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Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme

Author

Listed:
  • Hajo Terbrack

    (International Institute (IHI) Zittau, Technische Universität Dresden, Markt 23, 02763 Zittau, Germany)

  • Thorsten Claus

    (International Institute (IHI) Zittau, Technische Universität Dresden, Markt 23, 02763 Zittau, Germany)

  • Frank Herrmann

    (Innovation and Competence Centre for Production Logistics and Factory Planning (IPF), Ostbayerische Technische Hochschule Regensburg, P.O. Box 12 03 27, 93025 Regensburg, Germany)

Abstract

Scarcity of resources, structural change during the further development of renewable energy sources, and their corresponding costs, such as increasing resource costs or penalties due to dirty production, lead industrial firms to adapt ecological actions. In this regard, research on energy utilization in production planning has received increased attention in the last years, resulting in a large number of research articles so far. With the paper at hand, we review the literature on energy-oriented production planning. The aim of this study is to derive similar core issues and related properties along energy-oriented models within hierarchical production planning. For this, we carry out a systematic literature review and analyze and synthesize 375 research articles. We classify the underlying literature with a novel two-dimensional classification scheme and identify three key topics and five frequently found characteristics, which are presented in detail throughout this article. Based on these results, we state several potentials for further research.

Suggested Citation

  • Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13317-:d:692930
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    References listed on IDEAS

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    1. Fei He & Kang Shen & Li Guan & Mingming Jiang, 2017. "Research on Energy-Saving Scheduling of a Forging Stock Charging Furnace Based on an Improved SPEA2 Algorithm," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    2. Tzu-Li Chen & Chen-Yang Cheng & Yi-Han Chou, 2020. "Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming," Annals of Operations Research, Springer, vol. 290(1), pages 813-836, July.
    3. Leilei Meng & Chaoyong Zhang & Xinyu Shao & Yaping Ren & Caile Ren, 2019. "Mathematical modelling and optimisation of energy-conscious hybrid flow shop scheduling problem with unrelated parallel machines," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1119-1145, February.
    4. Ozdamar, Linet & Birbil, Sevket Ilker, 1999. "A hierarchical planning system for energy intensive production environments," International Journal of Production Economics, Elsevier, vol. 58(2), pages 115-129, January.
    5. Mehdi Golari & Neng Fan & Tongdan Jin, 2017. "Multistage Stochastic Optimization for Production-Inventory Planning with Intermittent Renewable Energy," Production and Operations Management, Production and Operations Management Society, vol. 26(3), pages 409-425, March.
    6. Aghelinejad, MohammadMohsen & Ouazene, Yassine & Yalaoui, Alice, 2019. "Complexity analysis of energy-efficient single machine scheduling problems," Operations Research Perspectives, Elsevier, vol. 6(C).
    7. Sven Schulz & Udo Buscher & Liji Shen, 2020. "Multi-objective hybrid flow shop scheduling with variable discrete production speed levels and time-of-use energy prices," Journal of Business Economics, Springer, vol. 90(9), pages 1315-1343, November.
    8. Pham, An & Jin, Tongdan & Novoa, Clara & Qin, Jin, 2019. "A multi-site production and microgrid planning model for net-zero energy operations," International Journal of Production Economics, Elsevier, vol. 218(C), pages 260-274.
    9. Cheng-Hsiang Liu, 2016. "Mathematical programming formulations for single-machine scheduling problems while considering renewable energy uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1122-1133, February.
    10. Maria De Salvo & Sandra Notaro & Giuseppe Cucuzza & Laura Giuffrida & Giovanni Signorello, 2021. "Protecting the Local Landscape or Reducing Greenhouse Gas Emissions? A Study on Social Acceptance and Preferences towards the Installation of a Wind Farm," Sustainability, MDPI, vol. 13(22), pages 1-19, November.
    11. Zhai, Y. & Biel, K. & Zhao, F. & Sutherland, J. W., 2017. "Dynamic scheduling of a flow shop with on-site wind generation for energy cost reduction under real time electricity pricing," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 87366, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Sven Schulz, 2018. "A Multi-criteria MILP Formulation for Energy Aware Hybrid Flow Shop Scheduling," Operations Research Proceedings, in: Andreas Fink & Armin Fügenschuh & Martin Josef Geiger (ed.), Operations Research Proceedings 2016, pages 543-549, Springer.
    13. Artigues, Christian & Lopez, Pierre & Haït, Alain, 2013. "The energy scheduling problem: Industrial case-study and constraint propagation techniques," International Journal of Production Economics, Elsevier, vol. 143(1), pages 13-23.
    14. Fernandez, Mayela & Li, Lin & Sun, Zeyi, 2013. "“Just-for-Peak” buffer inventory for peak electricity demand reduction of manufacturing systems," International Journal of Production Economics, Elsevier, vol. 146(1), pages 178-184.
    15. Foumani, Mehdi & Smith-Miles, Kate, 2019. "The impact of various carbon reduction policies on green flowshop scheduling," Applied Energy, Elsevier, vol. 249(C), pages 300-315.
    16. Xiuli Wu & Xianli Shen & Qi Cui, 2018. "Multi-Objective Flexible Flow Shop Scheduling Problem Considering Variable Processing Time due to Renewable Energy," Sustainability, MDPI, vol. 10(3), pages 1-30, March.
    17. Biel, K. & Glock, C. H., 2017. "Prerequisites of efficient decentralized waste heat recovery and energy storage in production planning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 76907, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    18. Sun, Zeyi & Li, Lin & Bego, Andres & Dababneh, Fadwa, 2015. "Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system," International Journal of Production Economics, Elsevier, vol. 165(C), pages 112-119.
    19. Fang Wang & Yunqing Rao & Chaoyong Zhang & Qiuhua Tang & Liping Zhang, 2016. "Estimation of Distribution Algorithm for Energy-Efficient Scheduling in Turning Processes," Sustainability, MDPI, vol. 8(8), pages 1-20, August.
    20. Biel, K. & Glock, C. H., 2016. "Systematic literature review of decision support models for energy-efficient production planning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83071, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Dababneh, Fadwa & Li, Lin & Sun, Zeyi, 2016. "Peak power demand reduction for combined manufacturing and HVAC system considering heat transfer characteristics," International Journal of Production Economics, Elsevier, vol. 177(C), pages 44-52.
    22. Rapine, Christophe & Penz, Bernard & Gicquel, Céline & Akbalik, Ayse, 2018. "Capacity acquisition for the single-item lot sizing problem under energy constraints," Omega, Elsevier, vol. 81(C), pages 112-122.
    23. Wichmann, Matthias Gerhard & Johannes, Christoph & Spengler, Thomas Stefan, 2019. "Energy-oriented Lot-Sizing and Scheduling considering energy storages," International Journal of Production Economics, Elsevier, vol. 216(C), pages 204-214.
    24. Biel, K. & Glock, C. H., 2016. "On the use of waste heat in a two-stage production system with controllable production rates," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 82130, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    25. Biel, Konstantin & Glock, Christoph H., 2016. "On the use of waste heat in a two-stage production system with controllable production rates," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 174-190.
    26. Oussama Masmoudi & Alice Yalaoui & Yassine Ouazene & Hicham Chehade, 2017. "Lot-sizing in a multi-stage flow line production system with energy consideration," International Journal of Production Research, Taylor & Francis Journals, vol. 55(6), pages 1640-1663, March.
    27. En-da Jiang & Ling Wang, 2019. "An improved multi-objective evolutionary algorithm based on decomposition for energy-efficient permutation flow shop scheduling problem with sequence-dependent setup time," International Journal of Production Research, Taylor & Francis Journals, vol. 57(6), pages 1756-1771, March.
    28. Gahm, Christian & Denz, Florian & Dirr, Martin & Tuma, Axel, 2016. "Energy-efficient scheduling in manufacturing companies: A review and research framework," European Journal of Operational Research, Elsevier, vol. 248(3), pages 744-757.
    29. Sylverin Kemmoe & Damien Lamy & Nikolay Tchernev, 2017. "Job-shop like manufacturing system with variable power threshold and operations with power requirements," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6011-6032, October.
    30. Ramin, D. & Spinelli, S. & Brusaferri, A., 2018. "Demand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process," Applied Energy, Elsevier, vol. 225(C), pages 622-636.
    31. Konstantin Biel & Christoph H. Glock, 2017. "Prerequisites of efficient decentralized waste heat recovery and energy storage in production planning," Journal of Business Economics, Springer, vol. 87(1), pages 41-72, January.
    32. Ashok, S., 2006. "Peak-load management in steel plants," Applied Energy, Elsevier, vol. 83(5), pages 413-424, May.
    33. Rapine, Christophe & Goisque, Guillaume & Akbalik, Ayse, 2018. "Energy-aware lot sizing problem: Complexity analysis and exact algorithms," International Journal of Production Economics, Elsevier, vol. 203(C), pages 254-263.
    34. Leenders, Ludger & Bahl, Björn & Hennen, Maike & Bardow, André, 2019. "Coordinating scheduling of production and utility system using a Stackelberg game," Energy, Elsevier, vol. 175(C), pages 1283-1295.
    35. Lixin Tang & Huizhi Ren & Yang Yang, 2015. "Reheat furnace scheduling with energy consideration," International Journal of Production Research, Taylor & Francis Journals, vol. 53(6), pages 1642-1660, March.
    36. Liu, Ying & Dong, Haibo & Lohse, Niels & Petrovic, Sanja, 2016. "A multi-objective genetic algorithm for optimisation of energy consumption and shop floor production performance," International Journal of Production Economics, Elsevier, vol. 179(C), pages 259-272.
    37. Xenos, Dionysios P. & Mohd Noor, Izzati & Matloubi, Mitra & Cicciotti, Matteo & Haugen, Trond & Thornhill, Nina F., 2016. "Demand-side management and optimal operation of industrial electricity consumers: An example of an energy-intensive chemical plant," Applied Energy, Elsevier, vol. 182(C), pages 418-433.
    38. Zhou, Shengchao & Jin, Mingzhou & Du, Ni, 2020. "Energy-efficient scheduling of a single batch processing machine with dynamic job arrival times," Energy, Elsevier, vol. 209(C).
    39. Alain Haït & Christian Artigues, 2011. "A hybrid CP/MILP method for scheduling with energy costs," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 5(4), pages 471-489.
    40. Zhang, Hao & Cai, Jie & Fang, Kan & Zhao, Fu & Sutherland, John W., 2017. "Operational optimization of a grid-connected factory with onsite photovoltaic and battery storage systems," Applied Energy, Elsevier, vol. 205(C), pages 1538-1547.
    41. Yu, Mengmeng & Lu, Renzhi & Hong, Seung Ho, 2016. "A real-time decision model for industrial load management in a smart grid," Applied Energy, Elsevier, vol. 183(C), pages 1488-1497.
    42. Çağrı Latifoğlu & Pietro Belotti & Lawrence V. Snyder, 2013. "Models for production planning under power interruptions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(5), pages 413-431, August.
    43. Lvjiang Yin & Xinyu Li & Chao Lu & Liang Gao, 2016. "Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm," Sustainability, MDPI, vol. 8(12), pages 1-33, December.
    44. Jingjing Xu & Lei Wang, 2017. "A Feedback Control Method for Addressing the Production Scheduling Problem by Considering Energy Consumption and Makespan," Sustainability, MDPI, vol. 9(7), pages 1-14, July.
    45. Ding, Jian-Ya & Song, Shiji & Wu, Cheng, 2016. "Carbon-efficient scheduling of flow shops by multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 248(3), pages 758-771.
    46. Yevgenia Mikhaylidi & Hussein Naseraldin & Liron Yedidsion, 2015. "Operations scheduling under electricity time-varying prices," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 7136-7157, December.
    47. Kan Fang & Nelson Uhan & Fu Zhao & John Sutherland, 2013. "Flow shop scheduling with peak power consumption constraints," Annals of Operations Research, Springer, vol. 206(1), pages 115-145, July.
    48. Zheng, Huan-yu & Wang, Ling, 2015. "Reduction of carbon emissions and project makespan by a Pareto-based estimation of distribution algorithm," International Journal of Production Economics, Elsevier, vol. 164(C), pages 421-432.
    49. Zixiao Pan & Deming Lei & Qingyong Zhang, 2018. "A New Imperialist Competitive Algorithm for Multiobjective Low Carbon Parallel Machines Scheduling," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-13, April.
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    2. Marco Trost & Thorsten Claus & Frank Herrmann, 2022. "Social Sustainability in Production Planning: A Systematic Literature Review," Sustainability, MDPI, vol. 14(13), pages 1-31, July.
    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.

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