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In pursuit of humanised order picking planning: methodological review, literature classification and input from practice

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  • Thomas De Lombaert
  • Kris Braekers
  • René De Koster
  • Katrien Ramaekers

Abstract

At the core of every high-performing warehouse is an efficient order picking (OP) system. To attain such a system, policy choices should be carefully aligned with subjects responsible for the actual picking within the established system. Despite recent advancements in automating the picking process due to Industry 4.0, human operators will continue to play a crucial role in the future of warehousing. However, unlike robots, human operators have specific skills, conduct, and perceptions, which are only partly accounted for in current planning models. This review adopts a multimethod approach to identify and analyse how these phenomena are currently integrated into OP planning problems. In addition, we assess the relevance and adequacy of human factors modelling in academic literature with practice-based insights gathered via semi-structured interviews. This leads to five major human factors integration constructs and dedicated recommendations on how to refine them. We then take the analysis one step further and make suggestions on how to integrate these constructs with leading research methodologies in the context of Industry 5.0. The results highlight the prevalent need to increasingly account for psychosocial phenomena and their impact on operational performance. Future research opportunities provide a substantiated foundation to assist in human-centric work design.

Suggested Citation

  • Thomas De Lombaert & Kris Braekers & René De Koster & Katrien Ramaekers, 2023. "In pursuit of humanised order picking planning: methodological review, literature classification and input from practice," International Journal of Production Research, Taylor & Francis Journals, vol. 61(10), pages 3300-3330, May.
    • Handle: RePEc:taf:tprsxx:v:61:y:2023:i:10:p:3300-3330
    DOI: 10.1080/00207543.2022.2079437
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    Cited by:

    1. Sobrie, Léon & Verschelde, Marijn & Roets, Bart, 2024. "Explainable real-time predictive analytics on employee workload in digital railway control rooms," European Journal of Operational Research, Elsevier, vol. 317(2), pages 437-448.
    2. Diefenbach, Heiko & Grosse, Eric H. & Glock, Christoph H., 2024. "Human-and-cost-centric storage assignment optimization in picker-to-parts warehouses," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1049-1068.

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