IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i23p13317-d692930.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/23/13317/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/23/13317/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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).
    19. 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.
    20. Aghelinejad, MohammadMohsen & Ouazene, Yassine & Yalaoui, Alice, 2019. "Complexity analysis of energy-efficient single machine scheduling problems," Operations Research Perspectives, Elsevier, vol. 6(C).
    21. 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.
    22. Ashok, S., 2006. "Peak-load management in steel plants," Applied Energy, Elsevier, vol. 83(5), pages 413-424, May.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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).
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. 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).
    43. 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.
    44. 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).
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Marco Trost & Thorsten Claus & Frank Herrmann, 2023. "Master Production Scheduling with Consideration of Utilization-Dependent Exhaustion and Capacity Load," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    3. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Markus Hilbert & Andreas Dellnitz & Andreas Kleine, 2023. "Production planning under RTP, TOU and PPA considering a redox flow battery storage system," Annals of Operations Research, Springer, vol. 328(2), pages 1409-1436, September.
    2. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    3. 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.
    4. 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.
    5. Masmoudi, Oussama & Delorme, Xavier & Gianessi, Paolo, 2019. "Job-shop scheduling problem with energy consideration," International Journal of Production Economics, Elsevier, vol. 216(C), pages 12-22.
    6. 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.
    7. 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).
    8. Weiwei Cui & Lin Li & Zhiqiang Lu, 2019. "Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(2), pages 154-173, March.
    9. João M. R. C. Fernandes & Seyed Mahdi Homayouni & Dalila B. M. M. Fontes, 2022. "Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review," Sustainability, MDPI, vol. 14(10), pages 1-34, May.
    10. 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.
    11. Matthias Gerhard Wichmann & Christoph Johannes & Thomas Stefan Spengler, 2019. "An extension of the general lot-sizing and scheduling problem (GLSP) with time-dependent energy prices," Journal of Business Economics, Springer, vol. 89(5), pages 481-514, July.
    12. Beck, Fabian G. & Biel, Konstantin & Glock, Christoph H., 2019. "Integration of energy aspects into the economic lot scheduling problem," International Journal of Production Economics, Elsevier, vol. 209(C), pages 399-410.
    13. Ghorbanzadeh, Masoumeh & Ranjbar, Mohammad, 2023. "Energy-aware production scheduling in the flow shop environment under sequence-dependent setup times, group scheduling and renewable energy constraints," European Journal of Operational Research, Elsevier, vol. 307(2), pages 519-537.
    14. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria, 2020. "Towards circular economy in production planning: Challenges and opportunities," European Journal of Operational Research, Elsevier, vol. 287(1), pages 168-190.
    15. 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.
    16. Jin Huang & Liangliang Jin & Chaoyong Zhang, 2017. "Mathematical Modeling and a Hybrid NSGA-II Algorithm for Process Planning Problem Considering Machining Cost and Carbon Emission," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    17. Bohlayer, Markus & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2020. "Energy-intense production-inventory planning with participation in sequential energy markets," Applied Energy, Elsevier, vol. 258(C).
    18. Adrian Kampa & Iwona Paprocka, 2021. "Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times," Energies, MDPI, vol. 14(21), pages 1-25, November.
    19. Xiangxin An & Guojin Si & Tangbin Xia & Qinming Liu & Yaping Li & Rui Miao, 2022. "Operation and Maintenance Optimization for Manufacturing Systems with Energy Management," Energies, MDPI, vol. 15(19), pages 1-19, October.
    20. Mohamed Habib Jabeur & Sonia Mahjoub & Cyril Toublanc, 2023. "Sustainable Production Scheduling with On-Site Intermittent Renewable Energy and Demand-Side Management: A Feed-Animal Case Study," Energies, MDPI, vol. 16(14), pages 1-24, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13317-:d:692930. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.