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Home » Industry News » Warehousing & Storage News » Innovative digital slotting design solutions for warehousing

Innovative digital slotting design solutions for warehousing

WAREHOUSING and distribution operations are critical in integrated supply chains. As part of the company’s portfolio of technology innovations, Maersk is exploring AI-empowered, warehouse design slotting digital solutions.

In large scale fulfilment operations, slotting is essential to maximize the overall efficiency of warehouse operations by maximizing space utilization, increasing productivity, and reducing inventory handling. The constant optimization of inventory layout within warehouses improves workflows, order preparation processing times and the company’s operational strategy.

“Utilizing AI, developing algorithms, predictive analytics, simulations and data-driven analytics added to business model innovations enables us to continuously improve supply chain processes. This visibility enables our customers to compete with a faster time-to-market proposition. AI solutions embedded with deep expertise in machine learning, optimization, simulation, and data-driven analytics also upskills decision-making” says Erez Agmoni, Maersk’s Head of Innovation and Strategic Growth for the Warehousing and Development product,

Since November 2021 in Redlands, California, Maersk’s cross-functional innovation team collaborated with IAI Labs Technology to create a customized digital application for the slotting solution process in omni-channel fulfilment centres. The new technology being prototyped enables software analysis to improve the accuracy and efficiency of results and enhance the storage location distribution of items for warehouse utilization.

“The solution is well-ahead in the proof-of-concept process and is already tracking with a 97% accuracy rate which will significantly improve decision-making through digitalization” explains Manuel Pappaterra, Maersk’s Warehousing and Distribution, Head of Customer Implementations.

  • More testing and research is planned for phase two of the project in Q1 2022.
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