| 1. |
- Bohlin, Markus, et al.
(författare)
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Searching for gas turbine maintenance schedules
- 2010
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Ingår i: The AI Magazine. - : Wiley. - 0738-4602. ; 31:1, s. 21-36
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Tidskriftsartikel (refereegranskat)abstract
- Preventive-maintenance schedules occurring in industry are often suboptimal with regard to maintenance coallocation, loss-of-production costs, and availability. We describe the implementation and deployment of a software decision support, tool for the maintenance planning of gas turbines, with the goal of reducing the direct maintenance costs and the often costly production losses during maintenance down time. The optimization problem is formally defined, and we argue that the feasibility version 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 result's from using integer programming and d'iscuss the deployment of the application. The experimental results indicate that down time reductions up to 65 percent can be achieved, compared to traditional preventive maintenance. In addition, the use of our tool is expected to improve availability by up to 1 percent and to reduce the number of planned maintenance days by 12 percent. Compared to an integer programming approach, our algorithm is not optimal but is much faster and produces results that 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. |
- Doganay, Kivanc, et al.
(författare)
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Maintenance plan optimization for a train fleet
- 2010. - 10
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Ingår i: WIT Transactions on the Built Environment Volume 114. - 9781845644680 ; , s. 349-358
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Konferensbidrag (refereegranskat)abstract
- Maintenance planning is an important problem for railways, as well as other application domains that employ machinery with expensive replacements and high downtime costs. In a previous paper, we have developed methods for efficiently finding optimized maintenance schedules for a single unit, and proposed that the maintenance plan should be continuously re-optimized based on the condition of components. However, fleet-level resources, such as the availability of expensive spare parts, have largely been ignored. In this paper, we extend our previous approach by proposing a solution for the fleet level maintenance scheduling problem with spare parts optimization. The new solution is based on a mixed integer linear programming formulation of the problem. We demonstrate the merits of our approach by optimizing instances of maintenance schedules based on maintenance data from railway companies operating in Sweden.
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| 3. |
- Östlund, Stefan, 1961-, et al.
(författare)
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An Integrated Adaptive Maintenance Concept
- 2010
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Ingår i: International Conference on Condition Monitoring and Diagnosis 2010. - Tokyo, Japan.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this paper, we present a novel maintenance concept based on condition monitoring and dynamic maintenance packaging, by showing how to connect the information flow from low-level sensors to high-level operations and planning under uncertainty. Today, condition-based maintenance systems are focused on data collection and custom-made rule based systems for data analysis. In many cases, the focus is on measuring "everything" without considering how to use the measurements. In addition, the measurements are often noisy and the future is unpredictable which adds a lot of uncertainty. As a consequence, maintenance is often planned in advance and not replanned when new condition data is available. This often reduces the benefits of condition monitoring. The concept is based on the combination of robust, dynamically adapted maintenance optimization and statistical data analysis where the uncertainty is considered. This approach ties together low-level data acquisition and high-level planning and optimization. The concept has been illustrated in a context of rail vehicle maintenance, where measurements of brake pad and pantograph contact strip wear is used to predict the near future condition, and plan the maintenance activities.
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