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

  • Thomas De Lombaert*
  • , Kris Braekers
  • , René De Koster
  • , Katrien Ramaekers
  • *Corresponding author for this work
  • Hasselt University

Research output: Contribution to journal › Article › Academic › peer-review

88 Citations (Scopus)
1820 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)3300-3330
Number of pages31
JournalInternational Journal of Production Research
Volume61
Issue number10
Early online date1 Jun 2022
DOIs
Publication statusPublished - 2023

Bibliographical note

Funding Information:
This research is supported by the Special Research Fund (BOF) of Hasselt University and the Research Foundation Flanders (FWO) (Strategic Basic Research project Data-driven logistics,  FWO-SOO7318N).

Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.

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