IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v145y2013i2p799-806.html
   My bibliography  Save this article

Reducing worker(s) by converting assembly line into a pure cell system

Author

Listed:
  • Yu, Yang
  • Tang, Jiafu
  • Sun, Wei
  • Yin, Yong
  • Kaku, Ikou

Abstract

The line-cell conversion is established as a new production system towards converting traditional conveyor assembly line to a cell system, in which one (or multiple) worker carries out all of the operations of a job in a cell. Its performance improvement can be enhanced by reducing worker(s) without decreasing productivity. How to conduct this conversion by determining how many cells should be formatted and which workers are assigned in a cell, is a complicated decision problem. This paper presents a multi-objective line-cell conversion model with the two goals of reducing worker(s) and increasing productivity simultaneously, in a production environment that converts traditional conveyor assembly line into a pure cell system. We identify several mathematical insights on solution space of the multi-objective line-cell conversion model and prove that it is an NP-hard problem. Then we provide an improved exact algorithm to obtain Pareto-optimal solutions of the multi-objective model. Several numerical simulation experiments are performed to illustrate that the line-cell conversion can be used to reduce worker(s) and the total throughput time at the same time.

Suggested Citation

  • Yu, Yang & Tang, Jiafu & Sun, Wei & Yin, Yong & Kaku, Ikou, 2013. "Reducing worker(s) by converting assembly line into a pure cell system," International Journal of Production Economics, Elsevier, vol. 145(2), pages 799-806.
    • Handle: RePEc:eee:proeco:v:145:y:2013:i:2:p:799-806
    DOI: 10.1016/j.ijpe.2013.06.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S092552731300279X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2013.06.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Yin-Yann & Cheng, Chen-Yang & Wang, Li-Chih & Chen, Tzu-Li, 2013. "A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry," International Journal of Production Economics, Elsevier, vol. 141(1), pages 66-78.
    2. Duan, Qinglin & Warren Liao, T., 2013. "Optimization of replenishment policies for decentralized and centralized capacitated supply chains under various demands," International Journal of Production Economics, Elsevier, vol. 142(1), pages 194-204.
    3. Kathryn E. Stecke & Yong Yin & Ikou Kaku & Yasuhiko Murase, 2012. "Seru: The Organizational Extension of JIT for a Super-Talent Factory," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 3(1), pages 106-119, January.
    4. Solimanpur, Maghsud & Elmi, Atabak, 2013. "A tabu search approach for cell scheduling problem with makespan criterion," International Journal of Production Economics, Elsevier, vol. 141(2), pages 639-645.
    5. Che, Ada & Chabrol, Michelle & Gourgand, Michel & Wang, Yuan, 2012. "Scheduling multiple robots in a no-wait re-entrant robotic flowshop," International Journal of Production Economics, Elsevier, vol. 135(1), pages 199-208.
    6. Wu, Tai-Hsi & Chang, Chin-Chih & Yeh, Jinn-Yi, 2009. "A hybrid heuristic algorithm adopting both Boltzmann function and mutation operator for manufacturing cell formation problems," International Journal of Production Economics, Elsevier, vol. 120(2), pages 669-688, August.
    7. Safaei, Nima & Tavakkoli-Moghaddam, Reza, 2009. "Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems," International Journal of Production Economics, Elsevier, vol. 120(2), pages 301-314, August.
    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. Li, Dongni & Lyu, Yao & Zhang, Jinhui & Cui, Zihua & Yin, Yong, 2024. "Order sequencing for a bucket brigade seru in a mass customization environment," International Journal of Production Economics, Elsevier, vol. 270(C).
    2. Kuo-Ching Ying & Yi-Ju Tsai, 2017. "Minimising total cost for training and assigning multiskilled workers in production systems," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2978-2989, May.
    3. Zhang, Zhe & Song, Xiaoling & Huang, Huijung & Zhou, Xiaoyang & Yin, Yong, 2022. "Logic-based Benders decomposition method for the seru scheduling problem with sequence-dependent setup time and DeJong’s learning effect," European Journal of Operational Research, Elsevier, vol. 297(3), pages 866-877.
    4. Zhe Zhang & Xiaoling Song & Huijun Huang & Yong Yin & Benjamin Lev, 2022. "Scheduling problem in seru production system considering DeJong’s learning effect and job splitting," Annals of Operations Research, Springer, vol. 312(2), pages 1119-1141, May.
    5. Ye Wang & Jiafu Tang, 2022. "Optimized skill configuration for the seru production system under an uncertain demand," Annals of Operations Research, Springer, vol. 316(1), pages 445-465, September.
    6. Yu, Yang & Tang, Jiafu & Gong, Jun & Yin, Yong & Kaku, Ikou, 2014. "Mathematical analysis and solutions for multi-objective line-cell conversion problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 774-786.
    7. Battaïa, Olga & Delorme, Xavier & Dolgui, Alexandre & Hagemann, Johannes & Horlemann, Anika & Kovalev, Sergey & Malyutin, Sergey, 2015. "Workforce minimization for a mixed-model assembly line in the automotive industry," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 489-500.
    8. Zhang, Zhe & Gong, Xue & Song, Xiaoling & Yin, Yong & Lev, Benjamin & Chen, Jie, 2022. "A column generation-based exact solution method for seru scheduling problems," Omega, Elsevier, vol. 108(C).

    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. Lin, Shih-Wei & Ying, Kuo-Ching & Lu, Chung-Cheng & Gupta, Jatinder N.D., 2011. "Applying multi-start simulated annealing to schedule a flowline manufacturing cell with sequence dependent family setup times," International Journal of Production Economics, Elsevier, vol. 130(2), pages 246-254, April.
    2. Zhang, XiaoLi & Liu, ChenGuang & Li, WenJuan & Evans, Steve & Yin, Yong, 2017. "Effects of key enabling technologies for seru production on sustainable performance," Omega, Elsevier, vol. 66(PB), pages 290-307.
    3. Zhang, Zhe & Song, Xiaoling & Gong, Xue & Yin, Yong & Lev, Benjamin & Zhou, Xiaoyang, 2024. "Coordinated seru scheduling and distribution operation problems with DeJong’s learning effects," European Journal of Operational Research, Elsevier, vol. 313(2), pages 452-464.
    4. Preil, Deniz & Krapp, Michael, 2022. "Bandit-based inventory optimisation: Reinforcement learning in multi-echelon supply chains," International Journal of Production Economics, Elsevier, vol. 252(C).
    5. Lili Wang & Min Li & Guanbin Kong & Haiwen Xu, 2024. "Joint decision-making for divisional seru scheduling and worker assignment considering process sequence constraints," Annals of Operations Research, Springer, vol. 338(2), pages 1157-1185, July.
    6. Dobromir Herzog, 2021. "Human factor aspects in information security management in the traditional IT and cloud computing models," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 93-108.
    7. Li, Dongni & Jiang, Yuzhou & Zhang, Jinhui & Cui, Zihua & Yin, Yong, 2023. "An on-line seru scheduling algorithm with proactive waiting considering resource conflicts," European Journal of Operational Research, Elsevier, vol. 309(2), pages 506-515.
    8. Faiza Hamdi & Ahmed Ghorbel & Faouzi Masmoudi & Lionel Dupont, 2018. "Optimization of a supply portfolio in the context of supply chain risk management: literature review," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 763-788, April.
    9. Duan, Qinglin & Liao, T. Warren, 2013. "A new age-based replenishment policy for supply chain inventory optimization of highly perishable products," International Journal of Production Economics, Elsevier, vol. 145(2), pages 658-671.
    10. Yu, Yang & Tang, Jiafu & Gong, Jun & Yin, Yong & Kaku, Ikou, 2014. "Mathematical analysis and solutions for multi-objective line-cell conversion problem," European Journal of Operational Research, Elsevier, vol. 236(2), pages 774-786.
    11. Junming Liu & Weiwei Chen & Jingyuan Yang & Hui Xiong & Can Chen, 2022. "Iterative Prediction-and-Optimization for E-Logistics Distribution Network Design," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 769-789, March.
    12. Wu, Lingxiao & Wang, Shuaian, 2018. "Exact and heuristic methods to solve the parallel machine scheduling problem with multi-processor tasks," International Journal of Production Economics, Elsevier, vol. 201(C), pages 26-40.
    13. Absalom E Ezugwu & Olawale J Adeleke & Serestina Viriri, 2018. "Symbiotic organisms search algorithm for the unrelated parallel machines scheduling with sequence-dependent setup times," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    14. Sadeghi, Parisa & Rebelo, Rui Diogo & Ferreira, José Soeiro, 2021. "Using variable neighbourhood descent and genetic algorithms for sequencing mixed-model assembly systems in the footwear industry," Operations Research Perspectives, Elsevier, vol. 8(C).
    15. Sun, Jing & Yamamoto, Hisashi & Matsui, Masayuki, 2020. "Horizontal integration management: An optimal switching model for parallel production system with multiple periods in smart supply chain environment," International Journal of Production Economics, Elsevier, vol. 221(C).
    16. Duan, Qinglin & Liao, T. Warren, 2014. "Optimization of blood supply chain with shortened shelf lives and ABO compatibility," International Journal of Production Economics, Elsevier, vol. 153(C), pages 113-129.
    17. T. V. S. R. K. Prasad & Kolla Srinivas & C. Srinivas, 2020. "Investigations into control strategies of supply chain planning models: a case study," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 874-907, September.
    18. Avci, Mualla Gonca & Selim, Hasan, 2018. "A multi-objective simulation-based optimization approach for inventory replenishment problem with premium freights in convergent supply chains," Omega, Elsevier, vol. 80(C), pages 153-165.
    19. Zhe Zhang & Xiaoling Song & Huijun Huang & Yong Yin & Benjamin Lev, 2022. "Scheduling problem in seru production system considering DeJong’s learning effect and job splitting," Annals of Operations Research, Springer, vol. 312(2), pages 1119-1141, May.
    20. Ye Wang & Jiafu Tang, 2022. "Optimized skill configuration for the seru production system under an uncertain demand," Annals of Operations Research, Springer, vol. 316(1), pages 445-465, September.

    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:eee:proeco:v:145:y:2013:i:2:p:799-806. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.