An availability-based design optimization by using a fuzzy goal programming approach
الموضوعات :zahra sobhani 1 , mahmoud Shahrokhi 2 , Alain bernard 3
1 - Iran,Kurdistan, Sanandaj, University of Kurdistan,
2 - Iran,Kurdistan, Sanandaj, University of Kurdistan,
3 - Digital Sciences Laboratory, LS2N UMR CNRS 6004, Ecole Centrale de Nantes, France
الکلمات المفتاحية: Goal programming, reliability (RBD), concurrent engineering, Markov model, Fuzzy theory,
ملخص المقالة :
Selecting systems configuration is a critical step in the safe design of systems. Optimizing systems configuration means maximizing their availability and minimizing their overall cost. In this regard, this paper aims to present a novel binary non-linear fuzzy goal programming (FGP) model to choose parts suppliers of multistate parallel series systems based on availability and manufacturing costs. Quantity-based discounts, components purchase cost, and penalties for delaying system construction were also considered. In addition, a fuzzy target programming model was applied to minimize deviations from goal values of expenses. A system reliability block diagram illustrates the system's status. The Markov chain model describes a sequence of possible events in which the probability of each event depends on the reliability of system parts. The other effect of ordering several pieces from the same supplier is considered (reducing the unit price of elements and increasing their delivery lead time). Model results indicate the practical application of this method to optimize system parts reliability, taking into account life cycle parameters, including system construction cost and operational reliability.
1. Ali Ahmed Qaid, A., Ahmad, R., Mustafa, S. A., & Mohammed, B. A. (2024) "A systematic reliability-centred maintenance framework with fuzzy computational integration–a case study of manufacturing process machinery," Journal of Quality in Maintenance Engineering, 30(2), 456-492. DOI: 10.1108/JQME-04-2022-0021.
2. Ezzeldin, R., Zelenakova, M., Abd-Elhamid, H. F., Pietrucha-Urbanik, K., & Elabd, S. (2023) "Hybrid optimization algorithms of firefly with GA and PSO for the optimal design of water distribution networks," Water, 15(10), 1906. DOI: 10.3390/w15101906.
3. Mirzaei, D., Behbahaninia, A., Abdalisousan, A., & Lavasani, S. M. M. (2023) "A novel approach to repair time prediction and availability assessment of the equipment in power generation systems using fuzzy logic and Monte Carlo simulation," Energy, 282, 128842. DOI: 10.1016/j.energy.2023.128842.
4. Mirzaei, D., Behbahaninia, A., Abdalisousan, A., & Miri Lavasani, S. M. (2023) "Annual availability assessment of a gas turbine power plant using Monte Carlo simulation based on fuzzy logic and an adaptive neuro-fuzzy repair time prediction system," Journal of Thermal Analysis and Calorimetry, 148(16), 8675-8696. DOI: 10.1016/j.energy.2023.128842.
5. Gomilanovic, M., Tanasijevic, M., & Stepanovic, S. (2022) "Determining the Availability of Continuous Systems at Open Pits Applying Fuzzy Logic," Energies, 15(18), 6786. DOI: 10.3390/en15186786.
6. Jazouli, T. (2011). A “design for availability” methodology for systems design and support. University of Maryland, College Park.
7. Gomilanovic, M., Tanasijevic, M., Stepanovic, S., & Miletic, F. (2023) "A Model for Determining Fuzzy Evaluations of Partial Indicators of Availability for High-Capacity Continuous Systems at Coal Open Pits Using a Neuro-Fuzzy Inference System," Energies, 16(7), 2958. DOI: 10.3390/en16072958.
8. Ke, J. C., Huang, H. I., & Lin, C. H. (2006) "Fuzzy analysis for steady-state availability: a mathematical programming approach," Engineering Optimization, 38(8), 909-921. DOI: 10.1080/03052150600795854.
9. Zakikhani, K., Nasiri, F., & Zayed, T. (2020) "Availability-based reliability-centered maintenance planning for gas transmission pipelines," International Journal of Pressure Vessels and Piping, 183, 104105. DOI: 10.1016/j.ijpvp.2020.104105.
10. Jagtap, H. P., Bewoor, A. K., Kumar, R., Ahmadi, M. H., & Chen, L. (2020) "Performance analysis and availability optimization to improve maintenance schedule for the turbo-generator subsystem of a thermal power plant using particle swarm optimization," Reliability Engineering & System Safety, 204, 107130. DOI: 10.1016/j.ress.2020.107130.
11. Soltanali, H., Garmabaki, A. H. S., Thaduri, A., Parida, A., Kumar, U., & Rohani, A. (2019) "Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing," Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(4), 682-697. DOI: 10.1177/1748006X18818266.
12. Hadroug, N., Hafaifa, A., Kouzou, A., & Chaibet, A. (2018) "Improvement of gas turbine availability using reliability modeling based on fuzzy System," In Advances in Technical Diagnostics: Proceedings of the 6th International Congress on Technical Diagnostic, ICDT2016, 12-16 September 2016, Gliwice, Poland 6 (pp. 15-28). Springer International Publishing.
13. Mehta, M., Singh, M., Francis, V., Singh, J., & Taufik, M. (2023) "Mathematical modelling, performance analysis and optimization for the availability of casting system using Markov integrated genetic algorithm approach," International Journal on Interactive Design and Manufacturing (IJIDeM), 1-11. DOI: 10.1007/s12008-023-01572-6.
14. Jagtap, H. P., Bewoor, A. K., Kumar, R., Ahmadi, M. H., Assad, M. E. H., & Sharifpur, M. (2021) "RAM analysis and availability optimization of thermal power plant water circulation system using PSO," Energy Reports, 7, 1133-1153. DOI: 10.1016/j.egyr.2020.12.025.
15. Mund, J., Junker, M., Bougouffa, S., Cha, S., & Vogel-Heuser, B. (2017, September) "Model-based availability analysis for automated production systems: a case study," In Proceedings of the 15th ACM-IEEE International Conference on Formal Methods and Models for System Design (pp. 46-55). DOI: 10.1007/978-3-540-79707-4_7.
16. Zakikhani, K. (2020) "Failure prediction and availability-based maintenance planning of gas transmission pipelines," (Doctoral dissertation, Concordia University).
17. Du, S., Zio, E., & Kang, R. (2017) "A new analytical approach for interval availability analysis of Markov repairable systems," IEEE Transactions on Reliability, 67(1), 118-128.
18. Galdino, S. and P. Maciel "Availability with input uncertainties using an interval-based approach," in 2010 IEEE International Conference on Systems, Man and Cybernetics. 2010. IEEE.
19. Ostadi, B., & Hamedankhah, R. (2021) "A two-stage reliability optimization approach for solving series–parallel redundancy allocation problem considering the sale of worn-out parts," Annals of Operations Research, 304(1), 381-396. DOI: 10.1007/s10479-021-04093-1.
20. Bahou, Z., Lemnaouar, M. R., & Krimi, I. (2024) "A dynamic availability analysis of an N-component production system with interdependency effects: a fractional-order approach," Production Engineering, 18(1), 99-115. DOI: 10.1007/s11740-023-01216-4
21. Rubinstein, R. Y., Levitin, G., Lisnianski, A., & Ben-Haim, H. (1997) "Redundancy optimization of static series-parallel reliability models under uncertainty," IEEE Transactions on Reliability, 46(4), 503-511.
22. Esfahani, M. S., Heidary, M. H., & Jaberi, S. (2014) “A simulated annealing algorithm for fuzzy reliability optimization model in series-parallel and standby systems,” International Journal of Industrial Engineering, 24(4), 413-422.
23. Özder, E. H., Eren, T., & Çetin, S. Ö. (2015) “Supplier selection with TOPSIS and goal programming methods: A case study,” Journal of Trends in the Development of Machinery and Associated Technology, 19(1), 109-112.
24. Jane, C. C., & Laih, Y. W. (2017) “Distribution and reliability evaluation of max-flow in dynamic multi-state flow networks,” European Journal of Operational Research, 259(3), 1045-1053. DOI:10.1016/j.ejor.2016.12.030.
25. Peng, R., Xiao, H., & Liu, H. (2017) “Reliability of multi-state systems with a performance sharing group of limited size,” Reliability Engineering & System Safety, 166, 164-170. DOI: 10.1016/j.ress.2016.09.008.
26. Li, Y. Y., Chen, Y., Yuan, Z. H., Tang, N., & Kang, R. (2017) “Reliability analysis of multi-state systems subject to failure mechanism dependence based on a combination method,” Reliability Engineering & System Safety, 166, 109-123. DOI:10.1016/j.ress.2016.11.007.
27. Montoro-Cazorla, D., & Pérez-Ocón, R. (2018) “Constructing a Markov process for modelling a reliability system under multiple failures and replacements,” Reliability Engineering & System Safety, 173, 34-47.
28. Ge, Q., Peng, H., van Houtum, G. J., & Adan, I. (2018) “Reliability optimization for series systems under uncertain component failure rates in the design phase,” International Journal of Production Economics, 196, 163-175. DOI:10.1016/j.ijpe.2017.10.022.
29. Carpitella, S., Certa, A., Izquierdo, J., & La Fata, C. M. (2018) “k-out-of-n systems: An exact formula for the stationary availability and multi-objective configuration design based on mathematical programming and TOPSIS,” Journal of Computational and Applied Mathematics, 330, 1007-1015. DOI:10.1016/j.cam.2017.01.006.
30. Kumar, G., Jain, V., & Gandhi, O. P. (2018) “Availability analysis of mechanical systems with condition-based maintenance using semi-Markov and evaluation of optimal condition monitoring interval,” Journal of Industrial Engineering International, 14(1), 119-131. DOI:10.1007/s40092-017-0212-z.
31. Mellal, M. A., & Zio, E. (2022) “Multi-objective availability and cost optimization by PSO and COA for series-parallel systems with subsystems failure dependencies,” Microprocessors and Microsystems, 89, 104422. DOI:10.1016/j.micpro.2021.104422.
32. Akrouche, J., Sallak, M., Châtelet, E., Abdallah, F., & Haj Chhadé, H. (2022) “An interval approach for the availability optimization of multi-state systems in the presence of aleatory and epistemic uncertainties,” ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 8(2), 021202. DOI:10.1115/1.4052461
33. Kumar, A., & Punia, D. (2022) “Performance Evaluation of Availability of Complex Repairable System and Selection of Optimal Performance Parameters Using Particle Swarm Optimization,” In Proceedings of the International Conference on Industrial and Manufacturing Systems (CIMS-2020) Optimization in Industrial and Manufacturing Systems and Applications (pp. 123-139). Springer International Publishing. DOI:10.1007/978-3-030-73495-4_9.
34. Kumar, A., Saini, M., Gupta, N., Sinwar, D., Sin
