Adaptive Intelligent Redeployment Strategy for Service Parts Inventory Management: A Case Study of a High-Tech Company

Daniel Y. Mo (), Danny C. K. Ho, Eugene Y. C. Wong and Yue Wang
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Daniel Y. Mo: The Hang Seng University of Hong Kong
Danny C. K. Ho: The Hang Seng University of Hong Kong
Eugene Y. C. Wong: The Hang Seng University of Hong Kong
Yue Wang: The Hang Seng University of Hong Kong

A chapter in Intelligent Engineering and Management for Industry 4.0, 2022, pp 107-115 from Springer

Abstract: Abstract Much attention and resources have been put to the integration of emerging technologies such as robotics, Internet of Things (IoT), big data analytics, Artificial Intelligence (AI), and cloud computing, for developing smart factories. Yet, the key to success in the Industry 4.0 era depends not only on the advancement and adoption of intelligent engineering for production but also on a concerted effort of intelligent systems management applied across multiple functions within a company and multiple partners on the supply chain. To show the potential benefits of applying an intelligent systems management approach to inventory management, an adaptive intelligent redeployment strategy is developed to integrate replenishment and redeployment of excess stock strategies with the application of redeployment model in a closed-loop service logistics network. A case study is presented to illustrate how an international high-tech company can apply this model and provide better customer services at lower costs. This adaptive strategy compels managers to rethink the conventional way of managing inventory of items with non-stationary demand and to pursue digitalization of inventory management jointly with supply chain partners for operations excellence in the Industry 4.0 era.

Keywords: Excess inventory; Service logistics network design; Network flow model; Spare parts (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-030-94683-8_10

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