Abstract
Due to technical progress and business competition, design alternatives and maintenance strategies have to be contemplated to optimize the performance of physical assets when new facilities are projected and built. That combined optimization (Design & Maintenance) is required by all industrial installations to develop their activity in an increasingly competitive environment. The Design and Maintenance combined optimization process is a complex problem which requires research and development. The objectives to optimize are Unavailability (due to production losses) and Maintenance Cost (due to overcharge when it is not optimal). The Design and Maintenance strategy for a technical system are optimized jointly by modifying its Functionability Profile, which is closely related to the system’s availability. The Functionability Profile is generated by applying Monte Carlo Simulation that allows characterizing the process’ randomness until the failure and to modify that Functionability Profile by the optimal Maintenance strategy. An application case is presented, where several configurations of the elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) are used to optimize the multi-objective problem, successfully finding non-dominated solutions with optimum performance for the simultaneous Design and Maintenance strategy combination.
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A. Cacereño is recipient of a contract from the Program of training for Predoctoral research staff of University of Las Palmas de Gran Canaria. The authors are grateful for this support.
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Cacereño, A., Galván, B., Greiner, D. (2021). Solving Multi-objective Optimal Design and Maintenance for Systems Based on Calendar Times Using NSGA-II. In: Gaspar-Cunha, A., Periaux, J., Giannakoglou, K.C., Gauger, N.R., Quagliarella, D., Greiner, D. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 55. Springer, Cham. https://doi.org/10.1007/978-3-030-57422-2_16
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DOI: https://doi.org/10.1007/978-3-030-57422-2_16
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