نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، دانشگاه بجنورد.
2 کارشناس، دانشگاه صنعتی نوشیروانی بابل.
3 دانشیار، دانشگاه تهران.
چکیده
با توجه به اثر عوامل تصادفی مانند خرابی ماشین‌ها بر قدرت رقابتی سازمان‌های تولیدی، اهمیت برنامه‌ریزی تولید دوچندان شده است. لذا سیستم‌های تولیدی مستعد شکست برای مقابله با این عدم قطعیت، پدید آمده‌اند. جهت حفظ سهم در بازار رقابت و افزایش بهره‌وری، سیستم‌های صنعتی به اسـتراتژی نگهداری و تعمیرات به‌منظور کاهش نرخ خرابی و افزایش قابلیت اطمینان روی آورده‌اند. به‌منظور افزایش ظرفیت تولید، فراهمآوردن انعطاف‌پذیری بیشتر و اطمینان از رضایت‌مندی مشتری از نظر کمیّت، کیفیت و زمان‌بندی، استفاده از پیمانکاری فرعی با رویکرد اشتراک درآمدها، گزینه‌ای مناسب در این پژوهش است. این پژوهش، سیستمی متشکل از شبکه‌ای از ماشین‌آلات با محدودیت رابطه و زمان خرابی و تعمیر تصادفی می باشد. به‌منظور جلوگیری از کمبود از بافرهای میانی و یک بافر نهایی استفاده می‌شود. پارامتر مؤثر دیگر تعیین دفعات بهینه نگهداری پیشگیرانه است که منتج به حداقل رساندن هزینه نگهداری و تعمیرات پیشگیرانه و اصلاحی می‌شود. هدف تعیین نرخ بهینه تولید و متغیر‌های نگهداری پیشگیرانه و متغیر‌های مربوط به پیمانکاران فرعی است. برای این منظور از شبیه‌سازی گسسته ـ پیشامد استفاده می‌شود. بعد از مدل‌سازی در نرم‌افزار ارنا بهترین مقادیر متغیر‌های تصمیم در بستر Opt Quest بهدست می‌آید که به کاهش 5/22 درصدی هزینه‌های کل سیستم منجر می‌شود.
کلیدواژه‌ها
- شبیه‌سازی
- سیستم‌های تولیدی مستعد شکست
- نگهداری و تعمیرات پیشگیرانه
- نرخ تولید
- قابلیت اطمینان
- قرارداد اشتراک درآمدها
موضوعات
عنوان مقاله [English]
A Simulation – Optimization Model of Network Failure Prone Manufacturing Systems with a Reliability-Based Maintenance and Revenue Sharing Approach
نویسندگان [English]
- Mehdi Deiranlou 1
- Farnaz Azadjou 2
- Seyed Mojtaba Sajadi 3
1 Assistant Professor, University of Bojnord.
2 BSc, Babol Noshirvani University of Technology.
3 Associate Professor, University of Tehran.
چکیده [English]
Due to the effect of random factors such as machine failure on the competitiveness of production organizations and the importance of production planning, failure-prone manufacturing systems have emerged to deal with uncertainty. In order to maintain a competitive market share and increase productivity and safety, industrial systems have resorted to a maintenance strategy to reduce failure rates and increased reliability. Increasing production capacity, providing more flexibility and ensuring customer satisfaction in terms of quantity, quality and timing have made the use of subcontracting with a revenue sharing approach a viable option in this study. In this research, a network of machines with relationship limitation and failure and accidental repair is considered. To prevent shortages, intermediate buffers and a final buffer are used. Another important parameter is determining the optimal frequency of preventive maintenance, which results in minimizing the cost of preventive and corrective maintenance and repairs. The goal is to determine the optimal production rate and preventive maintenance variables and subcontractor variables. Discrete-event-simulation is used for this purpose. After modeling in Arena, the best values of decision variables are obtained in the opt-quest platform, which leads to a 22.5% reduction in total system costs.
کلیدواژه‌ها [English]
- Simulation of Failure-Prone Production Systems
- Preventive Maintenance؛ Production Rate؛ Reliability؛ Revenue Sharing Contract
- Afshar-Bakeshloo, M., Bozorgi-Amiri, A., Sajadi, S. M., & Jolai, F. (2018). A multi-objective Environmental Hedging Point Policy with customer satisfaction criteria. Journal of Cleaner Production, 179, 478-494.
- Aiassi, R., Sajadi, S. M., Hadji-Molana, S. M., & Zamani-Babgohari, A. (2020). Designing a stochastic multi-objective simulation-based optimization model for sales and operations planning in built-to-order environment with uncertain distant outsourcing. Simulation Modelling Practice and Theory, 104, 102103.
- Amelian, S., Sajadi, S. M., & Alinaghian, M. (2015). Optimal production and preventive maintenance rate in a failure-prone manufacturing system using discrete event simulation. International Journal of Industrial and Systems Engineering, 20(4), 483-496.
- Seyed Bathaee, M. S., Ghahremani-Nahr, J., Nozari, H., & Najafi, S. E. (2022). Designing a Mathematical Model of a Collaborative Production System Based on Make to Order under Uncertainty. Journal of Industrial Management Perspective, 12(Issue 1, Spring 2022), 193-224. doi: 10.52547/jimp.12.1.193 (In persian)
- Dror, Moshe, Kenneth R. Smith, and Candace Arai Yano. Deux Chemicals Inc. Goes Just-in-Time. Interfaces 39.6 (2009): 503-515.
- Glock, C.H., 20136- Berg, M., Posner, M.J.M., Zhao, H. (1994). Production-inventory systems with unreliable machines. Res. 42(1), 111–118.
- Hafidi, N., El Barkany, A., & Mahmoudi, M. (2018). Modelling and Optimization of Integrated Planning of Production and Maintenance with Subcontract Constraint. International Journal of Engineering Research in Africa 40, 184–203.
- Hajej, Zied, Nidhal Rezg, & Ali Gharbi. (2014). Forecasting and maintenance problem under subcontracting constraint with transportation delay." International Journal of Production Research, 52(22), 6695-6716.
- Haoues, M., Dahane, M., & Mouss, N. K. (2019). Optimization of Single Outsourcer–Single Subcontractor Outsourcing Relationship under Reliability and Maintenance Constraints. Journal of Industrial Engineering International.
- Hatami-Marbini, A., Sajadi, S. M., & Malekpour, H. (2020). Optimal control and simulation for production planning of network failure-prone manufacturing systems with perishable goods. Computers & Industrial Engineering, 146,
- Kenné, J. P., Gharbi, A., & Boukas, E. K. (1997). Control policy simulation based on machine age in a failure prone one-machine, one-product manufacturing system. International Journal of Production Research, 35(5), 1431-1445.
- Keynia F. (2017). Preventive and Corrective Maintenance to the Lifetime Efficiency of Power Transformer Considering the Effect of Aging on Reliability. Journal of Engineering & Mnagement., 7(3), 20-31 (In persian)
- Khairy, A. H. K. (2008). Complex System Maintenance Handbook. Springer Science & Business Media.
- Khatab, A. (2018). Maintenance optimization in failure-prone systems under imperfect preventive maintenance. Journal of Intelligent Manufacturing, 29(3), 707-717.
- Malekpour, H., Sajadi, S. M., & Vahdani, H. (2016). Using discrete-event simulation and the Taguchi method for optimising the production rate of network failure-prone manufacturing systems with perishable goods. International Journal of Services and Operations Management, 23(4), 387-406.
- Peymankar, M., Dehghanian, F., Ghiami, Y., & Abolbashari, M. H. (2018). The effects of contractual agreements on the economic production quantity model with machine breakdown. International Journal of Production Economics, 201, 203-215.
- Rad, M. F., Sajadi, S. M., & Kashan, A. H. (2015). Determination of optimal production rate in stochastic manufacturing systems by simulation optimisation approach. International Journal of Industrial and Systems Engineering, 20(3), 306-322.
- Rivera-Gómez, H., Gharbi, A., Kenné, J. P., Montaño-Arango, O., & Hernandez-Gress., E. S. (2018). Subcontracting Strategies with Production and Maintenance Policies for a Manufacturing System Subject to Progressive Deterioration. International Journal of Production Economics, 200, 103–118.
- Rivera-Gómez, Héctor, et al. (2016). Production control problem integrating overhaul and subcontracting strategies for a quality deteriorating manufacturing system. International Journal of Production Economics, 171, 134-150.
- Sadat khansari, E., Haji Molana, M., Sajadi, M., (2017). Designing an integrated fuzzy simulation model to optimize preventive maintenance and repairs of multi-product manufacturing businesses. 14th International Industrial Engineering Conference, IIEC14_338 (In persian)
- Taheri, S., Mokhtari, H., Fallahi, A. (2021). An Economic Production Quantity Model with Probabilistic Machine Breakdown and Multiple Shipments Policy. The Journal of Industrial Management Perspective, 11(4), 223-252. (In persian)
- Tavan, F., & Sajadi, S. M. (2015). Determination of optimum of production rate of network failure prone manufacturing systems with perishable items using discrete event simulation and Taguchi design of experiment. Journal of Industrial Engineering and Management Studies, 2(1), 16-26.
- Mousavi, S., Sajadi, S., AlemTabriz, A., Najafi, S. (2021). Designing a Hierarchical Network of Temporary Urban Medical Centers in a Disaster through a Hybrid Approach of Mathematical Model – Simulation. The Journal of Industrial Management Perspective, 11(2), 99-124. (In persian)
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