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    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 15 Dec 2020, available online: https://www.tandfonline.com/doi/abs/10.1080/00207543.2020.1857451

    Accepted author manuscript, 1.17 MB, PDF document

    Embargo ends: 15/12/21

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Direct Workload Control: Simplifying Continuous Order Release

Research output: Contribution to journalJournal articlepeer-review

E-pub ahead of print
<mark>Journal publication date</mark>15/12/2020
<mark>Journal</mark>International Journal of Production Research
Publication StatusE-pub ahead of print
Early online date15/12/20
<mark>Original language</mark>English

Abstract

Workload Control withholds orders from the shop floor in a backlog from which they are released to meet certain performance metrics. This release decision precedes the execution of orders at shop floor stations. For each station there are consequently three types of workload: indirect, released work that is still upstream of the station; direct, work that is currently at the station; and, completed, work that is still on the shop floor but is downstream of the station. Most release methods control an aggregate workload made up of some representation of at least two of these three workload types. Yet the core objective of Workload Control release methods relates to only one of the three types – that is, to create a small, stable direct load in front of each station. Clearly, order release would be greatly simplified if only the direct load had to be considered. Using discrete event simulation, we show that Direct Workload Control leads to performance levels that match those of more complex and sophisticated approaches to Workload Control. Further, it greatly simplifies continuous order release, decentralising the release decision by allowing it to be executed at each gateway station. This has important implications for research and practice.

Bibliographic note

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 15 Dec 2020, available online: https://www.tandfonline.com/doi/abs/10.1080/00207543.2020.1857451