Towards sustainable manufacturing by enabling optimum selection of life extension strategy for industrial equipment based on cost modelling

Abstract

Sustainable manufacturing is of great importance in today’s world. In manufacturing, keep industrial equipment well-functioning is important because failure of equipment leads to significant financial and production losses. In addition, disposal of such failed equipment is both costly and environmentally unfriendly and does not recover any residual value. This raises the need to adopt methods and means that help extending the life of equipment and reduce waste of material. This paper presents a digital toolkit of cost model to estimate and understand the costs to be incurred when applying life extension strategy for industrial equipment. It is meant to be integrated with other tools and methodologies to enable end-users to perform optimal decision-making regarding which life extension strategy (e.g., remanufacturing, refurbishment, repair) to implement for large industrial equipment that is towards its end-of-life or needs maintenance, taking into account criteria such as cost, machine performance, and energy consumption. The cost model developed integrates a combination of parametric costing and activity-based costing methods to per form cost estimation. It has been implemented in an Excel-based Macro platform. A case study with application scenarios has been conducted to demonstrate the application of the cost model to optimize life extension strategies for industrial equipment. Finally, conclusions on the developed cost model have been reported.

Publication DOI: https://doi.org/10.1007/s13243-023-00129-w
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Smart and Sustainable Manufacturing
Funding Information: The work described in this paper is part of the RECLAIM project “REmanufaCturing and Refurbishment LArge Industrial equipMent” and received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869884.
Additional Information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Funding: The work described in this paper is part of the RECLAIM project “REmanufaCturing and Refurbishment LArge Industrial equipMent” and received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869884.
Uncontrolled Keywords: Asset management,Circular economy,Cost modelling,Decision making,Digital manufacturing,Industrial engineering,Industrial equipment,Life extension,Maintenance,Refurbishment,Remanufacturing,Smart manufacturing,Sustainable manufacturing,Waste Management and Disposal,Industrial and Manufacturing Engineering,Management, Monitoring, Policy and Law
Publication ISSN: 2210-4690
Last Modified: 24 May 2024 07:19
Date Deposited: 12 Sep 2023 08:52
Full Text Link:
Related URLs: https://link.sp ... -w#article-info (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-11
Published Online Date: 2023-09-05
Accepted Date: 2023-08-14
Authors: Amaitik, Nasser (ORCID Profile 0000-0002-0962-4341)
Zhang, Ming (ORCID Profile 0000-0001-5202-5574)
Xu, Yuchun (ORCID Profile 0000-0001-6388-813X)
Thomson, Gareth A. (ORCID Profile 0000-0002-7104-4348)
Kolokas, Nikolaos
Maisuradze, Alexander
Peschl, Michael
Tzovaras, Dimitrios

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