IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i3p1651-d739319.html
   My bibliography  Save this article

Modularized Design of ACDCD: An Improved Spectral Clustering-Based Approach

Author

Listed:
  • Qiu-Ping Bi

    (College of Safety Science and Engineering, Liaoning Technical University, Fuxin 123000, China
    Key Laboratory of Mine Thermodynamic Disasters and Control of Ministry of Education, Liaoning Technical University, Fuxin 123000, China)

  • Yu-Cheng Li

    (School of Safety and Emergency Management Engineering, Taiyuan University of Technology, Taiyuan 030600, China)

  • Rong Li

    (College of Resources and Environmental Engineering, Jilin Institute of Chemical Technology, Jilin 132000, China)

  • Cheng Shen

    (School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China)

  • Huan-Zhi Lou

    (Engineering College, Gengdan Institute of Beijing University of Technology, Beijing 101301, China)

  • Yuan-Yuan Zhang

    (Engineering College, Gengdan Institute of Beijing University of Technology, Beijing 101301, China)

Abstract

The air curtain dust control device (ACDCD) utilizes the air curtain formed by high-speed gas ejected from an injection cavity to separate the driver working area from the roadheader pollution area, so as to achieve the purpose of dust control. The existing ACDCDs are customized for various roadheaders and various production conditions, which are not flexible enough and are difficult to industrialize. Meanwhile, the existing ACDCD has drawbacks such as its costly maintenance, difficulty in replacement of the core parts, and costly iterative design of products. Due to the growing resource demand and sustainable development needs, the ACDCD should be designed considering the full life cycle technology of the product. In this paper, we proposed a modular method of the ACDCD based on improved spectral cluster module division and proposed an improved air curtain dust control device (IACDCD). Specifically, a similarity matrix construction method considering the functional and structural correlation matrix of components was proposed to strengthen the connection relationship of components. Two existing ACDCDs and the IACDCD were modularized using the improved spectral cluster module division method. The results showed that the improved spectral clustering module division method could effectively improve the clustering effect. The results of the module division of the three ACDCDs proved that the IACDCD could effectively increase the replaceability and maintenance of the injection cavity, and then reduce the maintenance cost and iterative design cost of the ACDCD.

Suggested Citation

  • Qiu-Ping Bi & Yu-Cheng Li & Rong Li & Cheng Shen & Huan-Zhi Lou & Yuan-Yuan Zhang, 2022. "Modularized Design of ACDCD: An Improved Spectral Clustering-Based Approach," Sustainability, MDPI, vol. 14(3), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1651-:d:739319
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/3/1651/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/3/1651/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiong, Yixuan & Du, Gang & Jiao, Roger J., 2018. "Modular product platforming with supply chain postponement decisions by leader-follower interactive optimization," International Journal of Production Economics, Elsevier, vol. 205(C), pages 272-286.
    2. Vladimir Modrak & Slavomir Bednar & Pavol Semanco, 2016. "Decision-Making Approach to Selecting Optimal Platform of Service Variants," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-8, July.
    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. Leandro Gauss & Daniel P. Lacerda & Paulo A. Cauchick Miguel, 2021. "Module-based product family design: systematic literature review and meta-synthesis," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 265-312, January.
    2. Gauss, Leandro & Lacerda, Daniel P. & Cauchick Miguel, Paulo A., 2022. "Market-Driven Modularity: Design method developed under a Design Science paradigm," International Journal of Production Economics, Elsevier, vol. 246(C).
    3. Wu, Jun & Du, Gang & Jiao, Roger J., 2021. "Optimal postponement contracting decisions in crowdsourced manufacturing: A three-level game-theoretic model for product family architecting considering subcontracting," European Journal of Operational Research, Elsevier, vol. 291(2), pages 722-737.
    4. Camel, Afaf & Belhadi, Amine & Kamble, Sachin & Tiwari, Sunil & Touriki, Fatima Ezahra, 2024. "Integrating smart Green Product Platforming for carbon footprint reduction: The role of blockchain technology and stakeholders influence within the agri-food supply chain," International Journal of Production Economics, Elsevier, vol. 272(C).
    5. Ma, Yujie & Du, Gang & Jiao, Roger J., 2020. "Optimal crowdsourcing contracting for reconfigurable process planning in open manufacturing: A bilevel coordinated optimization approach," International Journal of Production Economics, Elsevier, vol. 228(C).
    6. Chen, Wenchong & Gong, Xuejian & Rahman, Humyun Fuad & Liu, Hongwei & Qi, Ershi, 2021. "Real-time order acceptance and scheduling for data-enabled permutation flow shops: Bilevel interactive optimization with nonlinear integer programming," Omega, Elsevier, vol. 105(C).
    7. Wang, Jian & He, Shulin, 2022. "Optimal decisions of modularity, prices and return policy in a dual-channel supply chain under mass customization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).

    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:14:y:2022:i:3:p:1651-:d:739319. 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.