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Mathematical Model Assisted Six-Sigma Approach for Reducing the Logistics Costs of a Pipe Manufacturing Company: A Novel Experimental Approach

Author

Listed:
  • Âli Yurdun Orbak

    (Department of Industrial Engineering, Bursa Uludag University, Gorukle, Bursa 16059, Turkey)

  • Metin Küçük

    (Graduate School of Applied Science, Bursa Uludag University, Gorukle, Bursa 16059, Turkey
    Quality Engineer & Customer Representative, Bosch GmbH, Bursa 16159, Turkey)

  • Mehmet Akansel

    (Department of Industrial Engineering, Bursa Uludag University, Gorukle, Bursa 16059, Turkey)

  • Shubham Sharma

    (Department of Mechanical Engineering, University Centre for Research and Development, Chandigarh University, Punjab 140413, India
    School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China)

  • Changhe Li

    (School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China)

  • Raman Kumar

    (Department of Mechanical and Production Engineering, Guru Nanak Dev Engineering College, Ludhiana 141006, India)

  • Sunpreet Singh

    (Department of Mechanical Engineering, University Centre for Research and Development, Chandigarh University, Punjab 140413, India
    Department of Mechanical Engineering, National University of Singapore, Singapore 119077, Singapore)

  • Gianpaolo Di Bona

    (Department of Civil and Industrial Engineering, University of Cassino and Southern Lazio, 03043 Cassino, Italy)

Abstract

This research addresses and analyzes the results of a six-sigma approach used to optimize the logistics costs of a pipe manufacturing company. Two mathematical models are developed for containers to control the company’s logistics. The Mathematical Programming Language (MPL) software is used to generate and solve these models. The results verify that the proposed mathematical models result in the company’s logistics improvement, especially in the DMAIC (define, measure, analyze, improve, and control) cycle by providing flexibility in choosing the most appropriate containers for logistics.

Suggested Citation

  • Âli Yurdun Orbak & Metin Küçük & Mehmet Akansel & Shubham Sharma & Changhe Li & Raman Kumar & Sunpreet Singh & Gianpaolo Di Bona, 2023. "Mathematical Model Assisted Six-Sigma Approach for Reducing the Logistics Costs of a Pipe Manufacturing Company: A Novel Experimental Approach," Mathematics, MDPI, vol. 11(3), pages 1-18, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:621-:d:1047345
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    References listed on IDEAS

    as
    1. Chen, C. S. & Lee, S. M. & Shen, Q. S., 1995. "An analytical model for the container loading problem," European Journal of Operational Research, Elsevier, vol. 80(1), pages 68-76, January.
    2. Ozlem Ergun & Gultekin Kuyzu & Martin Savelsbergh, 2007. "Reducing Truckload Transportation Costs Through Collaboration," Transportation Science, INFORMS, vol. 41(2), pages 206-221, May.
    3. Varun Tripathi & Somnath Chattopadhyaya & Alok Kumar Mukhopadhyay & Shubham Sharma & Changhe Li & Gianpaolo Di Bona, 2022. "A Sustainable Methodology Using Lean and Smart Manufacturing for the Cleaner Production of Shop Floor Management in Industry 4.0," Mathematics, MDPI, vol. 10(3), pages 1-23, January.
    Full references (including those not matched with items on IDEAS)

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