IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i10p1101-d553836.html
   My bibliography  Save this article

Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach

Author

Listed:
  • Hsin-Chieh Wu

    (Department of Industrial Engineering and Management, College of Science and Engineering, Chaoyang University of Science and Technology, Taichung 413310, Taiwan)

  • Horng-Ren Tsai

    (Department of Information Technology, Lingtung University, Taichung 408213, Taiwan)

  • Tin-Chih Toly Chen

    (Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan)

  • Keng-Wei Hsu

    (Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan)

Abstract

Analyzing energy consumption is an important task for a factory. In order to accomplish this task, most studies fit the relationship between energy consumption and product design features, process characteristics, or equipment types. However, the energy-saving effects of product yield learning are rarely considered. To bridge this gap, this study proposes a two-stage fuzzy approach to estimate the energy savings brought about by yield improvement. In the two-stage fuzzy approach, a fuzzy polynomial programming approach is first utilized to fit the yield-learning process of a product. Then, the relationship between monthly electricity consumption and increase in yield was fit to estimate the energy savings brought about by the improvement in yield. The actual case of a dynamic random-access memory factory was used to illustrate the applicability of the two-stage fuzzy approach. According to the experiment results, product yield learning can greatly reduce electricity consumption.

Suggested Citation

  • Hsin-Chieh Wu & Horng-Ren Tsai & Tin-Chih Toly Chen & Keng-Wei Hsu, 2021. "Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach," Mathematics, MDPI, vol. 9(10), pages 1-17, May.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:10:p:1101-:d:553836
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/10/1101/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/10/1101/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hongping Wang & Xi Lu & Yuxian Du & Chenwei Zhang & Rehan Sadiq & Yong Deng, 2017. "Fault tree analysis based on TOPSIS and triangular fuzzy number," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(4), pages 2064-2070, December.
    2. Kumar, Rakesh & Mishra, J.S. & Mondal, Surajit & Meena, Ram Swaroop & Sundaram, P.K. & Bhatt, B.P. & Pan, R.S. & Lal, Rattan & Saurabh, Kirti & Chandra, Naresh & Samal, S.K. & Hans, Hansraj & Raman, R, 2021. "Designing an ecofriendly and carbon-cum-energy efficient production system for the diverse agroecosystem of South Asia," Energy, Elsevier, vol. 214(C).
    3. Guo, Peijun & Tanaka, Hideo, 2006. "Dual models for possibilistic regression analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 253-266, November.
    4. Min-Suk Jo & Jang-Hoon Shin & Won-Jun Kim & Jae-Weon Jeong, 2017. "Energy-Saving Benefits of Adiabatic Humidification in the Air Conditioning Systems of Semiconductor Cleanrooms," Energies, MDPI, vol. 10(11), pages 1-23, November.
    5. Toly Chen & Li-Chih Wang & Min-Chi Chiu, 2018. "A multi-granularity approach for estimating the sustainability of a factory simulation model: semiconductor packaging as an example," Operational Research, Springer, vol. 18(3), pages 711-729, October.
    6. Panno, Domenico & Messineo, Antonio & Dispenza, Antonella, 2007. "Cogeneration plant in a pasta factory: Energy saving and environmental benefit," Energy, Elsevier, vol. 32(5), pages 746-754.
    7. Chang, Cheng-Kuang & Hu, Shih-Cheng & Liu, Vincent & Chan, David Yi-Liang & Huang, Chin-Yi & Weng, Ling-Chia, 2012. "Specific energy consumption of dynamic random access memory module supply chain in Taiwan," Energy, Elsevier, vol. 41(1), pages 508-513.
    8. Yu-Cheng Lin & Toly Chen, 2013. "A Biobjective Fuzzy Integer-Nonlinear Programming Approach for Creating an Intelligent Location-Aware Service," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-11, November.
    9. Toly Chen, 2014. "Strengthening the Competitiveness and Sustainability of a Semiconductor Manufacturer with Cloud Manufacturing," Sustainability, MDPI, vol. 6(1), pages 1-16, January.
    10. Shijin Wang & Xiaodong Wang & Feng Chu & Jianbo Yu, 2020. "An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production," International Journal of Production Research, Taylor & Francis Journals, vol. 58(8), pages 2283-2314, April.
    11. Dipankar Chakraborty & Dipak Kumar Jana & Tapan Kumar Roy, 2016. "A new approach to solve fully fuzzy transportation problem using triangular fuzzy number," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 26(2), pages 153-179.
    12. Sonntag, Danja & Kiesmüller, Gudrun P., 2018. "Disposal versus rework – Inventory control in a production system with random yield," European Journal of Operational Research, Elsevier, vol. 267(1), pages 138-149.
    13. Hu, Shih-Cheng & Xu, Tengfang & Chaung, Tony & Chan, David Y.-L., 2010. "Characterization of energy use in 300 mm DRAM (Dynamic Random Access Memory) wafer fabrication plants (fabs) in Taiwan," Energy, Elsevier, vol. 35(9), pages 3788-3792.
    14. Wadhah Abualfaraa & Konstantinos Salonitis & Ahmed Al-Ashaab & Maher Ala’raj, 2020. "Lean-Green Manufacturing Practices and Their Link with Sustainability: A Critical Review," Sustainability, MDPI, vol. 12(3), pages 1-21, January.
    Full references (including those not matched with items on IDEAS)

    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. Anna Horzela & Jakub Semrau, 2021. "Using Tools to Improve Logistics and Production Processes in a Selected Construction Company," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 1211-1232.
    2. 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.
    3. Mehdi Salimi & Mahboubeh Khodaparast, 2019. "Providing a combined model of fuzzy AHP and numerical taxonomy analysis for sport organizational ranking and performance appraisal," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 1133-1144, October.
    4. Maria Ferraro & Paolo Giordani, 2012. "A multiple linear regression model for imprecise information," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1049-1068, November.
    5. Hsien-Chung Wu, 2019. "Solving Fuzzy Linear Programming Problems with Fuzzy Decision Variables," Mathematics, MDPI, vol. 7(7), pages 1-105, June.
    6. Manuel Arana-Jiménez & Carmen Sánchez-Gil, 2020. "On generating the set of nondominated solutions of a linear programming problem with parameterized fuzzy numbers," Journal of Global Optimization, Springer, vol. 77(1), pages 27-52, May.
    7. Lisa Branchini & Maria Chiara Bignozzi & Benedetta Ferrari & Barbara Mazzanti & Saverio Ottaviano & Marcello Salvio & Claudia Toro & Fabrizio Martini & Andrea Canetti, 2021. "Cogeneration Supporting the Energy Transition in the Italian Ceramic Tile Industry," Sustainability, MDPI, vol. 13(7), pages 1-17, April.
    8. Arshad Ali & Yuvraj Gajpal & Tarek Y. Elmekkawy, 2021. "Distributed permutation flowshop scheduling problem with total completion time objective," OPSEARCH, Springer;Operational Research Society of India, vol. 58(2), pages 425-447, June.
    9. Tin-Chih Toly Chen, 2017. "Cloud intelligence in manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1057-1059, June.
    10. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.
    11. Badami, M. & Camillieri, F. & Portoraro, A. & Vigliani, E., 2014. "Energetic and economic assessment of cogeneration plants: A comparative design and experimental condition study," Energy, Elsevier, vol. 71(C), pages 255-262.
    12. Compernolle, Tine & Witters, Nele & Van Passel, Steven & Thewys, Theo, 2011. "Analyzing a self-managed CHP system for greenhouse cultivation as a profitable way to reduce CO2-emissions," Energy, Elsevier, vol. 36(4), pages 1940-1947.
    13. Andrzej Bożek, 2020. "Energy Cost-Efficient Task Positioning in Manufacturing Systems," Energies, MDPI, vol. 13(19), pages 1-21, September.
    14. Wang, Kung-Jeng & Lin, Chiuhsiang Joe & Dagne, Teshome Bekele & Woldegiorgis, Bereket Haile, 2022. "Bilayer stochastic optimization model for smart energy conservation systems," Energy, Elsevier, vol. 247(C).
    15. Toly Chen & Chi-Wei Lin, 2017. "Estimating the simulation workload for factory simulation as a cloud service," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1139-1157, June.
    16. Messineo, Antonio & Volpe, Roberto & Marvuglia, Antonino, 2012. "Ligno-cellulosic biomass exploitation for power generation: A case study in sicily," Energy, Elsevier, vol. 45(1), pages 613-625.
    17. An, Xiangxin & Si, Guojin & Xia, Tangbin & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2023. "An energy-efficient collaborative strategy of maintenance planning and production scheduling for serial-parallel systems under time-of-use tariffs," Applied Energy, Elsevier, vol. 336(C).
    18. Toly Chen & Yi-Chi Wang & Zhirong Lin, 2017. "Predictive distant operation and virtual control of computer numerical control machines," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1061-1077, June.
    19. Konstantaras, Ioannis & Skouri, Konstantina & Benkherouf, Lakdere, 2021. "Optimizing inventory decisions for a closed–loop supply chain model under a carbon tax regulatory mechanism," International Journal of Production Economics, Elsevier, vol. 239(C).
    20. Hsien-Chung Wu, 2023. "Solving Fuzzy Optimization Problems Using Shapley Values and Evolutionary Algorithms," Mathematics, MDPI, vol. 11(24), pages 1-26, December.

    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:jmathe:v:9:y:2021:i:10:p:1101-:d:553836. 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.