ارائه یک مدل نوین بهینه‌سازی مبتنی بر شبیه‌سازی جهت یکپارچه‌سازی تصمیمات مربوط به محصولات تحت وارانتی و از وارانتی خارج‌شده

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دکتری مهندسی صنایع، دانشکده مهندسی صنایع و سیستم‌ها، دانشگاه تربیت مدرس، تهران، ایران

2 دانشیار، دانشکده مهندسی صنایع و سیستم‌ها، دانشگاه تربیت مدرس، تهران، ایران

3 استادیار، دانشکده مهندسی صنایع و سیستم‌ها، دانشگاه تربیت مدرس، تهران، ایران

چکیده

در بازار رقابتی امروز، بسیاری از محصولات تحت وارانتی پایه به فروش می­رسند و تولیدکنندگان به‌منظور افزایش حاشیه سود و رضایت مشتریان بعد از اتمام وارانتی پایه، تولیدکنندگان تمدید وارانتی را با قیمت و زمانی مشخص به مشتریان ارائه می‌کنند. در این تحقیق هدف بیشینه‌سازی سود تولیدکننده با تعیین مقادیر بهینه قیمت محصول، طول دوره وارانتی پایه، طول تمدید وارانتی، سطح تعمیر در تعمیر ناقص و میزان تولید قطعات یدکی (برای تقاضای محصولات تحت وارانتی پایه، تمدید وارانتی و از وارانتی خارج‌شده) است. برای مدل‌سازی هر چه‌بهتر شرایط واقعی، فرض بر این است که محصول با سه نوع تعمیر کمینه، ناقص و کامل در زمان خرابی می‌تواند مورد تعمیر قرار گیرد و درصد محصولاتی که هر بار تحت هر تعمیر قرار می‌گیرند نیز به‌عنوان متغیر تصمیم لحاظ شده‌اند. تابع پایایی محصول در زمان اعمال تعمیر ناقص با  رویکرد مدل عمر مجازی کیجیما مورد مدل‌سازی قرار است. رویکرد حل مسئله بر مبنای رویکرد بهینه‌سازی مبتنی بر شبیه‌سازی در سه مرحله صورت گرفته است در مرحله اول متغیرهای تصمیم نظیر قیمت محصول، طول دوره وارانتی پایه، طول دوره تمدید وارانتی، قیمت تمدید وارانتی، سطح تعمیر و احتمال اینکه هر محصول چه نوع تعمیری بر آن صورت گیرد با الگوریتم فرا ابتکاری تعیین می‌شود. سپس با استفاده از شبیه‌سازی مونت‌کارلو تعداد محصولاتی که تمدید وارانتی و تعداد خرابی محصولات را خریداری نموده‌اند محاسبه و در انتها با استفاده از الگوریتم برنامه‌ریزی پویا تولید قطعات یدکی مورد بهینه‌سازی قرار می‌گیرد. این مدل نیز برای محصول جاروبرقی با برند ال‌جی و خدمات پس از فروش گلدیران مورد حل و تحلیل قرارگرفته است.

کلیدواژه‌ها


عنوان مقاله [English]

Introduce a New Simulation-Based Optimization Model to Integrate Decisions about Products under Warranty and Out of Warranty

نویسندگان [English]

  • Mohsen Afsahi 1
  • Ali Hosseinzadeh Kashan 2
  • Bakhtiar Ostadi 3
1 PhD Student in Industrial Engineering, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
2 Assistant Professor, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
3 Assistant Professor, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
چکیده [English]

In today's competitive market, many products are sold under the basic warranty, and in order to increase profit margins and customer satisfaction after the end of the basic warranty, manufacturers offer warranty extensions to customers at a specific price and time. In this research, the aim is to maximize the producer profit by determining the optimal values of product price, length of basic warranty period, length of warranty renewal, repair level in incomplete repair and amount of spare parts (for demand of products under basic warranty, warranty extension and out of warranty). . In order to better model the real situation, it is assumed that the product can be repaired with three types of minimum, incomplete and complete repairs at the time of failure, and the percentage of products that are repaired each time is also considered as a decision variable. have became. The product reliability function is modeled at the time of incomplete repair with the Kijima virtual life model approach. The problem-solving approach is based on the simulation-based optimization approach in three stages. In the first stage, decision variables such as product price, basic warranty period, warranty renewal period, warranty renewal price, repair level and the probability of what kind of repair each product It is determined by a meta-heuristic algorithm. Then, using Monte Carlo simulation, the number of products that have purchased the warranty extension and the number of product failures is calculated, and finally, the production of spare parts is optimized using a dynamic programming algorithm. This model has also been analyzed for LG vacuum cleaner product and Goldiran after-sales service. 

کلیدواژه‌ها [English]

  • Basic Warranty
  • warranty extension
  • pricing
  • Simulation-based optimization
  • incomplete repair
  • products out of warranty. 
[1] W. R. Blischke and D. N. P. Murthy, “Product warranty management-I: A taxonomy for warranty policies,” Eur. J. Oper. Res., vol. 62, no. 2, pp. 127–148, Oct. 1992.
[2] D. N. . Murthy and I. Djamaludin, “New product warranty: A literature review,” Int. J. Prod. Econ., vol. 79, no. 3, pp. 231–260, Oct. 2002.
[3] D. Murthy, O. Solem, T. R.-E. J. of Operational, and  undefined 2004, “Product warranty logistics: Issues and challenges,” Elsevier.
[4] M. Shafiee and S. Chukova, “Maintenance models in warranty: A literature review,” Eur. J. Oper. Res., vol. 229, no. 3, pp. 561–572, Sep. 2013.
[5] D. N. . Murthy, O. Solem, and T. Roren, “Product warranty logistics: Issues and challenges,” Eur. J. Oper. Res., vol. 156, no. 1, pp. 110–126, Jul. 2004.
[6] D. N. . Murthy and I. Djamaludin, “New product warranty: A literature review,” Int. J. Prod. Econ., vol. 79, no. 3, pp. 231–260, Oct. 2002.
[7] Y. Lam and P. Kwok Wai Lam, “An extended warranty policy with options open to consumers,” Eur. J. Oper. Res., vol. 131, no. 3, pp. 514–529, Jun. 2001.
[8] T. S. Glickman and P. D. Berger, “Optimal Price and Protection Period Decisions for a Product Under Warranty,” Manage. Sci., vol. 22, no. 12, pp. 1381–1390, Aug. 1976.
[9] J.-T. Teng and G. L. Thompson, “Optimal strategies for general price-quality decision models of new products with learning production costs,” Eur. J. Oper. Res., vol. 93, no. 3, pp. 476–489, Sep. 1996.
[10] P.-C. Lin and L.-Y. Shue, “Application of optimal control theory to product pricing and warranty with free replacement under the influence of basic lifetime distributions,” Comput. Ind. Eng., vol. 48, no. 1, pp. 69–82, Jan. 2005.
[11] B. Kim and S. Park, “Optimal pricing, EOL (end of life) warranty, and spare parts manufacturing strategy amid product transition,” Eur. J. Oper. Res., vol. 188, no. 3, pp. 723–745, Aug. 2008.
[12] Z. Zhou, Y. Li, and K. Tang, “Dynamic pricing and warranty policies for products with fixed lifetime,” Eur. J. Oper. Res., vol. 196, no. 3, pp. 940–948, Aug. 2009.
[13] S. A. Yazdian, K. Shahanaghi, and A. Makui, “Joint optimisation of price, warranty and recovery planning in remanufacturing of used products under linear and non-linear demand, return and cost functions,” Int. J. Syst. Sci., vol. 47, no. 5, pp. 1155–1175, Apr. 2016.
[14] M. N. Darghouth, D. Ait-kadi, and A. Chelbi, “Joint optimization of design, warranty and price for products sold with maintenance service contracts,” Reliab. Eng. Syst. Saf., vol. 165, pp. 197–208, Sep. 2017.
[15] C.-K. Chen, C.-C. Lo, and T.-C. Weng, “Optimal production run length and warranty period for an imperfect production system under selling price dependent on warranty period,” Eur. J. Oper. Res., vol. 259, no. 2, pp. 401–412, Jun. 2017.
[16] H.-Z. Huang, Z.-J. Liu, and D. N. P. Murthy, “Optimal reliability, warranty and price for new products,” IIE Trans., vol. 39, no. 8, pp. 819–827, May 2007.
[17] J. Khawam, W. H. Hausman, and D. W. Cheng, “Warranty Inventory Optimization for Hitachi Global Storage Technologies, Inc.,” Interfaces (Providence)., vol. 37, no. 5, pp. 455–471, Oct. 2007.
[18] Y.-C. Tsao, W.-G. Teng, R.-S. Chen, and W.-Y. Chou, “Pricing and inventory policies for Hi-tech products under replacement warranty,” Int. J. Syst. Sci., vol. 45, no. 6, pp. 1255–1267, Jun. 2014.
[19] V. Padmanabhan, “U sage H eterogeneity and E xtended W arranties,” J. Econ. Manag. Strateg., vol. 4, no. 1, pp. 33–53, Mar. 1995.
[20] N. Jack and D. N. P. Murthy, “A flexible extended warranty and related optimal strategies,” J. Oper. Res. Soc., vol. 58, no. 12, pp. 1612–1620, Dec. 2007.
[21] J. C. Hartman and K. Laksana, “Designing and pricing menus of extended warranty contracts,” Nav. Res. Logist., vol. 56, no. 3, pp. 199–214, Apr. 2009.
[22] S. Wu and P. Longhurst, “Optimising age-replacement and extended non-renewing warranty policies in lifecycle costing,” Int. J. Prod. Econ., vol. 130, no. 2, pp. 262–267, Apr. 2011.
[23] S. Bouguerra, A. Chelbi, and N. Rezg, “A decision model for adopting an extended warranty under different maintenance policies,” Int. J. Prod. Econ., vol. 135, no. 2, pp. 840–849, Feb. 2012.
[24] N. Tao and S. Zhang, “The optimal extended warranty length of durable-goods-based preventive maintenance behaviour,” Syst. Sci. Control Eng., vol. 3, no. 1, pp. 472–477, Jan. 2015.
[25] M. Park, K. M. Jung, and D. H. Park, “Optimal maintenance strategy under renewable warranty with repair time threshold,” Appl. Math. Model., vol. 43, pp. 498–508, Mar. 2017.
[26] Z. Lu and J. Shang, “Warranty Mechanism for Pre-owned Tech Products: Collaboration Between E-tailers and Online Warranty Provider,” Int. J. Prod. Econ., Jan. 2019.
[27] M. Kijima and T. Nakagawa, “A cumulative damage shock model with imperfect preventive maintenance,” Nav. Res. Logist., vol. 38, no. 2, pp. 145–156, Apr. 1991.
[28] A. Husseinzadeh Kashan, “A new metaheuristic for optimization: Optics inspired optimization (OIO),” Comput. Oper. Res., vol. 55, pp. 99–125, Mar. 2015.