بهینه سازی هزینه های زنجیره تأمین با در نظر گرفتن کیفیت و طول زمان سفارش
محورهای موضوعی :
مدیریت صنعتی
Salahuddin Ghasimi
1
,
puria Fakhri
2
,
Jahedeh Tekiyekhah
3
1 - Assistant Professor, Department of Industrial Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran
2 - M.S in Industrial Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran
3 - Assistant Professor, Academic Center for Education, Culture, and Research (ACECR)
تاریخ دریافت : 1401/05/24
تاریخ پذیرش : 1401/11/16
تاریخ انتشار : 1401/12/01
کلید واژه:
مدلسازی ریاضی,
گارانتی,
کیفیت,
طول زمان سفارش,
زنجیره تأمین,
چکیده مقاله :
چکیدهدر عصر کنونی با توجه به رقابتی بودن بازار، نگرانی تولید کننده ها تسخیر بیشتر سهم بازار می باشد، برای این کار رضایت مندی مشتریان در اولویت قرار دارند. با بررسی مطالعات پیشین فاکتورهای کیفیت، هزینه و زمان تحویل نقش اساسی در رضایت مندی مشتریان را بازی می کنند. بنابراین برای تحقق این هدف ارائه مدل ریاضی جهت بهینه کردن هزینه‌های زنجیره تأمین با در نظر گرفتن کیفیت و زمان سفارش می تواند بسیار مفید باشد. دراین تحقیق یک مدل ریاضی جامع ارائه شده است که هزینه های مربوط به شبکه زنجیره تامین از جمله: هزینه های تولید، حمل ونقل، گارانتی، دوباره کاری محصولات معیوب، نگهداری مواد اولیه و محصولات، قراضه آلات، و همچنین هزینه های ناشی از افزایش طول زمان سفارش و هزینه های کیفیت را کمینه می کند. برای حل مدل پیشنهادی از نرم افزار بهینه ساز گمز استفاده گردید. نتایج نشان داد که با افزایش کیفیت هزینه های کل و همچنین طول زمان سفارش کاهش یافت. همچنین بمنظور اعتبار سنجی، مدل پیشنهادی در شرکت کابل باختر برای محصول ACSR MINK در 5 دوره پیاده سازی گردید. نتایج بدست آمده از پیاده سازی این مدل در شرکت مذکور نشان داد که با بکارگیری این مدل هزینه های شرکت به اندازه 6.7% کاهش یافت.
چکیده انگلیسی:
In today's era, due to the competitive of the market, the concern of producers is to capture more of the market share, for this, customer satisfaction is a priority. By examining previous studies, quality, cost, and delivery time factors play an important role in customer satisfaction. Therefore, in order to achieve this goal, it can be very useful to provide a mathematical model to optimize the costs of the supply chain, taking into account the quality and time of the order. In this research, a comprehensive mathematical model has been presented, which includes costs related to the supply chain network, including: production costs, transportation, warranty, rework of defective products, storage of raw materials and products, scrap, as well as costs caused by the increase It minimizes the order time and quality costs. Games optimizer software was used to solve the proposed model. The results showed that with the increase in quality, the total costs and also the length of the order decreased. Also, for the purpose of validation, the proposed model was implemented in Bakhtar Cable Company for ACSR MINK product in 5 periods. The results obtained from the implementation of this model in the mentioned company showed that by using this model, the company's costs were reduced by 6.7%.
منابع و مأخذ:
Ahmadi, K., R. (2008). A total quality model for the supply chain of the automotive industry. (Case study: Iran Khodro Company). [Doctoral dissertation, Tarbiat Modares University, Tehran].
Akkerman, R., Farahani, P., & Grunow, M. (2010). Quality, safety and sustainability in food distribution: a review of quantitative operations management approaches and challenges. OR spectrum, 32, 863-904.
Bandyopadhyay, J. K., & Sprague, D. A. (2003). Total quality management in an automotive supply chain in the United States. International Journal of Management, 20(1), 17.
Doosti A., & Moghaddam S. R., (2022) Presenting a Multi-Objective Mathematical Model of Multi-Product and MultiStage Fuzzy Production Planning For Several Periods in Gamz Software. Journal of Strategic Management in Industrial System, 17(59), 99-112.
Ghasimi, A., S., Ramli, R., & Saibani, N., (2013) A genetic algorithm for optimizing defective goods supply chain,costs using JIT logistics and each-cycle lengths. Journal of Applied Mathematical Modelling, 38 (2014), 1534–1547.
Gunasekaran, A., & McGaughey, R. E. (2003). TQM is suppy chain management. The TQM magazine, 15(6), 361-363.
Hasni, A., A. (2010). Designing a stable reverse/forward supply chain for perishable goods. [Master Thesis in Industrial Engineering, Tarbiat Modares University, Tehran].
Bajani, S. E., Saberi, S., & Toyasaki, F. (2022). Reverse Supply Chain Network with Return Products Quality Consideration. IFAC-PapersOnLine, 55(10), 2926-2931.
Jaafarnejad, A. (2012). Modern production and operations management, 2nd ed, Faculty of Management, University of Tehran.
Juran, J. M., Godfrey, A. B., Hoogstoel, R. E., & Schilling, E. G. (1999). Juran’s quality handbook 5th ed.
Karthick, B., & Uthayakumar, R. (2022). Impact of carbon emission reduction on supply chain model with manufacturing decisions and dynamic lead time under uncertain demand. Cleaner Logistics and Supply Chain, 4, 100037.
Kazemi, , M., & Taki, P., (2016). Simulation of transportation cost for supply chain network design by considering the demand related to price and quality. Journal of quality engineering and management, 6(1), 57-65.
Li, S., Rao, S. S., Ragu-Nathan, T. S., & Ragu-Nathan, B. (2005). Development and validation of a measurement instrument for studying supply chain management practices. Journal of operations management, 23(6), 618-641.
Nazemi, , Usefinejad, M., & Ghafari, M., (2017). solving a three-level supply chain model with the aim of increasing quality and reducing possible delivery time. Journal of engineering management and soft computing, 3(1), 31-63.
Robinson, C. J., & Malhotra, M. K. (2005). Defining the concept of supply chain quality management and its relevance to academic and industrial practice. International journal of production economics, 96(3), 315-337.
Tabrizi, S., Ahmadi, A., & Karimi, A. (2012). Modeling the supply chain of warm-water farmed fish in Iran with an integrated logistics approach. The 9th International Industrial Engineering Conference, Tehran, Iran Industrial Engineering Association, Khwaja Nasiruddin Toosi University of Technology.
Vanichchinchai, A., & Igel, B. (2009). Total quality management and supply chain management: similarities and differences. The TQM Journal, 21(3), 249-260.
Dai, Y., Zhou, S. X., & Xu, Y. (2012). Competitive and collaborative quality and warranty management in supply chains. Production and Operations management, 21(1), 129-144.
Chien, Y. H. (2019). Optimal periodic replacement policy for a GPP repairable product under the free-repair warranty. Quality Technology & Quantitative Management, 16(3), 347-354.
Wu, X., Nie, L., Xu, M., & Yan, F. (2018). A perishable food supply chain problem considering demand uncertainty and time deadline constraints: Modeling and application to a high-speed railway catering service. Transportation Research Part E: Logistics and Transportation Review, 111, 186-209.
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Ahmadi, K., R. (2008). A total quality model for the supply chain of the automotive industry. (Case study: Iran Khodro Company). [Doctoral dissertation, Tarbiat Modares University, Tehran].
Akkerman, R., Farahani, P., & Grunow, M. (2010). Quality, safety and sustainability in food distribution: a review of quantitative operations management approaches and challenges. OR spectrum, 32, 863-904.
Bandyopadhyay, J. K., & Sprague, D. A. (2003). Total quality management in an automotive supply chain in the United States. International Journal of Management, 20(1), 17.
Doosti A., & Moghaddam S. R., (2022) Presenting a Multi-Objective Mathematical Model of Multi-Product and MultiStage Fuzzy Production Planning For Several Periods in Gamz Software. Journal of Strategic Management in Industrial System, 17(59), 99-112.
Ghasimi, A., S., Ramli, R., & Saibani, N., (2013) A genetic algorithm for optimizing defective goods supply chain,costs using JIT logistics and each-cycle lengths. Journal of Applied Mathematical Modelling, 38 (2014), 1534–1547.
Gunasekaran, A., & McGaughey, R. E. (2003). TQM is suppy chain management. The TQM magazine, 15(6), 361-363.
Hasni, A., A. (2010). Designing a stable reverse/forward supply chain for perishable goods. [Master Thesis in Industrial Engineering, Tarbiat Modares University, Tehran].
Bajani, S. E., Saberi, S., & Toyasaki, F. (2022). Reverse Supply Chain Network with Return Products Quality Consideration. IFAC-PapersOnLine, 55(10), 2926-2931.
Jaafarnejad, A. (2012). Modern production and operations management, 2nd ed, Faculty of Management, University of Tehran.
Juran, J. M., Godfrey, A. B., Hoogstoel, R. E., & Schilling, E. G. (1999). Juran’s quality handbook 5th ed.
Karthick, B., & Uthayakumar, R. (2022). Impact of carbon emission reduction on supply chain model with manufacturing decisions and dynamic lead time under uncertain demand. Cleaner Logistics and Supply Chain, 4, 100037.
Kazemi, , M., & Taki, P., (2016). Simulation of transportation cost for supply chain network design by considering the demand related to price and quality. Journal of quality engineering and management, 6(1), 57-65.
Li, S., Rao, S. S., Ragu-Nathan, T. S., & Ragu-Nathan, B. (2005). Development and validation of a measurement instrument for studying supply chain management practices. Journal of operations management, 23(6), 618-641.
Nazemi, , Usefinejad, M., & Ghafari, M., (2017). solving a three-level supply chain model with the aim of increasing quality and reducing possible delivery time. Journal of engineering management and soft computing, 3(1), 31-63.
Robinson, C. J., & Malhotra, M. K. (2005). Defining the concept of supply chain quality management and its relevance to academic and industrial practice. International journal of production economics, 96(3), 315-337.
Tabrizi, S., Ahmadi, A., & Karimi, A. (2012). Modeling the supply chain of warm-water farmed fish in Iran with an integrated logistics approach. The 9th International Industrial Engineering Conference, Tehran, Iran Industrial Engineering Association, Khwaja Nasiruddin Toosi University of Technology.
Vanichchinchai, A., & Igel, B. (2009). Total quality management and supply chain management: similarities and differences. The TQM Journal, 21(3), 249-260.
Dai, Y., Zhou, S. X., & Xu, Y. (2012). Competitive and collaborative quality and warranty management in supply chains. Production and Operations management, 21(1), 129-144.
Chien, Y. H. (2019). Optimal periodic replacement policy for a GPP repairable product under the free-repair warranty. Quality Technology & Quantitative Management, 16(3), 347-354.
Wu, X., Nie, L., Xu, M., & Yan, F. (2018). A perishable food supply chain problem considering demand uncertainty and time deadline constraints: Modeling and application to a high-speed railway catering service. Transportation Research Part E: Logistics and Transportation Review, 111, 186-209.
