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- Bohlin, Markus, et al.
(författare)
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A Tool for Gas Turbine Maintenance Scheduling
- 2009. - 20
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Ingår i: Proceedings of the Twenty-First Conference on Innovative Applications of Artificial Intelligence (IAAI'09). - : IEEE Computer Society. - 9781577354239
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Konferensbidrag (refereegranskat)abstract
- We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines. The tool is used to plan the maintenance for turbines manufactured and maintained by Siemens Industrial Turbomachinery AB (SIT AB) with the goal to reduce the direct maintenance costs and the often very costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that feasibility in it is NP-complete. We outline a heuristic algorithm that can quickly solve the problem for practical purposes, and validate the approach on a real-world scenario based on an oil production facility. We also compare the performance of our algorithm with results from using mixed integer linear programming, and discuss the deployment of the application. The experimental results indicate that downtime reductions up to 65% can be achieved, compared to traditional preventive maintenance. In addition, using our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days with 12%. Compared to a mixed integer programming approach, our algorithm not optimal, but is orders of magnitude faster and produces results which are useful in practice. Our test results and SIT AB’s estimates based on operational use both indicate that significant savings can be achieved by using our software tool, compared to maintenance plans with fixed intervals.
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| 2. |
- Bohlin, Markus, et al.
(författare)
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Optimization of condition-based maintenance for industrial gas turbines: Requirements and results
- 2009
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Ingår i: Proceedings of the ASME Turbo Expo Volume 5. - 9780791848869 ; , s. 455-464
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Konferensbidrag (refereegranskat)abstract
- In oil and gas applications, the careful planning and execution of preventive maintenance is important due to the high costs associated with shutdown of critical equipment. Optimization and lifetime management for equipment such as gas turbines is therefore crucial in order to achieve high availability and reliability. In this paper, a novel condition-based gas turbine maintenance strategy is described and evaluated. Using custom-madegas turbine maintenance planning software, maintenance is repeatedly reoptimized to fit into the time intervals where production losses are least costly and result in the lowest possible impact. The strategy focuses on accurate online lifetime estimates for gas turbine components, where algorithms predicting future maintenance requirements are used to produce maintenance deadlines. This ensures that the gas turbines are maintained in accordance with the conditions on site. To show the feasibility and economic effects of a customer-adapted maintenance planning process, the maintenance plan for a gas turbine used in a real-world scenario is optimized using a combinatorial optimization algorithm and input from gas turbine operation data, maintenance schedules and operator requirements. The approach was validated through the inspection of a reference gas turbine after a predetermined time interval. It is shown that savings may be substantial compared to a traditional preventivemaintenance plan. In the evaluation, typical cost reductions range from 25 to 65 %. The calculated availability increase in practice is estimated to range from 0.5 to 1 %. In addition, down-time reductions of approximately 12 % are expected, due solely to improved planning. This indicates significant improvements.
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