Inspection Allocation Optimization with Resource Constraints Based on Modified NSGA-II in Flexible Manufacturing Systems

With the development of smart manufacturing, quality has become an indispensable issue in the manufacturing process. Although there is increasing publication about inspection allocation problems, inspection allocation optimization research considering resource capability is scarce. This paper focuses on the inspection allocation problem with resource constraints in the flexible manufacturing system. Combined with the inspection resource capability model, a bi-objective model is developed to minimize the cost and balance loads of the inspection station. A modified NSGA-II algorithm with adaptive mutation operators is suggested to deal with the proposed model. Finally, a simulation experiment is conducted to test the performance of the modified algorithm and the results demonstrate that modified NSGA-II can obtain acceptable inspection solutions.

[1]  Sofie Van Volsem,et al.  Joint optimisation of all inspection parameters for multistage processes: evolutionary algorithm and simulation , 2010 .

[2]  S. Unnikrishnan,et al.  Planning quality inspection operations in multistage manufacturing systems with inspection errors , 1998 .

[3]  Hsin Rau,et al.  Genetic algorithm modeling for the inspection allocation in reentrant production systems , 2009, Expert Syst. Appl..

[4]  Amir Hossein Alavi,et al.  An improved NSGA-III algorithm with adaptive mutation operator for Big Data optimization problems , 2018, Future Gener. Comput. Syst..

[5]  Yau-Ren Shiau.  Quick decision-making support for inspection allocation planning with rapidly changing customer requirements , 2003 .

[6]  Junyu Dong,et al.  Enhancing MOEA/D with information feedback models for large-scale many-objective optimization , 2020, Inf. Sci..

[7]  Wu Deng,et al.  Differential evolution algorithm with wavelet basis function and optimal mutation strategy for complex optimization problem , 2020, Appl. Soft Comput..

[8]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[9]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[10]  Przemyslaw Korytkowski,et al.  Genetic algorithm for optimization of inspection stations allocation in multi-product manufacturing systems , 2009, 2009 International Conference on Computers & Industrial Engineering.

[11]  Przemyslaw Korytkowski,et al.  A genetic algorithm with tournament selection for optimising inspection allocation in multiproduct multistage production systems , 2011, Int. J. Simul. Process. Model..

[12]  Yau-Ren Shiau.  Inspection resource assignment in a multistage manufacturing system with an inspection error model , 2002 .

[13]  Hendrik Van Landeghem,et al.  An Evolutionary Algorithm and discrete event simulation for optimizing inspection strategies for multi-stage processes , 2007, Eur. J. Oper. Res..

[14]  Fernando Romero,et al.  An ontology for integrated machining and inspection process planning focusing on resource capabilities , 2016, Int. J. Comput. Integr. Manuf..

[15]  Yau-Ren Shiau,et al.  Concurrent process/inspection planning for a customized manufacturing system based on genetic algorithm , 2007 .

[16]  Reza Tavakkoli-Moghaddam,et al.  A bi-objective robust inspection planning model in a multi-stage serial production system , 2018, Int. J. Prod. Res..

[17]  Horst Tempelmeier,et al.  Solving a multi-level capacitated lot sizing problem with multi-period setup carry-over via a fix-and-optimize heuristic , 2009, Comput. Oper. Res..

[18]  Reza Tavakkoli-Moghaddam,et al.  Mathematical modelling of a robust inspection process plan: Taguchi and Monte Carlo methods , 2015 .

[19]  Qingfu Zhang,et al.  MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.

[20]  Giacomo Maria Galante,et al.  Integrated approach to part scheduling and inspection policies for a job shop manufacturing system , 2007 .

[21]  E. Gerald Hurst,et al.  Imperfect Inspection in a Multistage Production Process , 1973 .

[22]  Libor Preucil,et al.  Inspection planning in the polygonal domain by Self-Organizing Map , 2011, Appl. Soft Comput..

[23]  Huimin Zhao,et al.  An Enhanced MSIQDE Algorithm With Novel Multiple Strategies for Global Optimization Problems , 2022, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[24]  Suash Deb,et al.  Monarch butterfly optimization: A comprehensive review , 2021, Expert Syst. Appl..

[25]  SahlingFlorian,et al.  Solving a multi-level capacitated lot sizing problem with multi-period setup carry-over via a fix-and-optimize heuristic , 2009 .

[26]  Nicola Beume,et al.  SMS-EMOA: Multiobjective selection based on dominated hypervolume , 2007, Eur. J. Oper. Res..

[27]  Lishan Kang,et al.  A New Evolutionary Algorithm for Solving Many-Objective Optimization Problems , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[28]  Yadati Narahari,et al.  Modeling reentrant manufacturing systems with inspection stations , 1996 .

[29]  D.A. Van Veldhuizen,et al.  On measuring multiobjective evolutionary algorithm performance , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[30]  Farouk Yalaoui,et al.  A NSGA-II and NSGA-III comparison for solving an open shop scheduling problem with resource constraints , 2016 .

[31]  Yau-Ren Shiau.  Inspection Allocation Planning for a Multiple Quality Characteristic Advanced Manufacturing System , 2003 .

[32]  J. Rene Villalobos,et al.  Information-based Inspection allocation for real-time Inspection systems , 2001 .

[33]  Glenn F. Lindsay,et al.  Allocation of Screening Inspection Effort---A Dynamic-Programming Approach , 1964 .