Artificial Intelligence and Automation in Logistics

Artificial Intelligence in the Logistics Industry

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How AI can solve logistics problems and generate value.

Artificial intelligence has started to impact the logistics industry, along with the supply chain. We are seeing innovations such as smart roads and autonomous vehicles. In this article, we’ll look at five promising AI use cases in logistics. The potential value to be gained is huge. Research shows it can generate from $1.3 trillion to $2 trillion per year.

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The primary purpose of many AI implementations in the logistics industry is to automate time-consuming actions and save money. Many tech enterprises (e.g. Google, Amazon) are heavily invested in this technology and leading the field.

Use Case 1: Automated Warehouses

Artificial intelligence technology changes many warehousing operations, e.g. data collection, inventory processes, and more. As a result, companies can increase revenues. AI in warehouse automation is being used for predicting the demand for particular products. Based on this data, orders can be modified and the in-demand items can be delivered to the local warehouse. This predicting of demand, and planning of logistics well in advance, means lower transportation costs.

Artificial intelligence can be used to predict demand, modify orders, and re-route in-transit goods to warehouses where needed. Such planning and agility in logistics means better service and lower logistics costs. Click To Tweet

Warehouse automation systems provide an opportunity to conquer a lot of routine tasks. The leading technology used in these systems is computer vision that can identify and help organize the inventory. Another promising use case is autonomous quality control.

These systems can also optimize inventory and transportation between warehouses.

Ocado’s Success Story

Ocado is a supermarket located in the United Kingdom. It has developed an automated warehouse. The system is based on a robot called ‘hive-grid-machine.’ This robot can execute 65,000 orders per week. ‘Hive-grid-machines’ main task is to move, sort, and lift items inside the warehouse. Ocado’s automated warehouse dramatically cuts labor and the time for orders to be executed.

Use Case 2: Autonomous Vehicles

Self-driving cars get a lot of press today, and for obvious reasons. The use of automated vehicles in the logistics industry promises to save time and money, and could reduce accident rates. There is a lot of work still to do, as currently, drivers are required to be at the wheel of autonomous vehicles, and it will take some time before the technology and regulations allow for fully autonomous vehicles to drive on roads without human supervision.

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Autonomous vehicles are the start of a major trend across the supply chain in general, from warehouse ground vehicles and drones, to autonomous business processes such that robotic process automation (RPA) manages. Some companies are even pioneering the autonomous supply chain, which automates many tasks in the supply chain that are traditionally handled by planners and managers.

Waymo’s Success Story

Waymo was the first company that decided to integrate a commercial taxi service with self-driving cars. This innovative service was launched in Phoenix, Arizona, in December 2018. These days, the company is working on building driverless trucks, which will have a dramatic impact on the logistics industry.

Rolls-Royce’s Success Story

Rolls-Royce is working with Intel to develop self-driving ships. Rolls-Royce released the Intelligence Awareness system in 2018, system that is able to classify all the nearby objects under the water. It can also monitor the engine condition and recommend the best routes. According to a market report, the market of autonomous ships will reach $13.8 billion by 2030.

Self-driving technology brings a lot of obvious benefits to the logistics field. Driverless vehicles offer to speed up the delivery process, can optimize routes, reduce human error accidents, work 24/7, and more.

Use Case 3: Smart Roads

Another AI use case in logistics is smart roads. Examples of this technology include highways with solar panels powered LED lights. Solar panels assist in producing the electricity while LED lights are used to alert drivers about the road conditions. Additionally, solar panels prevent the road from being slippery in winter. Another application is fiber optic sensors that can sense traffic volumes and patterns and alert drivers to road conditions ahead. They can also sense when vehicles leave the road or are involved in accidents, and alert the appropriate emergency services and authorities. This makes for faster deliveries and safer road conditions.

Integrated Roadways’ Success Story

Integrated Roadways company has created the Smart Pavement system. It can connect the vehicles all provide the drivers with real-life information about accidents, traffic jams, and so on. The Colorado Department of Transportation began actively testing the system in 2018.

Use Case 4: Back Office

Artificial Intelligence in combination with Robotic Process Automation (RPA) provides the workers with an opportunity to increase their quality of work. For instance, everyday repetitive  tasks can be automated. This lowers costs and improves the accuracy and timeliness of data for logistics companies.

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UiPath’s Success Story

UIPath works on robotic equipment. They’ve developed a robot that is able to conquer approximately 99% of back office tasks since the robot can “see” screen elements. The company’s ARR has grown to more than $200 million.

Use Case 5: Demand Prediction

One critical business need affecting most businesses, is the need to predict the amount of supplies and goods it needs in future. Running short of inventory means lost sales, lost revenue, and often lost customers who may defect to a competitor’s product.

AI provides various algorithms that can predict trends. According to Deloitte, in many cases, these algorithms can predict outcomes better than human experts.

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These days, AI can track and measure all inputs and variables, and do it quickly and precisely, improving the accuracy of predictions. This means lower inventory and simpler warehouse management.

AI can also improve customer experience through personalization, suggesting products and customizations tailored specifically to their buying habits and preferences.

There are many ways to implement AI into the supply chain and into the logistics sector. It improves logistics processes and reduces costs. It also plays a major role in automating routine tasks to improve the speed and accuracy in numerous back office applications.

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Vitaly Kuprenko
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