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DC Field | Value | Language |
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dc.contributor.author | Geng, H | - |
dc.contributor.author | Mousavi, A | - |
dc.contributor.author | Markatos, N | - |
dc.contributor.author | Chen, K | - |
dc.contributor.author | Gou, X | - |
dc.date.accessioned | 2024-04-03T19:29:04Z | - |
dc.date.available | 2024-04-03T19:29:04Z | - |
dc.date.issued | 2024-03-26 | - |
dc.identifier | ORCiD: Alireza Mousavi https://orcid.org/0000-0003-0360-2712 | - |
dc.identifier | ORCiD: Nikolaos Grigorios Markatos https://orcid.org/0000-0003-3953-6796 | - |
dc.identifier | 100001 | - |
dc.identifier.citation | Geng, H. et al. (2024) 'Reliable Cost Prediction and Control for Intelligent Manufacture: A Key Performance Indicator Perspective', International Journal of Network Dynamics and Intelligence, 3 (1), 100001, pp. 1 - 12. doi: 10.53941/ijndi.2024.100001. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/28690 | - |
dc.description | Data Availability Statement: Not applicable. Acknowledgments: We would like to thank Primal Electro for providing the industrial data. | en_US |
dc.description.abstract | Intelligent manufacturing is facing significant challenges in adapting to the ever-changing equipment, instrumentation, process and economics. Such a trend together with the pressure to reliably control and contain production costs means that frequent adjusting decisions are required to adapt to incessant volatility imposed on manufacturing systems. Under this circumstance, cost-effective and quality-guaranteed manufacturing strategies would be the most logical route to reducing production costs. In this paper, a novel dynamical cost prediction and control (CPC) model is proposed to support collective decision-making in intelligent manufacturing, where the model output is the real-time prediction of possible manufacturing costs, while the inputs are generic manufacturing key performance indicators covering inventory, product quality, production efficiency, resource utilisation and environmental impact. This proposed CPC model distinguishes itself from existing ones for its capability to translate manufacturing data (at both the physical level and operation management level) into financial metrics that contribute to forming a common language between engineering, financial and administrative departments of an enterprise. The case study about the assembly line of optoelectronic devices demonstrates that, although different enterprise departments have different priorities, our CPC model helps them to achieve certain consensus on intended production that finally creates satisfactory profitability for the company at controlled manufacturing costs. | en_US |
dc.description.sponsorship | Natural Science Foundation of Sichuan Province of China under Grant 23NSFSC1427; National Natural Science Foundation of China under Grants U2330206, U2230206, 62173068l European Union’s Horizon 2020 Research and Innovation Programme under Grant 820677 (IQONIC). | en_US |
dc.format.extent | 1 - 12 | - |
dc.format.medium | Electronic | - |
dc.language | English | - |
dc.language.iso | en | en_US |
dc.publisher | Scilight Press | en_US |
dc.rights | Copyright © 2024 by the authors. This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | intelligent manufacture | en_US |
dc.subject | reliable control | en_US |
dc.subject | cost prediction | en_US |
dc.subject | key performance indicator | en_US |
dc.title | Reliable Cost Prediction and Control for Intelligent Manufacture: A Key Performance Indicator Perspective | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.53941/ijndi.2024.100001 | - |
dc.relation.isPartOf | International Journal of Network Dynamics and Intelligence | - |
pubs.issue | 1 | - |
pubs.publication-status | Published | - |
pubs.volume | 3 | - |
dc.identifier.eissn | 2653-6226 | - |
dc.rights.license | https://creativecommons.org/licenses/by/4.0/leglacode.en | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Dept of Mechanical and Aerospace Engineering Research Papers Dept of Civil and Environmental Engineering Research Papers |
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FullText.pdf | Copyright © 2024 by the authors. This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). | 1.14 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License