Artificial intelligence of things and circular warehouse process management of automotive parts: conceptual framework and practice review
by Asmae El Jaouhari; Jabir Arif
International Journal of Process Management and Benchmarking (IJPMB), Vol. 17, No. 1, 2024

Abstract: In recent years, sustainable warehouse management strategies have been developed by businesses that desire to mitigate the adverse social and environmental effects within their warehouses. A circular method has been established in the warehouse management literature from this standpoint. The recycling process, knowledge, operational excellence and smart decision-making have all been enabled by circular economy models and solutions enabled by artificial intelligence and internet of things technologies. In this paper, an artificial intelligence of things (AIoT)-based circular warehouse management system (CWMS) is designed and tested within a real-world automotive supply chain to assess the sustainability performance of a CWMS for Industry 4.0. The results indicate that using AIoT technology to restructure the warehouse for a circular economy can enable CWMS. By connecting the proposed approach to the circular economy aspects of reuse, optimise, remove, recycle, and virtualise, clear benefits are provided. This study aims to enhance the current research by providing real proof of how AIoT and circular economy technology are used in practice.

Online publication date: Fri, 05-Apr-2024

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