Joint Optimization of Spare Parts Strategy and Maintenance Policies for Manufacturing Systems
محورهای موضوعی : optimization and simulationmohammadali farsi 1 , Enrico Zio 2
1 - Aerospace Research Institute, Ministry of Science, Research and Technology, Iran, Tehran
2 - Energy Engineering Department, Politecnico di Milano, Italy
کلید واژه: Storage condition, Multi-Component Manufacturing System, Spare Part Strategy, Supply Chain, Joint Optimization, Multi-Policy Maintenance,
چکیده مقاله :
Cost is the most important factor in engineering systems, thus cost reduction and producing components with a reasonable cost are mandatory for manufacturing engineers. Effective maintenance influences the total cost of manufacturing systems, and its efficiency depends on spare parts management. Therefore, maintenance and spare parts should be jointly managed and significant characters such as ordering, repair and replacement times, shortage, cost, quality, and storage condition of spare parts have to be considered. In this paper, intelligent manufacturing systems with the multi-component structure are considered, that three types of maintenance policies (condition-based maintenance, corrective maintenance, and preventive maintenance) simultaneously support these systems. A joint optimization method based on GA-PS and Monte Carlo simulation is proposed to achieve minimum cost and maximum availability. Also, the influence of spare parts degradation in storage to evaluate system performance is considered. A framework is proposed for this; it can successfully consider the manufacturing machines, maintenance policies and spare parts inventory to obtain the optimal system with the maximum availability and the minimum cost. Also, the results demonstrate that different factors impress the system, and these parameters must be jointly considered. The ordering and replacement times, storing conditions and suppliers' situation are the main factors considered to obtain an optimal system.
[1] Moghaddam, M. J., Farsi, M. A. and Anoushe, M. Development of a New Method to Automatic Nesting and Piloting System Design for Progressive Die, Int J Adv Manufacturing Technology, Vol. 77, 2015, pp. 1557-1569, DOI:10.1007/s00170-014-6542-8.
[2] Vahebi, M., Arezoo, B., Accuracy Improvement of Volumetric Error Modeling in CNC Machine Tools, Int J Adv Manufacturing Technology, Vol. 95, 2018, pp. 2243-2257, DOI:10.1007/s00170-017-1294-x.
[3] Aramon Bajestani, M., Integrating Maintenance Planning and Production Scheduling: Making Operational Decisions with a Strategic Perspective, Ph.D. Thesis, University of Toronto, 2014.
[4] Sherbrooke, C. C., Metric., A Multi-Echelon Technique for Recoverable Item Control. Operation Res. 1968, DOI:10.1287/opre.16.1.122.
[5] Armstrong, M., Atkins, D., Joint Optimization of Maintenance and Inventory Policies for A Simple System, IIE TRANSACTIONS, 1996, pp. 415-424.
[6] Chelbi, A., Aït-Kadi, D., Spare Provisioning Strategy for Preventively Replaced Systems Subjected to Random Failures, Int J Prod Econ., Vol. 74, 2001, pp. 183–189.
[7] Brezavšček, A., Hudoklin, A., Joint Optimization of Block-Replacement and Periodic-Review Spare-Provisioning Policy. Reliability, IEEE Transactions on, Vol. 52, 2003, pp. 112-117. DOI: 10.1109/TR.2002.805790.
[8] Chen, X., Xiao, L., Zhang, X., Xiao, W., and Li, J., An Integrated Model of Production Scheduling and Maintenance Planning Under Imperfect Preventive Maintenance, Eksploatacja I Niezawodnosc - Maintenance and Reliability, Vol. 17, 2015, pp. 70-79. 10.17531/ein.2015.1.10.
[9] Rausch, M., Joint Production and Spare Part Inventory Control Strategy Driven by Condition Based Maintenance, IEEE Transactions on Reliability, Vol. 59, No. 3, 2010, pp. 507 - 516. 2010.
[10] Elwany, A. H., Gebraeel, N. Z., Sensor-Driven Prognostic Models for Equipment Replacement and Spare Parts Inventory, IIE Transactions, Vol. 40, No. 7, pp. 629-639.
[11] Wang, Y., Gu, H., Zhao, J. Hongqiang Gu, and Zhonghua C., Modeling on Spare Parts Inventory Control Under Condition Based Maintenance Strategy, J. Shanghai Jiaotong Univ. Sci., Vol. 21, 2016, pp. 600-604, DOI:10.1007/s12204-016-1769-1.
[12] Chen, X., Xu, D., and Xiao, L., Joint Optimization of Replacement and Spare Ordering for Critical Rotary Component Based On Condition Signal to Date. Eksploatacja I Niezawodnosc - Maintenance and Reliability, Vol. 19, 2016, pp. 76-85, DOI:10.17531/ein.2017.1.11.
[13] Nguyen, K. A., Phuc, D., Antoine Grall, Joint Predictive Maintenance and Inventory Strategy for Multi-Component Systems Using Birnbaum’s Structural Importance, Reliability Engineering and System Safety, Vol. 168, 2017, pp. 249–261.
[14] Zahedi-Hosseini, F., Scarf, P., and Syntetos, A., Joint Maintenance-Inventory Optimization of Parallel Production Systems, Journal of Manufacturing Systems, Vol. 48, 2018, pp. 73–86.
[15] Sharma, P., Makarand, S. K., and Vikas, Y., A Simulation-Based Optimization Approach for Spare Parts Forecasting and Selective Maintenance, Reliability Engineering & System Safety, Vol. December, 2017, pp. 274-289.
[16] Kalinowska, N., Pawłowska, A., and Stachowiak., Factors Influencing Spare Parts Management in The Automotive Industry, 24th Inter, Conference on Production Research (ICPR 7102), 2017.
[17] Siddique, P. J., Huynh, T. L., and Shafiq, M., An Optimal Joint Maintenance and Spare Parts Inventory Model, Int. J. Industrial and Systems Engineering, Vol. 29, No. 2, 2018, pp. 177-185.
[18] Israel Eduardo, F., Albrecht, A., Enzo M., Frazzon, M., and Bernd, H., Operation Supply Chain Planning for Integrating Spare Parts Supply Chain and Intelligent Maintenance System, IFAC Papers On-Line, Vol. 50, No. 1, 2017, pp. 12428–12433.
[19] Bernd, H., Cordes, A. K., Approach for Integrating Condition Monitoring Information and Forecasting Methods to Enhance Spare Parts Supply Chain Planning, 11th IFAC Workshop on Intelligent Manufacturing Systems, The International Federation of Automatic Control, May 22-24, São Paulo, Brazil, 2013.
[20] Azadeh, A., Asadzadeh, S. M., Salehi, N., and Firoozi, M., Condition-Based Maintenance Effectiveness for Series-Parallel Power Generation System-A Combined Markovian Simulation Model, Reliability Engineering and System Safety, Vol. 142, 2015, pp. 357–368.
[21] Frank Joshua, D. De., Ph.D. Thesis, A Condition Based Maintenance Approach to Forecasting B-1 Aircraft Parts. Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio, 2017.
[22] Moubray, J., Reliability-Centered Maintenance (2nd ed.), New York: Industrial press, 1997.
[23] Goode, K. B., Moore, J., and Roylance, B. J., Plant Machinery Working Life Prediction Method Utilizing Reliability and Condition-Monitoring Data. Institution of Mechanical Engineers, Vol. 214, Part E, 2000, pp. 109–122.
[24] Farsi, M. A., Principles of Reliability Engineering, Symaye Danesh, Tehran, 2016.
[25] Loganathan, M. K., Gandhi, O. P., Maintenance Cost Minimization of Manufacturing Systems Using PSO Under Reliability Constraint, Int J System Assur Eng Manag. Vol. 7, 2016, pp. 47-61. DOI: 10.1007/s13198-015-0374-2.