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Energy-efficient control in multi-stage production lines with parallel machine workstations and production constraints

Author

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  • Alberto Loffredo
  • Nicla Frigerio
  • Ettore Lanzarone
  • Andrea Matta

Abstract

Nowadays, the growing interest in industry for enhancing manufacturing processes sustainability is a major trend. One of the most supported strategies to increase the energy-efficiency of manufacturing activities is the control of machine state towards the optimum trade-off between production rate and energy demand. This method is referred to as energy-efficient control and it triggers machines in a standby state with low power request. In this article, multi-stage production lines composed of identical parallel machine workstations are the systems of interest, and the energy-efficient control policies make use of buffer level information. Each machine can be switched off instantaneously and switched on with a stochastic startup time. Problem objective is to minimize the energy demand while ensuring production constraints. This article proposes a novel approach to solve the problem at hand. An exact model for two-stage system is formulated using a Markov Decision Process to be solved with a linear programming methodology. A novel technique, namely the Backward-Recursive approach, is used to address systems with more than two stages. Numerical experiments confirm the effectiveness of the proposed approach.

Suggested Citation

  • Alberto Loffredo & Nicla Frigerio & Ettore Lanzarone & Andrea Matta, 2024. "Energy-efficient control in multi-stage production lines with parallel machine workstations and production constraints," IISE Transactions, Taylor & Francis Journals, vol. 56(1), pages 69-83, January.
  • Handle: RePEc:taf:uiiexx:v:56:y:2024:i:1:p:69-83
    DOI: 10.1080/24725854.2023.2168321
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    Cited by:

    1. Balwin Bokor & Wolfgang Seiringer & Klaus Altendorfer & Thomas Felberbauer, 2024. "Energy Price and Workload Related Dispatching Rule: Balancing Energy and Production Logistics Costs," Papers 2405.02445, arXiv.org, revised Nov 2024.

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