shipment information, whereabouts, etc. were taught. It is quite easy to use Alexa. Alexa, where is my parcel? maybe asked and all the facts are provided to you.


( Also check: How Amazon Uses Warehouse Technologies )


As you can see, in the logistics area there are numerous AI usage cases. This powerful technology is evolving, in particular, to improve logistics and supply chains. AI enables ordinary chores which take a long time to automate.



The future of automated delivery systems


Logistics is an area in which as much information as possible needs to be correctly functioning. There is plenty that can be streamlined from stock rates, weights, and locations to route management and coordination. The wide deployment of these techniques will enable consumer-oriented, customized shipping in the future.


It remains to be seen whether it means the utilization of drones that bring selected products right at your door, but the degree of personalization that dominates AI and automation will likely become the logistics for shipment. This is already shown in the ability of Amazon to supply a large number of things within one day.


As AI improves, also automated technologies will enhance shipping logistics awareness and efficiency. This means speedier globe deliveries and a simpler global trading system. Companies that take advantage of this technology will certainly have a competitive edge now that AI use is more mainstream.


( Related blog - Types of Trading )


These developments in the industry are pioneering yet are only the end of the iceberg. In logistics, the most interesting part about AI is that there are many more use cases and companies that affect the business. Technology has an overall impact on the way we ship – and increased cooperation between logistics corporations and start-ups will surely lead to advances in the next few years and decades.

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    Sep 12, 2022

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