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Integrating production scheduling, maintenance planning and energy controlling for the sustainable manufacturing systems under TOU tariff

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  • Weiwei Cui
  • Huali Sun
  • Beixin Xia

Abstract

Climate change pushes the operation managers to take account of energy-saving issues in their decision-making of production scheduling and maintenance planning (PSMP). We address a PSMP problem for a single machine system under Time-of-Use electricity tariff. We consider two objectives including the makespan that measures the service level and the total energy cost that measures the energy sustainability. Both objectives are considered in a bi-objective mathematical model that is further solved using a novel heuristic algorithm consisting of two layers based on the problem decomposition. The inner layer problem, which is solved by a branch & bound algorithm, is to optimise the decision variables of preventive maintenance and machine’s setup. The outer layer problem, which is solved by a hybrid NSGA-II algorithm, is to optimise the sequence of jobs and the amount of inserted buffer time. The effectiveness and efficiency of the algorithm are demonstrated by a series of numerical experiments. The Pareto frontier can serve as a tool for managers to consider energy cost explicitly in making decisions. It is observed in some scenarios that reducing energy cost will not increase the makespan.

Suggested Citation

  • Weiwei Cui & Huali Sun & Beixin Xia, 2020. "Integrating production scheduling, maintenance planning and energy controlling for the sustainable manufacturing systems under TOU tariff," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(11), pages 1760-1779, November.
    • Handle: RePEc:taf:tjorxx:v:71:y:2020:i:11:p:1760-1779
    DOI: 10.1080/01605682.2019.1630327
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    Cited by:

    1. Konstantinos Plakas & Ioannis Karampinis & Panayiotis Alefragis & Alexios Birbas & Michael Birbas & Alex Papalexopoulos, 2023. "A Predictive Fuzzy Logic Model for Forecasting Electricity Day-Ahead Market Prices for Scheduling Industrial Applications," Energies, MDPI, vol. 16(10), pages 1-21, May.
    2. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2021. "Job Scheduling under Time-of-Use Energy Tariffs for Sustainable Manufacturing: A Survey," LIDAM Discussion Papers CORE 2021019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2023. "Job scheduling under Time-of-Use energy tariffs for sustainable manufacturing: a survey," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1091-1109.
    4. Lu-Miao Li, Peng Zhou, and Wen Wen, 2023. "Distributed Renewable Energy Investment: The Effect of Time-of-Use Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    5. Weiwei Cui & Biao Lu, 2020. "A Bi-Objective Approach to Minimize Makespan and Energy Consumption in Flow Shops with Peak Demand Constraint," Sustainability, MDPI, vol. 12(10), pages 1-22, May.

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