Real-Time Decision Support System for Dynamic Optimization in Multi-Product Process Manufacturing
The implementation of adaptive optimization in multi-product process manufacturing is a crucial strategy for the reduction of unplanned downtime and the enhancement of overall productivity. Nevertheless, the availability of real-time decision support tools for dynamic adjustments in large-scale indu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10933954/ |
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| Summary: | The implementation of adaptive optimization in multi-product process manufacturing is a crucial strategy for the reduction of unplanned downtime and the enhancement of overall productivity. Nevertheless, the availability of real-time decision support tools for dynamic adjustments in large-scale industries is currently limited. In response to this challenge, we propose a novel model that processes data collected from extensive manufacturing operations. By leveraging Explainable Artificial Intelligence, we developed a real-time decision support system designed to dynamically adjust process parameters following varying input variables. The proposed model achieved a capture rate of 62% of the minority of products that cause micro-stoppages due to non-compliance with specifications. This approach provides a robust framework for adaptive optimization in complex and large-scale manufacturing environments, enhancing productivity and resilience against unplanned disruptions. |
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| ISSN: | 2169-3536 |