Document Type : Original Article
Authors
1 Department of Industrial Engineering, Amirkabir University of Technology (Tehran Polytechnic), Garmsar Campus, Iran.
2 Department of Industrial Engineering and Management, Sadjad University of Technology, Mashhad, Iran.
Abstract
The nature of input materials is changed as long as the product reaches the consumer in many types of manufacturing processes. In designing and improving multi-stage systems, the study of the steps separately may not lead to the greatest possible improvement in the whole system, therefore the study of inputs and outputs of each stage can be effective in improving the output quality characteristics. In this study, the double sampling method is applied for inspection where decision variables are the sample size per sampling time and the maximum amount of defective items in the first and second samples in each stage. Furthermore, uncertainty in parameters such as production, inspection, and replacement costs are included in the objective function and handled by a Monte-Carlo based optimization method. In order to show the efficacies of the proposed method, a numerical example has been designed, and further analyses on solutions have been conducted.
Keywords
Azadeh, A., Sangari, M. S., and Amiri, A. S., (2012). "A Particle Swarm Algorithm for Inspection Optimization in Serial Multi-Stage Processes", Applied Mathematical Modelling, Vol. 36, pp. 1455-1464.
Azadeh, A., and Shamekhi Amiri, A., (2012). "A Particle Swarm Algorithm for Inspection Optimization in Serial Multi-Stage Processes", Applied Mathematical Modelling, Vol. 36, pp. 1455-1464.
Colledani, M., and Tolio, T., (2012). "Integrated Quality, Production Logistics and Maintenance Analysis of Multi-Stage Asynchronous Manufacturing Systems with Degrading Machines", Cirp Annals - Manufacturing Technology, Vol. 61, pp. 4.
Colledani, M., Tolio, T., Fischer, A., Iung, B., Lanza, G., Schmitt, R., and Váncza, J., (2014). "Design and Management of Manufacturing Systems for Production Quality", Cirp Annals, Vol. 63, pp. 773-796.
Díaz-García, J. A. and Bashiri, M., (2014). "Multiple Response Optimisation: An Approach from Multi-Objective Stochastic Programming", Applied Mathematical Modelling, Vol. 38, pp. 2015-2027.
Díaz-García, J. A., Ramos-Quiroga, R., and Cabrera-Vicencio, E., (2005). "Stochastic Programming Methods in the Response Surface Methodology", Computational Statistics and Data Analysis, Vol. 49, pp. 837-848.
Engin, O., Çelik, A., and Kaya, İ., (2008). "A Fuzzy Approach to Define Sample Size for Attributes Control Chart in Multistage Processes: An Application in Engine Valve Manufacturing Process", Applied Soft Computing, Vol. 8, pp. 1654-1663.
Gao, Y., Yang, L., and Li, S., (2016). "Uncertain Models on Railway Transportation Planning Problem", Applied Mathematical Modelling, Vol. 40, pp. 4921-4934.
Hawkins, D. M., (1991). "Multivariate Quality Control Based On Regression-Adjusted Variables", Technometrics, Vol. 33, pp. 61-75.
Hejazi, T. H., Bashiri, M., Díaz-García, J. A., and Noghondarian, K., (2012). "Optimization of Probabilistic Multiple Response Surfaces", Applied Mathematical Modelling, Vol. 36, pp. 1275-1285.
Hejazi, T. H., Seyyed-Esfahani, M. and Badri, H., (2014). "Two-Stage Stochastic Programming Based on the Desirability Function to Optimize the Performance of an Internal-Combustion Engine", Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol.228, pp. 104-114.
Hejazi, T. H., Seyyed-Esfahani, M., and Mahootchi, M., (2013). "Quality Chain Design and Optimization by Multiple Response Surface Methodology", The International Journal of Advanced Manufacturing Technology, Vol. 68, pp. 881-893.
Hejazi, T. H., Seyyed-Esfahani, M., and Mahootchi, M., (2015). "Optimization of Degree of Conformance in Multiresponse-Multistage Systems with a Simulation-Based Metaheuristic", Quality and Reliability Engineering International, Vol. 31, pp. 645-658.
Heredia-Langner, A., Montgomery, D. C., and Carlyle, W. M., (2002). "Solving a Multistage Partial Inspection Problem Using Genetic Algorithms", International Journal Of Production Research, Vol. 40, pp. 1923-1940.
Hong, S., Wernz, C., and Stillinger, J. D., (2016). "Optimizing Maintenance Service Contracts Through Mechanism Design Theory", Applied Mathematical Modelling, Vol. 40, pp. 8849-8861.
Hubbard, D. W., (2014). How To Measure Anything: Finding The Value Of Intangibles In Business, John Wiley and Sons.
Kaya, (2009). "A Genetic Algorithm Approach to Determine the Sample Size for Attribute Control Chart", Information Sciences, Vol. 179, pp. 1552-1566.
Kaya, and Engin, (2007). "A New Approach To Define Sample Size Attributes Control Chart In Multistage Processes: An Application In Engine Piston Manufacturing Process", Journal of Materials Processing Technology, Vol. 183, pp. 38-48.
Kaya, İ. and Engin, O. 2007b. A New Approach To Define Sample Size At Attributes Control Chart In Multistage Processes: An Application In Engine Piston Manufacturing Process. Journal Of Materials Processing Technology, 183, 38-48.
Kim, H., and Kim, P., (2017). "Reliability–Redundancy Allocation Problem Considering Optimal Redundancy Strategy Using Parallel Genetic Algorithm", Reliability Engineering and System Safety, Vol. 159, pp. 153-160.
Kuo, R. J., and Han, Y. S., (2011). "A Hybrid of Genetic Algorithm and Particle Swarm Optimization for Solving Bi-Level Linear Programming Problem – A Case Study On Supply Chain Model", Applied Mathematical Modelling, Vol. 35, pp. 3905-3917.
Lin, C. D., Anderson-Cook, C. M., Hamada, M. S., Moore, L. M., and Sitter, R. R., (2015). "Using Genetic Algorithms to Design Experiments: A Review", Quality And Reliability Engineering International, Vol. 31, pp. 155-167.
Lindsay, and Bishop, (1964). "Allocation of Screening Inspection Effort-Adynamic-Programming Approach", Management Science, Vol. 10, pp. 342-352.
Liu, X., Zheng, S., Feng, J., and Chen, T., (2015). "Reliability Reallocation for Fuel Cell Vehicles Based On Genetic Algorithm", Quality and Reliability Engineering International, Vol. 31, pp. 1495-1502.
Montgomery, D. C., (2009). Statistical Quality Control, Wiley New York.
Moura, M. D. C., Lins, I. D., Droguett, E. L., Soares, R. F., and Pascual, R., (2015). "A Multi-Objective Genetic Algorithm for Determining Efficient Risk-Based Inspection Programs", Reliability Engineering and System Safety, Vol. 133, pp. 253-265.
Rau, H., Cho, K., and Wang, Y., (2011). "Optimal Inspection Allocation for Workstations of Attribute Data with Multi-Characteristics in Multi-Station Systems", Engineering Materials, Vol. 450, pp. 397-400.
Rau, H., Cho, K. H., and Wang, Y. H., (2011). "Optimal Inspection Allocation for Workstations of Attribute Data with Multi-Characteristics in Multi-Station Systems", Key Engineering Materials, Vol. 450, pp. 397-400.
Aghaie, A., Fatemi Ghomi, S. M. T., and Jabari, S., (2014). "Economic Design of Exponentially Weighted Moving Average Control Chart Based On Measurement Error Using Genetic Algorithm", Quality and Reliability Engineering International, Vol. 30, pp. 1153-1163.
Sarhangian, V., Vaghefi, A., Eskandari, H., and Ardakani, M. K., (2008). "Optimizing Inspection Strategies for Multi-Stage Manufacturing Processes Using Simulation Optimization", 2008 Winter Simulation Conference, 7-10 Dec. 2008, pp. 1974-1980.
Shi, J., Liu, Z., Tang, L., and Xiong, J., (2017). "Multi-Objective Optimization For A Closed-Loop Network Design Problem Using An Improved Genetic Algorithm", Applied Mathematical Modelling, Vol. 45, pp. 14-30.
Shi, J., and Zhou, S., (2009). "Quality Control and Improvement for Multistage Systems: A Survey", Iie Transactions (Institute Of Industrial Engineers), Vol. 41, pp. 744-753.
Soleimani, H. and Kannan, G., (2015). "A Hybrid Particle Swarm Optimization and Genetic Algorithm for Closed-Loop Supply Chain Network Design In Large-Scale Networks", Applied Mathematical Modelling, Vol. 39, pp. 3990-4012.
Van Volsem, S., Dullaert, W., and Van Landeghem, H., (2007). "An Evolutionary Algorithm And Discrete Event Simulation For Optimizing Inspection Strategies For Multi-Stage Processes", European Journal of Operational Research, Vol. 179, pp. 621-633.
Wang, K., and Chenxu, D., (2014). "A Mixed-Effect Model for Analyzing Experiments with Multistage Processes", Quality Technology and Quantitative Management, Vol.11, pp. 491-511.
Williams, W. W., and Peters, M. H., (1989). "Economic Design of an Attributes Control System for a Multistage Serial Production Process", International Journal of Production Research, Vol. 27, pp. 1269-1286.
Xiang, L., and Tsung, F., (2008). "Statistical Monitoring Of Multi-Stage Processes Based On Engineering Models", Iie Transactions (Institute Of Industrial Engineers), Vol. 40, pp. 957-970.
Yum, B. J., and Mcdowellj, E. D., (2007). "Optimal Inspection Policies in A Serial Production System Including Scrap Rework And Repair: An MILP Approach", International Journal of Production Research, Vol. 25, pp. 1451-1464.
Zantek, P. F., Wright, G. P., and Plante, R. D., (2002). "Process and Product Improvement in Manufacturing Systems with Correlated Stages", Management Science, Vol. 48, pp. 591-606.
Zhang, X., Huang, S., and Wan, Z., (2016). "Optimal Pricing and Ordering In Global Supply Chain Management With Constraints Under Random Demand", Applied Mathematical Modelling, Vol. 40, pp. 10105-10130.
Zhou, S., Huang, Q., and Shi, J., (2003). "State Space Modeling Of Dimensional Variation Propagation in Multistage Machining Process Using Differential Motion Vectors", IEEE Transactions On Robotics And Automation, Vol. 19, pp. 296-309.
Zhu, H., Zhang, C., and Deng, Y., (2016). "Optimisation Design of Attribute Control Charts For Multi-Station Manufacturing System Subjected To Quality Shifts", International Journal of Production Research, Vol. 54, pp. 1804-1821.
)