2003 Fiscal Year Final Research Report Summary
A Study on an Optimal inspection Policy for Deterioration and Failure System
| Project/Area Number |
14580479
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
社会システム工学
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| Research Institution | Tottori University |
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Principal Investigator |
KAWAI Hajime Tottori University, Faculty of Engineering, Professor, 工学部, 教授 (50026316)
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| Co-Investigator(Kenkyū-buntansha) |
SATOW Takashi Tottori University, Faculty of Engineering, Assistant Researcher, 工学部, 助手 (30304405)
KOYANAGI Junji Tottori University, Faculty of Engineering, Assistant Professor, 工学部, 助教授 (90225590)
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| Project Period (FY) |
2002 – 2003
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| Keywords | Markov Deterioration / Inspection / Replacement / Optimal Policy / Maintenance Opportunity / Discount |
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| Research Abstract |
We report the outline of the research executed in 2002 and 2003 fiscal year.
Assumption that the maintenance activity is enforceable at arbitrariness is general. However, various restrictions actually exist, and it is difficult to execute the maintenance activity at arbitrariness. We paid attention to maintenance opportunity that can maintain the system.
On the other hand, in more than one component systems, failure mechanism is usually considered as a combination of several factors. The component fails not only due to its own deterioration, but also being caused by the failure of adjacent component. We proposed some theoretical models to these problems by using stochastic processes. As a typical instance, we derived an expected maintenance host per unit time over infinite time horizon. The function as a criteria function for decision making, we discussed optimal maintenance policies to minimize the expected cost rate. As a result, the condition of the existence of the optimum solution was able to be led.
The system which consisted of the discrete time failure unit and Markov-deterioration unit was considered. The optimal inspection and replacement problem was formulated as a Markov decision process with a discount. The structure of the optimal policy was analyzed, and the optimality of the area policy was clarified.
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