Yes / The paper contributes to development of RMS through linkage with external stakeholders such as customers and
suppliers of parts/raw materials to handle demand fluctuations that necessitate information sharing across the supply
chain tiers. RMS is developed as an integrated supply chain hub for adjusting production capacity using a hybrid
methodology of decision trees and Markov analysis. The proposed Markov Chain model contributes to evaluate and
monitor system reconfigurations required due to changes of product families with consideration of the product life
cycles. The simulation findings indicate that system productivity and financial performance in terms of the profit contribution
of product-process allocation will vary over configuration stages. The capacity of an RMS with limited product
families and/or limited model variants becomes gradually inoperative whilst approaching upcoming configuration stages
due to the end of product life cycles. As a result, reconfiguration preparation is suggested quite before ending life cycle
of an existing product in process, for switching from a product family to a new/another product family in the production
range, subject to its present demand. The proposed model is illustrated through a simplified case study with given
product families and transition probabilities.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/11464 |
| Date | 09 June 2016 |
| Creators | Abdi, M. Reza, Labib, A.W. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Accepted manuscript |
| Rights | © 2017 Taylor & Francis. This is an Author's Original Manuscript of an article published by Taylor & Francis in International Journal of Production Research in 2016, available online at https://doi.org/10.1080/00207543.2016.1229066 |
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