Alexander Honigmann, Director, Transportation and Logistics, EMEA, Zebra Technologies, outlines the improvements that artificial intelligence has brought to modern warehouses by reworking the scale of data analytics.
The value of the global market for Artificial Intelligence (AI) in warehousing is projected to grow by almost a quarter by 2030, reaching around €39 billion. At the same time, warehouse businesses are saying that their most pressing challenges are developing smarter strategies around optimisation and automation and achieving a timely return on investment (ROI). The ongoing difficulty of finding enough skilled workers also means more operations turning to technology for help to maintain productivity. So it’s no wonder that 60% of warehouse leaders in Europe say they plan to implement AI within five years.
Cost savings is one of the key motivators behind that intention. Logistics research by McKinsey suggests that “thanks to forecasting with AI, it is possible to reduce supply chain errors to 20-50%. At the same time, warehouse and administration costs can be decreased by 5% to 10% and 25% to 40%, respectively”.
Savings of time and space are also key reasons why AI is sought out by warehouse leaders. One senior leader of operations at a global logistics company says that AI is delivering lots of small time and space savings which quickly add up to big cost savings for the company. And with on-device generative AI (GenAI) assistants on mobile computers and tablets, workers no longer need to leave the warehouse floor to consult a desk-based warehouse management system (WMS), as operating procedures, inventory data and task lists can be accessed quickly with the help of the AI assistant. And it’s on the warehouse floor that the everyday improvements delivered by AI add up to big gains for logistics operations. They’re also a more connected frontline workforce, with unified synchronised software designed to seamlessly connect workers with other.
As well as the need to save space in existing premises, the challenge of managing the increasing average size of warehouses is also driving the shift to AI and predictive analytics. Worldwide the average warehouse size is now estimated to be over 100,00 square metres, and total global volume is projected to increase by 27%, from 3.06 billion square metres in 2023 to 3.9 billion square metres in 2030.
Bigger Warehouses, More Data
The vast size of modern warehouses is matched by the vast amount of data generated from warehouse activities, which is simply too great for manual analysis alone. The processing power and level of insight provided by AI-driven analytics tools and intelligent automation allows decision-makers and frontline workers to gain greater visibility into assets and inventory and respond proactively to potential inefficiencies and bottlenecks.
AI-driven benefits can start long before the goods arrive at the loading area to be dispatched. The integration of AI into machine vision and fixed industrial scanning solutions enables inspection, sortation, and tracking workflows including the imaging of unstructured goods, such as a pallet or conveyor belt of items of different sizes and shapes. For example, implementing a scan tunnel solution for one of the world’s largest global transportation and logistics enterprises resulted in improved read rate accuracy by 37%, decreased downtime and manual handling by 29%, and reduced operational costs by 13%.
Then consider a team of warehouse workers tasked with loading delivery trucks. They must ensure that each truck is optimally filled, considering the weight, size, and destination of each parcel. Mobile dimensioning applications with AI algorithms can accurately measure box and package dimensions, significantly reducing manual errors and speeding up processing times.
And AI-driven software on a tablet can visually represent the best way to load the truck for balance and efficiency. The AI could analyse each parcel’s data and destination and suggests the order and position for loading. This ensures that the truck is securely packed and unloading at each stop is streamlined. It also reduces the risk of injury caused by manual handling – not a small concern, given that 73% of warehouse associates in Europe are concerned about injuries on the warehouse floor.
But AI doesn’t stop working its magic once the goods are on the truck and ready to go. By leveraging advanced algorithms and real-time data analysis, AI systems can calculate the most efficient paths for moving goods, based on a multitude of variables such as equipment availability, storage conditions, order priorities, and workforce distribution.
The bottom line is that over eight in 10 decision-makers and associates agree that the increased use of technology and automation helps boost frontline productivity. AI in warehouse intralogistics will continue to play an increasingly large role in that picture over the next five years and more.
Find out more about solutions transforming the warehouse logistics landscape here.
Source: Zebra Technologies
