Algorithmic Strategy for Simultaneous Optimization of Design and Maintenance of Multi-Component Industrial Systems
| Autor: | Améziane Aoussat, Oussama Adjoul, Khaled Benfriha, Chawki El Zant |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Optimal design
Risk Optimization Design Computer science 0211 other engineering and technologies 02 engineering and technology Plan (drawing) Multi-component industrial systems Sciences de l'ingénieur Industrial and Manufacturing Engineering Component (UML) Architecture Safety Risk Reliability and Quality Reliability (statistics) 021110 strategic defence & security studies 021103 operations research Dynamic maintenance Reliability Hybrid algorithm Quality Reliability engineering Term (time) Life Cycle Cost (LCC) Industrial systems Safety Total Operational Reliability (TOR) |
| Popis: | This article describes a new approach to simultaneous optimization of design and maintenance of large-scale multi-component industrial systems. This approach, in a form of an algorithm, aims to help designers in the search for solutions by characterizing the components and their architecture including maintenance issues. The aim is to improve the performance of the industrial systems by maximizing the Total Operational Reliability (TOR) at the lowest Life Cycle Cost (LCC). In the case of this research, the term "design" refers to the reliability properties of the components, possible redundancies, faulty component accessibility, and the ability to improve the component real-time monitoring architecture. The term “maintenance” refers to maintenance plan adapted to the opportunistic dynamic maintenance plan. Simultaneous optimization of design and maintenance is achieved by a two-level hybrid algorithm using evolutionary (genetic) algorithms. The first level identifies the optimal design solutions calculated relative to the TOR and the LCC. The second proposes a dynamic maintenance plan that maximizes the reliability of the system throughout its operating life. |
| Databáze: | OpenAIRE |
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