A few years ago, it was hard to imagine that AI would solve the many tasks it is dealing with today. Technological development has brought warehouses and transportation to a new level. Robots are doing routine stuff for humans. Humans are thinking of ways to optimize and modify robots.
Jonnie Penn, a researcher at the University of Cambridge, shared that “a lot of AI isn’t new. The moment today is a combination of past techniques with computing power.” It means we are happy to live in the opportune moment to benefit from all the progress of AI technologies.
In this post, professionals from the Belitsoft software development company share their expertise about the application of artificial intelligence in the logistics and supply chain domains.
How is AI used in logistics?
Document workflow
Optical character recognition and natural language processing reduced paperwork for logistics specialists. Computers can now read invoices, driver lists, and packing bills. The software scans the information, extracts the required details, and transforms the data into spreadsheets. Some AI functionality also allows sending notifications to stakeholders or, for example, requesting additional data and e-signatures. Cloud-based document management systems often contain ready-to-use AI features that enable customized data extraction.
Warehouses
If you try to visualize AI in warehouses, you will probably think of robots helping people lift heavy constructions, assemble details, sort items, and locate them in the required space. Those processes, if configured appropriately, minimize errors, speed up processes, and allow humans to dedicate their efforts to something more challenging.
Drones and self-driving vehicles introduce other examples of robotic automation in warehouses. Armed with computer vision, robots can scan barcodes and detect the following locations for the packages according to their routes. Robots then pass this information to drones or auto-drives for delivery. Driverless vehicles transfer goods quickly, which results in reduced costs as there is no need to pay a salary to drivers, and the vehicles run on batteries. Incidentally, the drone market is projected to reach a level of $17 billion in 2030.
Analytics and prediction
Machine learning algorithms traditionally rely on historical data. In logistics, however, more details are required for careful prediction. Modern software analyzes weather conditions, regional traffic peculiarities, and even local events that can cause delivery delays. As a result, customers receive the correct delivery time.
Another prediction area relates to timely equipment maintenance. Special sensors located on robots indicate their current condition and battery charge and require repairs if necessary. Prompt technical service saves money on serious damages.
Inventory audit
AI algorithms can forecast demand and adequately assign supply. Consequently, the situation “unfortunately, we’ve run out of inventory” will occur less often. Machine learning analyzes inbound orders, taking into consideration peak times, e.g., Christmas, and predicts the products that should be in stock. Utilizing 3D printers helps to solve inventory shortages. For instance, the military forces of Great Britain used those printers to produce protective equipment, turnstiles, spy glasses, and other minor things. Thus, technological progress changes military logistics as well.
Digital twins
This technology creates a virtual model of a real warehouse. All the processes that happen inside the warehouse are shown in the application. Robots and automated systems update the data regularly about the items shipped, packed, or assembled. Thus, a person monitoring the operation process may not even physically be present at such a warehouse.
Who has already implemented AI in logistics?
Amazon
Workers at Amazon warehouses claim that the delivery time can be as short as 3 hours from the moment of ordering an item online. That is possible due to the artificial intelligence machines that work on the site. Robotic drives and robotic arms help to pack and ship items faster. Robotic arms scan barcodes on the packages and put the items on the conveyor belt. Automated drives take those items to the appropriate vehicle, depending on their destination. Thus, human workers have to walk less and do less heavy lifting. Operating computer programs increases their competence level and develops skills.
FedEx
The DoraSorter robot is there to help with sorting parcels. It was first introduced at the Chinese subsidiary of FedEx in 2022. The robot sorts inbound and outbound parcels depending on their destinations. The functionality includes a barcode scanner and a gripper to connect to the conveyor belt. DoraSorter can handle parcels of up to 10 kg and 100 destinations simultaneously.
Nuro
Nuro is a driverless vehicle that transfers goods in the neighborhood areas of San Francisco and Houston. Three types of vehicles can deliver different cargo capacities. Modular compartments allow for keeping food hot or cold. The cars are emission-free, reducing environmental impact. An external airbag protects people in the street in case of emergencies.
DHL
The company uses AI technologies for multiple purposes. First, data analytics examines the traffic situation and builds the most appropriate routes for drivers to save time and fuel. Second, the AI solution OptiCarton determines the ideal packaging for items to use all the available space on the trucks. The items fill the space, as in the Tetris game. Besides those, DHL uses chatbots on the site, monitors the supply with AI programs, and exploits robots for parcel sorting.
Advantages of AI in logistics
- A solution to the shrinking labor force market. Robots neither go on strikes nor ask for wage increases.
- Better connection to the remote areas. Drones deliver life-saving medical supplies, as well as blood and plasma, to distant African villages. Traditional transportation is helpless in those territories.
What are the challenges?
- Increased risks of cyberattacks. As for logistics, drones are the biggest concern, as they record data, which can then be transmitted wirelessly to any third-party device.
How to address it? Use anti-virus software on the controller and a VPN to secure the connection.
- Unsatisfied customers. Of 1,059 people surveyed in 2022, 43% said they were unsatisfied while interacting with virtual assistants.
How to address it? Conduct a feedback interview with your customers. They might be unhappy with the exact type of assistance. You can assign this to human consultants.
- Implementation costs. On the one hand, it includes hardware. On the other hand, the staff needs training, mentoring programs, and time to get used to new equipment.
- How to address it? If you feel new technologies are urgent for your business, develop a step-by-step strategy to invest money in portions.
Final thoughts
Applying artificial intelligence to logistics leads to improved business performance. It optimizes the workload and cuts costs required for paying wages. Virtual assistants tackle repetitive tasks, increasing human expertise and skills. Driverless vehicles are ecologically friendly, which answers another demand for sustainable modern business. At the same time, advanced technologies require a comprehensive strategy with a new corporate culture and business processes.
