Abstract
Tool reliability is one of the most important issues in a flexible manufacturing system. If a tool fails to operate correctly, the performance of the manufacturing system is reduced, the due date may be violated, or the product quality falls behind the standards. This paper develops a bi-objective mathematical model for tool selection in a flexible manufacturing system in order to optimize both reliability and cost. The tools in these environments are considered to have increasing failure rates as they are used over time; a case closer to reality. This paper aims to evaluate the availability of different tools used in a production system, in which the reliability of a tool is dependent on the failure occurring to any other compatible tool. Two multi-objective genetic algorithms along with the \(\varepsilon \)-constraint method are proposed to solve the problem. The Taguchi method is also employed to calibrate the parameters of the proposed algorithms and to enhance their performances. Finally, a hybrid AHP-TOPSIS is utilized to prioritize the solution algorithms. The results indicate that while the \(\varepsilon \)-constraint is the best to solve small-size problems, the non-dominated rank genetic algorithm performs the best in solving large-size problems.
Similar content being viewed by others
References
Ayres, R.: (1) Future trends in factory automation, (2) Technology forecasts for CIM. Manuf. Rev. 1, 2 (1989)
Jain, A.S.; Meeran, S.: Deterministic job-shop scheduling: past, present and future. Eur. J. Oper. Res. 113, 390–434 (1999)
Palei, S.: Optimization of choosing the rule for changing a cutting tool in exploitation of the flexible manufacturing module. Stanki Instrum. 11, 27–30 (1988)
Al-Fawzan, M.; Al-Sultan, K.: A tabu search based algorithm for minimizing the number of tool switches on a flexible machine. Comput. Ind. Eng. 44, 35–47 (2003)
Groover, T.A.: Impedance Cardiography: Techniques Applicable to Extrapolation. University of Texas at Austin, Austin (1981)
Jeang, A.: Reliable tool replacement policy for quality and cost. Eur. J. Oper. Res. 108, 334–344 (1998)
Jeang, A.: Tool replacement policy for probabilistic tool life and random wear process. Qual. Reliab. Eng. Int. 15, 205–212 (1999)
Buyurgan, N.; Saygin, C.; Kilic, S.E.: Tool allocation in flexible manufacturing systems with tool alternatives. Robot. Comput. Integr. Manuf. 20, 341–349 (2004)
Sun, J.-W.; Xi, L.-F.; Du, S.-C.; Ju, B.: Reliability modeling and analysis of serial-parallel hybrid multi-operational manufacturing system considering dimensional quality, tool degradation and system configuration. Int. J. Prod. Econ. 114, 149–164 (2008)
Mahdavi, I.; Jazayeri, A.; Jahromi, M.; Jafari, R.; Iranmanesh, H.: P-ACO approach to assignment problem in FMSs. World Acad. Sci. Eng. Technol. 42, 196–203 (2008)
Hsu, B.-M.; Shu, M.-H.: Reliability assessment and replacement for machine tools under wear deterioration. Int. J. Adv. Manuf. Technol. 48, 355–365 (2010)
Rodriguez, C.E.P.; De Souza, G.F.M.: Reliability concepts applied to cutting tool change time. Reliab. Eng. Syst. Saf. 95, 866–873 (2010)
Vagnorius, Z.; Rausand, M.; Sørby, K.: Determining optimal replacement time for metal cutting tools. Eur. J. Oper. Res. 206, 407–416 (2010)
Chen, B.; Chen, X.; Li, B.; He, Z.; Cao, H.; Cai, G.: Reliability estimation for cutting tools based on logistic regression model using vibration signals. Mech. Syst. Signal Process. 25, 2526–2537 (2011)
Salonitis, K.; Kolios, A.: Reliability assessment of cutting tools life based on advanced approximation methods. Procedia CIRP 8, 397–402 (2013)
Salonitis, K.; Kolios, A.: Reliability assessment of cutting tool life based on surrogate approximation methods. Int. J. Adv. Manuf. Technol. 71, 1197–1208 (2014)
Sgarbossa, F.; Persona, A.; Pham, H.: Using systemability function for periodic replacement policy in real environments. Qual. Reliab. Eng. Int. 31, 617–633 (2015)
Liu, S.; Hu, Y.; Liu, C.; Zhang, H.: Real-time reliability self-assessment in milling tools operation. Qual. Reliab. Eng. Int. 32, 2245–2252 (2016)
Lugtigheid, D.; Jardine, A.K.; Jiang, X.: Optimizing the performance of a repairable system under a maintenance and repair contract. Qual. Reliab. Eng. Int. 23, 943–960 (2007)
Asadzadeh, S.; Aghaie, A.: Improving the product reliability in multistage manufacturing and service operations. Qual. Reliab. Eng. Int. 28, 397–407 (2012)
Bennane, A.; Yacout, S.: LAD-CBM; new data processing tool for diagnosis and prognosis in condition-based maintenance. J. Intell. Manuf. 23, 265–275 (2012)
Wu, Y.; Hong, G.; Wong, W.: Prognosis of the probability of failure in tool condition monitoring application—a time series based approach. Int. J. Adv. Manuf. Technol. 76, 513–521 (2015)
Aghdam, B.; Vahdati, M.; Sadeghi, M.: Vibration-based estimation of tool major flank wear in a turning process using ARMA models. Int. J. Adv. Manuf. Technol. 76, 1631–1642 (2015)
Letot, C.; Serra, R.; Dossevi, M.; Dehombreux, P.: Cutting tools reliability and residual life prediction from degradation indicators in turning process. Int. J. Adv. Manuf. Technol. 86, 495–506 (2016)
Garg, H.; Sharma, S.P.: Multi-objective reliability-redundancy allocation problem using particle swarm optimization. Comput. Ind. Eng. 64, 247–255 (2013)
Soltani, R.; Sadjadi, S.J.; Tofigh, A.A.: A model to enhance the reliability of the serial parallel systems with component mixing. Appl. Math. Model. 38, 1064–1076 (2014)
Garg, H.: An efficient biogeography based optimization algorithm for solving reliability optimization problems. Swarm Evol. Comput. 24, 1–10 (2015)
Miriha, M.; Niaki, S.T.A.; Karimi, B.; Zaretalab, A.: Bi-objective reliability optimization of switch-mode k-out-of-n series-parallel systems with active and cold standby components having failure rates dependent on the number of components. Arab. J. Sci. Eng. 42, 5305–5320 (2017)
Garg, H.; Rani, M.; Sharma, S.P.; Vishwakarma, Y.: Bi-objective optimization of the reliability-redundancy allocation problem for series-parallel system. J. Manuf. Syst. 33, 335–347 (2014)
Garg, H.: Reliability, availability and maintainability analysis of industrial systems using PSO and fuzzy methodology. Mapan 29, 115–129 (2014)
Garg, H.; Rani, M.; Sharma, S.P.; Vishwakarma, Y.: Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment. Expert Syst. Appl. 41, 3157–3167 (2014)
Garg, H.: An approach for analyzing the reliability of industrial system using fuzzy Kolmogorov’s differential equations. Arab. J. Sci. Eng. 40, 975–987 (2015)
Garg, H.: An approach for solving constrained reliability-redundancy allocation problems using Cuckoo search algorithm. Beni-Suef Univ. J. Basic Appl. Sci. 4, 14–25 (2015)
Rani, D.; Gulati, T.R.; Garg, H.: Multi-objective non-linear programming problem in intuitionistic fuzzy environment: optimistic and pessimistic view point. Expert Syst. Appl. 64, 228–238 (2016)
Garg, H.: A hybrid PSO-GA algorithm for constrained optimization problems. Appl. Math. Comput. 274, 292–305 (2016)
Garg, H.: Performance analysis of an industrial system using soft computing based hybridized technique. J Braz. Soc. Mech. Sci. Eng. 39, 1441–1451 (2017)
Kumar, K.; Garg, H.: Connection number of set pair analysis based TOPSIS method on intuitionistic fuzzy sets and their application to decision making. Appl. Intell. 1, 1–8 (2017)
Kumar, K.; Garg, H.: TOPSIS method based on the connection number of set pair analysis under interval-valued intuitionistic fuzzy set environment. Comput. Appl. Math. 1, 1–11 (2016). https://doi.org/10.1007/s40314-016-0402-0
Sharifi, M.; Memariani, A.; Noorossana, R.: Real time study of a k-out-of-n system: n identical elements with increasing failure rates. Iran. J. Oper. Res. 1, 56–67 (2009)
Chern, M.-S.: On the computational complexity of reliability redundancy allocation in a series system. Oper. Res. Lett. 11, 309–315 (1992)
Goldberg, D.E.; Holland, J.H.: Genetic algorithms and machine learning. Mach. Learn. 3, 95–99 (1988)
Deb, K.; Pratap, A.; Agarwal, S.; Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6, 182–197 (2002)
Jadaan, O.A.; Rajamani, L.; Rao, C.R.: Non-dominated ranked genetic algorithm for solving constrained multi-objective optimization problems. J. Theor. Appl. Inf. Technol. 5, 714–725 (2009)
Taguchi, G.: Introduction to Quality Engineering. Asian Productivity Organization, UNIPUB, White Plains, New York (1986)
Rahmati, S.H.A.; Hajipour, V.; Niaki, S.T.A.: A soft-computing Pareto-based meta-heuristic algorithm for a multi-objective multi-server facility location problem. Appl. Soft Comput. 13, 1728–1740 (2013)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Karimi, B., Niaki, S.T.A., Haleh, H. et al. Reliability optimization of tools with increasing failure rates in a flexible manufacturing system. Arab J Sci Eng 44, 2579–2596 (2019). https://doi.org/10.1007/s13369-018-3309-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13369-018-3309-9