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Solving Complex Maintenance Planning Optimization Problems Using Stochastic Simulation and Multi-Criteria Fuzzy Decision Making - Softcover
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Master's Thesis from the year 2014 in the subject Mathematics - Applied Mathematics, grade: A+, Mälardalen University, language: English, abstract: The main goal of this project is to explore the use of stochastic simulation, genetic algorithms, fuzzy decision making and other tools for solving complex maintenance planning optimization problems. We use two different maintenance activities, corrective maintenance and preventive maintenance. Since the evaluation of specifc candidate maintenance policies can take a long time to execute and the problem of finding the optimal policy is both non-linear and non-convex, we propose the use of genetic algorithms (GA) for the optimization. The main task of the GA is to find the optimal maintenance policy, which involves: (1) the probability of breakdown, (2) calculation of the cost of corrective maintenance, (3) calculation of the cost of preventive maintenance and (4) calculation of ROI (Return On Investment). Another goal of this project is to create a decision making model for multi-criteria systems. To find a near-optimal maintenance policy, we need to have an overview over the health status of the system components. To model the health of a component we should find all the operational criteria that affect it. We also need to analyze alternative maintenance activities in order to make the best maintenance decisions. In order to do that, the TOPSIS method and fuzzy decision making has been used. To evaluate the proposed methodology, internal combustion engine cooling of a typical Scania truck was used as a case study.
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- PublisherGrin Verlag
- Publication date2014
- ISBN 10 365675618X
- ISBN 13 9783656756187
- BindingPaperback
- LanguageEnglish
- Number of pages108
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Solving Complex Maintenance Planning Optimization Problems Using Stochastic Simulation and Multi-Criteria Fuzzy Decision Making
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Solving Complex Maintenance Planning Optimization Problems Using Stochastic Simulation and Multi-Criteria Fuzzy Decision Making
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master's Thesis from the year 2014 in the subject Mathematics - Applied Mathematics, grade: A+, Mälardalen University, language: English, abstract: The main goal of this project is to explore the use of stochastic simulation, genetic algorithms, fuzzy decision making and other tools for solving complex maintenance planning optimization problems. We use two different maintenance activities, corrective maintenance and preventive maintenance. Since the evaluation of specifc candidate maintenance policies can take a long time to execute and the problem of finding the optimal policy is both non-linear and non-convex, we propose the use of genetic algorithms (GA) for the optimization. The main task of the GA is to find the optimal maintenance policy, which involves: (1) the probability of breakdown, (2) calculation of the cost of corrective maintenance, (3) calculation of the cost of preventive maintenance and (4) calculation of ROI (Return On Investment). Another goal of this project is to create a decision making model for multi-criteria systems. To find a near-optimal maintenance policy, we need to have an overview over the health status of the system components. To model the health of a component we should find all the operational criteria that affect it. We also need to analyze alternative maintenance activities in order to make the best maintenance decisions. In order to do that, the TOPSIS method and fuzzy decision making has been used. To evaluate the proposed methodology, internal combustion engine cooling of a typical Scania truck was used as a case study. 108 pp. Englisch. Seller Inventory # 9783656756187
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Solving Complex Maintenance Planning Optimization Problems Using Stochastic Simulation and Multi-Criteria Fuzzy Decision Making
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2014 in the subject Mathematics - Applied Mathematics, grade: A+, Mälardalen University, language: English, abstract: The main goal of this project is to explore the use of stochastic simulation, genetic algorithms, fuzzy decision making and other tools for solving complex maintenance planning optimization problems. We use two different maintenance activities, corrective maintenance and preventive maintenance. Since the evaluation of specifc candidate maintenance policies can take a long time to execute and the problem of finding the optimal policy is both non-linear and non-convex, we propose the use of genetic algorithms (GA) for the optimization. The main task of the GA is to find the optimal maintenance policy, which involves: (1) the probability of breakdown, (2) calculation of the cost of corrective maintenance, (3) calculation of the cost of preventive maintenance and (4) calculation of ROI (Return On Investment). Another goal of this project is to create a decision making model for multi-criteria systems. To find a near-optimal maintenance policy, we need to have an overview over the health status of the system components. To model the health of a component we should find all the operational criteria that affect it. We also need to analyze alternative maintenance activities in order to make the best maintenance decisions. In order to do that, the TOPSIS method and fuzzy decision making has been used. To evaluate the proposed methodology, internal combustion engine cooling of a typical Scania truck was used as a case study. Seller Inventory # 9783656756187
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Solving Complex Maintenance Planning Optimization Problems Using Stochastic Simulation and Multi-Criteria Fuzzy Decision Making
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Taschenbuch. Condition: Neu. Solving Complex Maintenance Planning Optimization Problems Using Stochastic Simulation and Multi-Criteria Fuzzy Decision Making | Sahar Tahvili | Taschenbuch | 108 S. | Englisch | 2014 | GRIN Verlag | EAN 9783656756187 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 105064021
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