Abstract
This paper is devoted to developing an integrated model to minimise energy consumption while maintaining desired productivity in Bernoulli serial lines with unreliable machines and finite buffers. For small systems, such as three-and four-machine lines with small buffers, exact analysis to optimally allocate production capacity is introduced. For medium size systems (e.g. three-and four-machine lines with larger buffers, or five-machine lines with small buffers), an aggregation procedure to evaluate line production rate is introduced. Using it, optimal allocation of machine efficiency is searched to minimise energy consumption. Insights and allocation principles are obtained through the analyses. Finally, for larger systems, a fast and accurate heuristic algorithm is presented and validated through extensive numerical experiments to obtain optimal allocation of production capacity to minimise energy consumption while maintaining desired productivity. © 2017 Informa UK Limited, trading as Taylor & Francis Group.
| Original language | English |
|---|---|
| Pages (from-to) | 7356-7379 |
| Journal | International Journal of Production Research |
| Volume | 55 |
| Issue number | 24 |
| DOIs | |
| Publication status | Published - 13 Jul 2017 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
This work is supported in part by NSF [grant number CMMI-106365]; NIST [grant number 70NANB14H260]; National Science Foundation of China (NSFC) [grant number 71501109].
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
Research Keywords
- Bernoulli reliability model
- Energy efficient manufacturing
- Key performance indicator
- Probabilistic models
- Production modelling
- Reliability engineering
- Serial line
- Stochastic models
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