IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i14p2783-d249976.html
   My bibliography  Save this article

Carbon Emission Evaluation Based on Multi-Objective Balance of Sewing Assembly Line in Apparel Industry

Author

Listed:
  • Xujing Zhang

    (College of Textile and Clothing Engineering, Soochow University, Suzhou 215021, China)

  • Yan Chen

    (College of Textile and Clothing Engineering, Soochow University, Suzhou 215021, China)

Abstract

Apparel manufacturing is an industry with high energy consumption and carbon emissions. With the development of the low-carbon economy, low-carbon production in the apparel manufacturing industry become more and more imperative. The apparel industry is encountering great challenges in reducing carbon emissions. Garment sewing comprises a large number of processes, machines and operators. However, the existing studies lack quantitative analysis of carbon sources in the sewing process. This study analyzed the carbon emission characteristics in garment sewing production. Evaluation models of carbon emission were established for the sewing process in this research and the factors of fabrics, accessories, sewing machines and operators were included in the models. The results showed that fabrics and accessories were the main sources of carbon emissions in garment sewing production. The second largest carbon emission source was sewing machines, followed by operators. According to the evaluation models, the number of machines, operators and the utilization rate of the machines were related to the balance of the assembly line. A multi-objective optimization model aimed at minimizing the time loss rate and smoothness index of the assembly line was established, and a fast and elitist multi-objective genetic algorithm was used to obtain the solution for carbon emission reduction. The men’s shirt assembly lines, based on three types of workstation layouts (the order of processes, the type of machines and the components of the garment), were applied to verify the effectiveness of the model and algorithm. The results indicated that the total carbon emissions of the three assembly lines based on balance optimization were less than that of the normal assembly line. The assembly line of the workstations arranged in the order of processes was the best assembly line since it had the highest efficiency and the lowest carbon emissions.

Suggested Citation

  • Xujing Zhang & Yan Chen, 2019. "Carbon Emission Evaluation Based on Multi-Objective Balance of Sewing Assembly Line in Apparel Industry," Energies, MDPI, vol. 12(14), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2783-:d:249976
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/14/2783/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/14/2783/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Borba, Leonardo & Ritt, Marcus & Miralles, Cristóbal, 2018. "Exact and heuristic methods for solving the Robotic Assembly Line Balancing Problem," European Journal of Operational Research, Elsevier, vol. 270(1), pages 146-156.
    2. Bukchin, Yossi & Raviv, Tal, 2018. "Constraint programming for solving various assembly line balancing problems," Omega, Elsevier, vol. 78(C), pages 57-68.
    3. Rafael Laurenti & Michael Redwood & Rita Puig & Björn Frostell, 2017. "Measuring the Environmental Footprint of Leather Processing Technologies," Journal of Industrial Ecology, Yale University, vol. 21(5), pages 1180-1187, October.
    4. Chau, C.K. & Leung, T.M. & Ng, W.Y., 2015. "A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings," Applied Energy, Elsevier, vol. 143(C), pages 395-413.
    5. Thompson, Edmund R., 2002. "Clustering of Foreign Direct Investment and Enhanced Technology Transfer: Evidence from Hong Kong Garment Firms in China," World Development, Elsevier, vol. 30(5), pages 873-889, May.
    6. Nanxi Wang & Daofang Chang & Xiaowei Shi & Jun Yuan & Yinping Gao, 2019. "Analysis and Design of Typical Automated Container Terminals Layout Considering Carbon Emissions," Sustainability, MDPI, vol. 11(10), pages 1-40, May.
    7. Agpak, Kursad & Gokcen, Hadi, 2005. "Assembly line balancing: Two resource constrained cases," International Journal of Production Economics, Elsevier, vol. 96(1), pages 129-140, April.
    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. Shashi & Piera Centobelli & Roberto Cerchione & Amit Mittal, 2021. "Managing sustainability in luxury industry to pursue circular economy strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 432-462, January.
    2. Caiping Zhang & Wenjie Yue & Deming Tan & Zhenkun Su, 2023. "Carbon performance evaluation system and practice analysis for the sustainable enterprises," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(1), pages 292-306, February.

    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. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    2. Eduardo Álvarez-Miranda & Jordi Pereira & Harold Torrez-Meruvia & Mariona Vilà, 2021. "A Hybrid Genetic Algorithm for the Simple Assembly Line Balancing Problem with a Fixed Number of Workstations," Mathematics, MDPI, vol. 9(17), pages 1-19, September.
    3. Boysen, Nils & Schulze, Philipp & Scholl, Armin, 2022. "Assembly line balancing: What happened in the last fifteen years?," European Journal of Operational Research, Elsevier, vol. 301(3), pages 797-814.
    4. Koltai, Tamás & Dimény, Imre & Gallina, Viola & Gaal, Alexander & Sepe, Chiara, 2021. "An analysis of task assignment and cycle times when robots are added to human-operated assembly lines, using mathematical programming models," International Journal of Production Economics, Elsevier, vol. 242(C).
    5. Patricia González-Vallejo & Radu Muntean & Jaime Solís-Guzmán & Madelyn Marrero, 2020. "Carbon Footprint of Dwelling Construction in Romania and Spain. A Comparative Analysis with the OERCO2 Tool," Sustainability, MDPI, vol. 12(17), pages 1-22, August.
    6. García-Villoria, Alberto & Corominas, Albert & Nadal, Adrià & Pastor, Rafael, 2018. "Solving the accessibility windows assembly line problem level 1 and variant 1 (AWALBP-L1-1) with precedence constraints," European Journal of Operational Research, Elsevier, vol. 271(3), pages 882-895.
    7. Domenico Gattuso & Domenica Savia Pellicanò, 2023. "HUs Fleet Management in an Automated Container Port: Assessment by a Simulation Approach," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    8. Pami Dua & B. N. GOLDAR & SMRUTI RANJAN BEHERA, 2011. "Foreign Direct Investment And Technology Spillover-- An Evaluation Across Different Clusters In India," Working papers 200, Centre for Development Economics, Delhi School of Economics.
    9. Bokyung Kim & Geunsub Kim & Moohong Kang, 2022. "Study on Comparing the Performance of Fully Automated Container Terminals during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(15), pages 1-13, August.
    10. Ana Ferreira & Manuel Duarte Pinheiro & Jorge de Brito & Ricardo Mateus, 2022. "Embodied vs. Operational Energy and Carbon in Retail Building Shells: A Case Study in Portugal," Energies, MDPI, vol. 16(1), pages 1-23, December.
    11. Mastrucci, Alessio & Marvuglia, Antonino & Leopold, Ulrich & Benetto, Enrico, 2017. "Life Cycle Assessment of building stocks from urban to transnational scales: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 316-332.
    12. Belen Moreno Santamaria & Fernando del Ama Gonzalo & Matthew Griffin & Benito Lauret Aguirregabiria & Juan A. Hernandez Ramos, 2021. "Life Cycle Assessment of Dynamic Water Flow Glazing Envelopes: A Case Study with Real Test Facilities," Energies, MDPI, vol. 14(8), pages 1-17, April.
    13. Zhu, Xuedong & Son, Junbo & Zhang, Xi & Wu, Jianguo, 2023. "Constraint programming and logic-based Benders decomposition for the integrated process planning and scheduling problem," Omega, Elsevier, vol. 117(C).
    14. Scholl, Armin & Becker, Christian, 2005. "A note on "An exact method for cost-oriented assembly line balancing"," International Journal of Production Economics, Elsevier, vol. 97(3), pages 343-352, September.
    15. Wang, Zhaohua & Liu, Qiang & Zhang, Bin, 2022. "What kinds of building energy-saving retrofit projects should be preferred? Efficiency evaluation with three-stage data envelopment analysis (DEA)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    16. Li, Zixiang & Kucukkoc, Ibrahim & Zhang, Zikai, 2020. "Branch, bound and remember algorithm for two-sided assembly line balancing problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 896-905.
    17. Nordås, Hildegunn Kyvik, 2007. "International production sharing: A case for a coherent policy framework," WTO Discussion Papers 11, World Trade Organization (WTO), Economic Research and Statistics Division.
    18. Hassan Zohali & Bahman Naderi & Vahid Roshanaei, 2022. "Solving the Type-2 Assembly Line Balancing with Setups Using Logic-Based Benders Decomposition," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 315-332, January.
    19. Liu, Xiuli & Guo, Pibin & Yue, Xiaohang & Qi, Xiaoyan & Guo, Shufeng & Zhou, Xijun, 2021. "Measuring metabolic efficiency of the Beijing–Tianjin–Hebei urban agglomeration: A slacks-based measures method," Resources Policy, Elsevier, vol. 70(C).
    20. Claudia Durán & Ivan Derpich & Raúl Carrasco, 2022. "Optimization of Port Layout to Determine Greenhouse Gas Emission Gaps," Sustainability, MDPI, vol. 14(20), pages 1-18, October.

    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:jeners:v:12:y:2019:i:14:p:2783-:d:249976. 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.