In computer science, artificial intelligence (AI) is a discipline that seeks to create machines that can duplicate the functions and reactions of a person as closely as possible. Its capabilities include the ability to do human-like activities, such as decision-making and speech recognition.
Data is the lifeblood of AI and warehouses, in general, have lots of it: from customer purchasing habits to machinery use to resource usage. Linking all this data together intelligently can greatly improve warehouse efficiency.
AI is able to link lots of data together, providing unique insights a human would not have been able to spot.
What value can AI bring to warehousing?
AI has the potential to improve business operations and increase profit margins in a multitude of warehouse areas. Below, the five core areas are listed.
AI may be utilized to increase the productivity of warehouse workers:
- Workforce planning. In many warehouses, managers make decisions about staffing depending on workload, deadlines, and past productivity. Most staffing decisions are typically reliant on the expertise and talent of the individual manager. Machine learning could be used to anticipate the number of workers needed and the time it will take to complete a task. AI can also help to simulate how the task should be done to prevent delays and ensure that the most effective use of labor is achieved.
- Performance planning. An AI system can support in performance planning. It can make relevant suggestions by taking into consideration a wide range of characteristics obtained from real-world warehouse operations like employee data, job type, start- and end location, timings, products handled, quantities handled, etc.
- Route optimization: warehouse workers spend significant time walking. Reducing walking time can therefore be a major factor in increasing productivity. Using AI-based route optimization, several warehouses have increased productivity in piece picking by twofold. Even warehouses doing case picking have achieved productivity benefits of 20 to 30%.
Adding AI doesn’t only help to save money by increasing the productivity of employees, but also allows for better use of available space.
- Dynamic slotting. To maximize productivity, throughput, and accuracy, product slotting must be done correctly. However, this is not a simple task. Traditional slotting systems need a great deal of warehouse mapping and manual data entry, which AI reduces. Based on warehouse activity-level data, AI systems can continuously suggest the most efficient slots based on spatial characteristics and walking time for example.
Easier inventory management
- Demand forecasting. One of the greatest advantages of artificial intelligence is that it can be used to monitor market demand and regulate inventory so that there is never too much (or too little).
- Automated counting and checking. Computer vision-based solutions like Powerhouse AI are replacing paper trails and barcode scanners. This new generation of warehouse technology enables more precise and accurate inventory management by automatically checking and counting inventory.
AI can help logistics companies to better manage the vast amount of data generated within their operations. Patterns can be discovered and automatic recommendations can be provided to help plan more effectively.
When data is sent back and forth between various individuals in a warehouse, it is easy for misunderstandings and errors to occur. Using artificial intelligence, it is possible to make sure that everyone is aware of what is going on at all times, reducing errors and increasing productivity.
The current state of AI in warehousing
Only 12% of those polled for the MHI Annual Industry Report 2020 said they were presently utilizing AI. Despite this relatively small number, more than half of those surveyed feel that artificial intelligence has the potential to disrupt their sector and provide their company with a competitive edge.
This is partially because logistics companies are looking for ways to improve efficiency and assess which routes to market are the fastest and most effective. With ever-growing labor scarcity, a rise in online shopping, and exciting technological breakthroughs, automation is becoming one of the most important topics for logistics executives to focus on. Some real-life examples:
- One of Zappos’ key goals was to automate their warehouse so that they could continue to offer free delivery, a 365-day return policy, and a full-time customer service center.
- UK-based online grocery store Ocado is using robots to unpack and unload inventory, stack shelves, and to transport its inventory through the warehouse.
- Automated systems and AI are used in Amazon’s warehouses to streamline operations and anticipate customer issues.
- Alibaba has a clever warehouse system where 70% of the labor is done by robots. Their robots can carry up to 500kg, have sensors to prevent accidents, and when they run short on power, they take themselves to a charging station.
- Coca-Cola’s EMEA warehouse is completely automated. It is able to handle more than 25,000 pallets and has smart systems in place to prevent double handling of goods.
Most warehouse operations could be automated by 2030, as AI will be able to take over more and more of the repetitive and simple tasks that warehouse workers are currently performing. That’s why this is the time for companies to explore opportunities for implementing and integrating AI in their operations.