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Energy Price and Workload Related Dispatching Rule: Balancing Energy and Production Logistics Costs

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Listed:
  • Balwin Bokor
  • Wolfgang Seiringer
  • Klaus Altendorfer
  • Thomas Felberbauer

Abstract

In response to the escalating need for sustainable manufacturing practices amid fluctuating energy prices, this study introduces a novel dispatching rule that integrates energy price and workload considerations with Material Requirement Planning (MRP) to optimize production logistics and energy costs. The dispatching rule effectively adjusts machine operational states, i.e. turn the machine on or off, based on current energy prices and workload. By developing a stochastic multi-item multi-stage job shop simulation model, this research evaluates the performance of the dispatching rule through a comprehensive full-factorial simulation. Findings indicate a significant enhancement in shop floor decision-making through reduced overall costs. Moreover, the analysis of the Pareto front reveals trade-offs between minimizing energy and production logistics costs, aiding decision-makers in selecting optimal configurations.

Suggested Citation

  • 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.
    • Handle: RePEc:arx:papers:2405.02445
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    References listed on IDEAS

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    1. Klaus Altendorfer, 2019. "Effect of limited capacity on optimal planning parameters for a multi-item production system with setup times and advance demand information," International Journal of Production Research, Taylor & Francis Journals, vol. 57(6), pages 1892-1913, March.
    2. 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.
    3. Nicla Frigerio & Barış Tan & Andrea Matta, 2024. "Simultaneous control of multiple machines for energy efficiency: a simulation-based approach," International Journal of Production Research, Taylor & Francis Journals, vol. 62(3), pages 933-948, February.
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