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Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing

Author

Listed:
  • Nasser Amaitik

    (Aston University)

  • Ming Zhang

    (Aston University)

  • Zezhong Wang

    (Aston University)

  • Yuchun Xu

    (Aston University)

  • Gareth Thomson

    (Aston University)

  • Yiyong Xiao

    (Beihang University)

  • Nikolaos Kolokas

    (Centre for Research and Technology Hellas)

  • Alexander Maisuradze

    (Harms & Wende GmbH & Co. KG)

  • Oscar Garcia

    (Information Catalyst of Enterprises)

  • Michael Peschl

    (Harms & Wende GmbH & Co. KG)

  • Dimitrios Tzovaras

    (Centre for Research and Technology Hellas)

Abstract

Industrial equipment/machinery is an important element of manufacturing. They are used for producing objects that people need for everyday use. Therefore, there is a challenge to adopt effective maintenance strategies to keep them well-functioning and well-maintained in production lines. This will save energy and materials and contribute genuinely to the circular economy and creating value. Remanufacturing or refurbishment is one of the strategies to extend life of such industrial equipment. The paper presents an initial framework of cost estimation model based on combination of activity-based costing (ABC) and human expertise to assist the decision-making on best life extension strategy (e.g. remanufacturing, refurbishment, repair) for industrial equipment. Firstly, ABC cost model is developed to calculate cost of life extension strategy to be used as a benchmark strategy. Next, expert opinions are employed to modify data of benchmark strategy, which is then used to estimate costs of other life extension strategies. The developed cost model has been implemented in VBA-based Excel® platform. A case study with application examples has been used to demonstrate the results of the initial cost model developed and its applicability in estimating and analysing cost of applying life extension strategy for industrial equipment. Finally, conclusions on the developed cost model have been reported.

Suggested Citation

  • Nasser Amaitik & Ming Zhang & Zezhong Wang & Yuchun Xu & Gareth Thomson & Yiyong Xiao & Nikolaos Kolokas & Alexander Maisuradze & Oscar Garcia & Michael Peschl & Dimitrios Tzovaras, 2022. "Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing," Circular Economy and Sustainability, Springer, vol. 2(4), pages 1425-1444, December.
    • Handle: RePEc:spr:circec:v:2:y:2022:i:4:d:10.1007_s43615-022-00154-0
    DOI: 10.1007/s43615-022-00154-0
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    References listed on IDEAS

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    1. Kirsten van Dam & Luca Simeone & Duygu Keskin & Brian Baldassarre & Monia Niero & Nicola Morelli, 2020. "Circular Economy in Industrial Design Research: A Review," Sustainability, MDPI, vol. 12(24), pages 1-19, December.
    2. Langmaak, Stephan & Wiseall, Stephen & Bru, Christophe & Adkins, Russell & Scanlan, James & Sóbester, András, 2013. "An activity-based-parametric hybrid cost model to estimate the unit cost of a novel gas turbine component," International Journal of Production Economics, Elsevier, vol. 142(1), pages 74-88.
    3. Wang, Yacan & Zhu, Quan & Krikke, Harold & Hazen, Benjamin, 2020. "How product and process knowledge enable consumer switching to remanufactured laptop computers in circular economy," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Qian, Li & Ben-Arieh, David, 2008. "Parametric cost estimation based on activity-based costing: A case study for design and development of rotational parts," International Journal of Production Economics, Elsevier, vol. 113(2), pages 805-818, June.
    5. Alessandro Fontana & Andrea Barni & Deborah Leone & Maurizio Spirito & Agata Tringale & Matteo Ferraris & Joao Reis & Gil Goncalves, 2021. "Circular Economy Strategies for Equipment Lifetime Extension: A Systematic Review," Sustainability, MDPI, vol. 13(3), pages 1-28, January.
    6. Cavalieri, Sergio & Maccarrone, Paolo & Pinto, Roberto, 2004. "Parametric vs. neural network models for the estimation of production costs: A case study in the automotive industry," International Journal of Production Economics, Elsevier, vol. 91(2), pages 165-177, September.
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    Cited by:

    1. Juan Angel Chica Urzola, 2024. "Manufacturing Operations Scheduling Based in a Multidimensional Sustainable Manufacturing Index (SMIik)," Circular Economy and Sustainability, Springer, vol. 4(2), pages 1339-1356, June.

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