ارائه مدلی برای کشف و بررسی ارتباطات علّی بین ریسک‌های موثر در فرآیند توسعه خانواده محصول در صنعت خودرو ایران

نوع مقاله : مقاله صنایع

نویسندگان

گروه مهندسی صنایع، دانشگاه پیام نور، ص.پ. 19395-3697، تهران، ایران

چکیده

راهبرد فرآیند توسعه خانواده محصول در رقابت‌ پاسخ به نیازهای متنوع بازار با ریسک‌هایی مواجه است. تعیین احتمال بروز، نحوه مواجهه و شناخت ریسک‌هایی که مسبب بروز سایر ریسک‌ها هستند، همواره چالش‌زا است. هدف این پژوهش مدیریت تأثیر عدم قطعیت بر نتایج قابل انتظار و افزایش موفقیت فرآیند توسعه خانواده محصول از طریق پرداختن به ریسک‌های مسبب که احتمال شرطی بالاتری دارند، می‌باشد. در این مقاله ریسک‌های هر مرحله از این فرآیند با تمرکز بر نظریه داده بنیاد و نظر 18فرد خبره در صنعت خودروسازی ایران احصاء گردید. سپس جداول تاثیر ریسک‌ها مبتنی بر نقشه شناخت فازی بر مبنای داده‌های حاصل از پرسشنامه تکمیلی در صنایع خودروسازی ایران شکل گرفت. در ادامه جداول احتمالات شرطی تشکیل و با کمک شبکه باور بیزین احتمال شرطی هر ریسک بصورت سیستماتیک محاسبه و ریسک‌های مسبب سایر ریسک‌ها، شناسایی گردید. نتیجه حاصل از مطالعات و محاسبات صورت گرفته نشان دادند که نه تنها برای اولین‌بار ریسک‌‌های خوشه‌بندی مشتریان، ریسک فنی مشخصات طراحی قطعات و ریسک بخش‌بندی استاندارد مختص فرایند توسعه خانواده محصول شناسایی گردیدند، بلکه خروجی مدل، نمایانگر ریسک‌های نیاز با احتمال (19.7%)، ریسک الزامات با احتمال (10.52%) و ریسک فنی مشخصات طراحی قطعات با احتمال (6.32%) بعنوان ریسک‌های مسبب و دارای بالاترین احتمال شرطی بروز جنبه‌های منفی در فرآیند توسعه خانواده محصول درصنعت خودرو ایران می‌باشند. مدیران اجرایی با تمرکز بر کنترل این سه ریسک که بعنوان علت یا ریسک ریشه‌ای مرحله بعد عمل می‌نمایند، به موفقیت بیشتری دست یافته و این فرآیند را با اطمینان بیشتری به پیش ببرند.

کلیدواژه‌ها


عنوان مقاله [English]

Presenting a model for determining and discovering the causal relationships between the effective risks of the product family developing process in the Iranian automotive industry

نویسندگان [English]

  • majid kordbacheh
  • roksana fekri
  • gholamreza Esmaeilian
Dept. of Industrial Engineering, Payame Noor University, Post BOX 3697-19395 ,tehran, iran
چکیده [English]

Companies are always faced with risks in competing to response diversified needs of markets. Determining the probability of occurrence and how to manage and recognize the risks that cause other risks is always a challenge. The purpose of this study is to manage the effect of uncertainty on expected results and increase of product family developing process success through addressing causal risks that have bigger Conditional probability
In this article, the risks of each stage of the product family development process are identified by focusing on the grounded theory based on the responses gathered from 18 experts in Iranian automotive industry Also the effect of the variables was determined through fuzzy cognitive map based on the 18 supplementary questionnaire data in these companies. Then, the conditional probability tables were formed and the probability of each variable was calculated systematically with the help of the Bayesian Belief Networks and causal risk of other risks were identified. The results show that the clustering of customers risk, parts design feature technical risk and modularity risk are specified to this process. The model output, also indicates that the needs risk with the probability of (19.7%), requirement risk (10.52%), and parts design feature technical risk (6.32%) As the causal risk with the highest conditional probability of a negative aspect. The executive managers could achieve greater success by focusing on controlling these three risks that act as the root cause of the next step risks , getting more success and make progress with more certainty .

کلیدواژه‌ها [English]

  • Product family
  • developing process
  • Risk management
  • Conditional probability of risk
  • Fuzzy cognition map
  • Bayesian Belief Networks
[1] L. Gauss, D. P. Lacerda, and P.A. Cauchick Miguel, "Module- based product family design: systematic literature review and meta-synthesis", Journal of Intelligent Manufacturing, 2020, https://doi.org/10.1007/s10845-020-01572-3
[2] P. Francis, M. Golden, and W. Woods, "Defense Acquisitions: Managing Risk to Achieve Better Outcomes", Government Accountability Office, No. GAO-10-374T, Washington DC, 2010.
[3] K. S. Chin, D. W. Tang, J. B. Yang, S. Y. Won, and H. Wang, "Assessing new product development project risk by Bayesian network with a systematic probability generation methodology", Expert Systems with Applications, No. 36, 2009, pp. 9879–9890.
[4] Q. zhu, S. F. Golrizgashti, and J. sarkis, "Product deletion and supply chain repercussions: risk management using FMEA", benchmarking:An International journal, 2020, pp.1463-5771, Doi.10.1108/BIJ-01-2020-0007
[5] J. Jiao, T. W. Simpson, and Z. Siddique, "Product family design and platform-based product development: a state-of-the-art review", Journal of Intelligent Manufacturing, Vol.18, 2007, pp. 5–29.
[6] مجید بهزادیان و رضا برادران کاظم زاده ، "همکاری بخش بندی بازار در توسعه خانه کیفیت و طراحی خانواده محصول ماژولار "، رساله دکتری مهندسی صنایع، دانشگاه امیر کبیر، تهران، ایران، 1387، صفحه 60.
[7] Y. Zhao, and H. Cao, "Risk management on joint product development with power asymmetry between supplier and manufacturer ", International Journal of project management, Vol. 15, No. 33, 2015, pp. 1812 – 1826.
[8] F. Y. Lin, and L. Zhou, " The impacts of product design changes on supply chain risk: a case study ", International Journal of Physical Distribution & Logistics Management, Vol. 41, No. 2, 2011, pp. 162-186.
[9] M. Marinich, "Relationship between risk identification, risk response, and project success", Walden University, doctoral study,2020.
[10] ISO 9000, QUALITY MANAGEMENT SYSTEMS -Fundamentals and vocabulary, International Organization for Standardization, 2015.
[11] ISO 31000, Risk management – Guidelines, provides principles, framework and a process for managing risk, International Organization for Standardization, 2018.
[12] F. Chao, F. Marle, E. Zio, and J. C. Bocquet," Network theory-based analysis of risk interactions in large engineering projects ", Reliability Engineering and System Safety, Vol. 106, 2012, pp. 1-10.
[13] M. Goci'c, G. T. Aronica, G. E. S.tavroulakis, and S. Trajkovic ," Natural Risk Management and Engineering", Springer Tracts in Civil Engineering, 2020, pp.1-21,https://doi.org/10.1007/978-3-030-39391-5_1.
] 14[محمدرضا فضلی خلف، سید کمال چهارسوقی و میر سامان پیشوایی، "طراحی پایای شبکه زنجیره تأمینتأمین حلقه بسته تحت عدم قطعیت: مطالعه موردی یک تولید‌کننده باتری‌‌ اسیدی"، مدل سازی در مهندسی،دوره12، شماره39،1393، صفحه 45-60.
[15] F. Badurdeen, M. Shuaib, K. Wijekoon, A. Brown, W. Faulkner, J. Amundson, I. S. Jawahir, T. J. Goldsby, D. Iyengar, and B. Boden, "Quantitative modeling and analysis of supply chain risks using Bayesian theory", Journal of Manufacturing Technology Management, Vol. 25, No. 6, 2014, pp. 631 – 654.
] 16[عباس شیخان، رضا حافظی، مهدی عمرانی اواردی، امیرناصر اخوان و احمد سعیدی، "ارائه مدل یکپارچه تولید سناریوهای نیمه کمی با استفاده از روش ترکیبی مبتنی بر نقشه شناخت فازی: مطالعه موردی تولید نفت ایران"، مدل سازی در مهندسی، دوره17، شماره 56، 1398، صفحه 157-168.
[17] S. B. Tsai, J. Zhou, Y. Gao, J. Wang, G. Li, Y. Zheng, and W. Xu," Combining FMEA with DEMATEL models to solve production process problems", PloS One, Vol. 12, NO. 8, 2017, e018634.
[18] E. I. Papgeorgiou, and J. L. Salmeron, "Fuzzy cognitive maps for applied sciences and engineering", Intelligent Systems Reference Library, Vol. 54, 2014, Doi: 10.1007/978-3-642-39739-4-1
[19] B. Nepal, and O. P. Yadav, "Bayesian belief network-based framework for sourcing risk analysis during supplier selection", International Journal of production research, Vol. 53, No. 20, 1997, pp. 6114-6135.
[20] R. Kanes, C. Ramirez-Marengo, H. Abdel-Moati, J. Caranefield, and L. Vechot, "Developing a framework for dynamic risk assessment using Bayesian networks and reliability data", Journal of loss prevention in process industries, Vol. 50, 2017, p. 142-153.
[21] R. Hesamamiri, M. M. Mazdeh, M. jafari, and K. Shahanaghi, "Knowledge management reliability assessment: an empirical investigation", Aslib Journal of Information Management, Vol. 67, No. 4, 2015, pp. 422-441.
[22] N. Yodo, and P. Wang, "Resilience Modeling and Quantification for Engineered Systems Using Bayesian Networks", Journal of Mechanical Design, Vol. 138, No. 031404, 2016, pp. 1-12.
[23] S. Nadkarni, and P. P. Shenoy, "A causal mapping approach to constructing Bayesian networks Decision Support Systems, Vol. 38, 2004, pp. 259–281.
[24] W. P. Cheah, K. Y. Kim, H. J. Yang, M. S. Kim, J. S. Kim, and J. S. Kim, " Constructing manufacturing environmental model in Bayesian belief networks for assembly design decision support through fuzzy cognitive maps", International Journal of Intelligent Information and Database Systems, Vol. 3, No. 1, 2009.
[25] R. Kanes, C. Ramirez-Marengo, H. Abdel-Moati, J. Cranefield, and L. Véchot," Developing a framework for dynamic risk assessment Using Bayesian networks and reliability data ", Journal of Loss Prevention in the Process Industries, 2017, doi: 10.1016/j.jlp.2017.09.011.
[26] J. Corbin, J. M. Morse, B. J. Bowers, K. C., A. E. Clarke, C. J. Porr, and P. N. Stern, " Developing Grounded Theory The Second Generation Revisited (2nd ed)", Routledge, 2021, pp. 20-31, https://doi.org/10.4324/9781315169170.
[27] A. S. Cambronero, N. G. Cancelas, and B. M. Serrano, "Analysis of port sustainability using the PPSC
methodology (PESTEL, Porter, SWOT, CAME", World Scientific News, No. 146, 2020, pp. 121–138.
[28] S. V. Flynn, and J. S. Korcuska," Credible phenomenological research: A mixed methods study ", Counselor Education and Supervision, 2018, https://doi.org/10.1002/ceas.12092.
 [29] حسن دانایی فرد، " تئوری‌پردازی با استفاده از رویکرد استقرایی: استراتژی مفهوم‌سازی تئوری بنیادی"، دو ماهنامه دانشور رفتار، دوره 12، شماره 11، تیرماه 1384، صفحه 57- 70.
[30] G. Oh, and Y. S. Hong, "Managing market risk caused by customer preference uncertainty in
product family design with launch flexibility: Product option ", Computers and Industrial Engineering, 2020, 8352-8360, https://doi.org/10.1016/j.cie.2020.106975
[31] V. Bouchereau, and H. Rowlands, “Methods and techniques to help quality function deployment (QFD) benchmarking ", International Journal, Vol. 7, No. 1, 2000, pp. 8 – 20.
[32] T. Lager, "The industrial usability of quality function deployment: a literature review and synthesis on meta- level ", R and D Manage, Vol. 35, No. 4, 2005, pp. 409 – 426.
[33] S. J. Carson, T. Wu, and W. L. Moore, “Managing the trade-off between ambiguity and volatility in new product development ", Journal of Product Innovation Managment, Vol. 29, No. 6, 2012, pp. 1061–1081.
[34] S. Nidumolu, " The effect of coordination and uncertainty on software project performance: residual performance risk as an intervening variable ", Information Systems, Vol. 6, No. 3, 1995, pp. 191–219.
[35] M. Iqbal, and A. Suziant, "Improvement of new product development process by evaluating the existing development approach: Lesson learned from pharmaceutical and ICT companies", AIP Conference Proceedings, 2020, pp. 2227, 040009, https://doi.org/10.1063/5.0001007
[36] B. Prasad, "Synthesis of market research data through a combined effort of QFD, value engineering and value graph techniques ", Qualitative Market Research: An International Journal, Vol. 1, No. 3, 1998a, pp. 156 – 172.
[37] H. Mill, "Enhanced quality functional", World Class Design to Manufacture, Vol. 1, No. 3, 1994, pp. 23 – 26.
[38] L. W. Chan, and M. L. Wu," A systematic approach to quality function deployment with full illustrative example ", Omega, Vol. 33, 2005, pp. 119 – 139.
[39] B. Parasad, "Review of QFD and related deployment techniques", Journal of Manufacturing Systems, Vol. 17, No. 3, 1998, pp. 221 – 234.
[40] J. S. Shin, K. J. Kim, and M. J. Chandra, "Consistency check of a house of quality chart", International Journal of Quality and Reliability Management, Vol. 19, No. 4, 2002, pp. 471 – 484.
[41] S. H. Iranmanesh, V. Thomson, and M. H. Salimi, "Design parameter estimation using a modified QFD method to improve customer perception", Concurrent ENG_RES A, Vol. 13, No. 1, 2005, pp. 57–67.
[42] Y. Z. Chen, and E. W. T. Ngai," A Fuzzy QFD program modelling approach using the method of imprecision, International journal of production research, Vol. 39, 2007, pp. 1 – 18.
[43] S. Myint, "A framework of an intelligent quality function deployment for discrete assembly environment", Computers and Industrial Engineering, Vol. 45, 2003, pp. 269 – 283.
[44] Q. Zhu, S. Golrizgashti, and J. Sarkis, "Product deletion and supply chain repercussions: risk management using FMEA", Benchmarking: International Journal, 2020, 1463-5771, DOI 10.1108/BIJ-01-2020-0007
[45] Y. Reich, and E. Levy, "Managing product quality under resource constraints", International Journal of Production Rsearch, Vol. 42, No. 13, 2004, pp. 2555 – 2572.
[46] G. Hartmann, M. B. Myers Branscomb, M. Lewis, and P. E. Auerswald, "Technical risk, product specifications, and market risk, taking technical risks: How Innovators, Executives, and Investors Manage High Tech Risks Flows", The MIT Press, 2003, pp. 30–43.
[47] J. Januardi, and E. Widodo, "Response surface methodology of dual-channel green supply-chain pricing
model by considering uncertainty", Supply Chain Forum: an International Journal, 2020, https://doi.org/10.1080/16258312.2020.1788904
[48] S. Ma, W. Wang, and L. Liu, "Commonality and postponement in multistage assembly systems European Journal of Operational Research, Vol. 142, 2002, pp. 523–538.
[49] S. Boccaletti, M. Ivanchenko, V. Latora, A. Pluchino, and A. Rapisarda "Detecting complex network modularity by dynamical clustering", Physical Review, Vol. E75, 2007, 045102(R).
[50] A. Jafarian, M. Rabiee, and M. Tavana, "A novel multi-objective co-evolutionary approach for supply chain gapanalysis with consideration of uncertainties", International Journal of Production Economics, Vol. 228, 2020, p. 107852, https://doi.org/10.1016/j.ijpe.2020.107852.
[51] J. Heimicke, C. Scheib, and A. Albers, "Dealing with development risk and complexity in planning situations within product engineering processes", Procedia CIRP, Vol. 91, 2020, pp. 220–229.
[52] D. Abbasi, M. Ashrafi, and S. H. Ghodsypour, "A multi objective-BSC model for new product development project portfolio selection", Expert Systems with Applications, Vol. 162, 2020, pp. 113757-113770
 
]53[ امیر رحیمی منش، حمزه امین طهماسبی و کامبیز شاهرودی، " ارائه مدل بهینه‌سازی ریاضی برای زنجیره تأمین چند محصولی با امکان وقوع اختلال در تأمین‌کننده در شرایط تحریم (مطالعه موردی صنایع تعمیراتی پالایشگاهی"، مدل­سازی در مهندسی، دوره 18شماره60، بهار1399.
 [54] هادی مختاری و علی فلاحی، "ارائه‌ی مدل مقدار اقتصادی تولید با در نظر گرفتن تورم، ارزش زمانی پول و متغیر سرمایه‌گذاری در ظرفیت تولید"، نشریه مهندسی صنایع و مدیریت، دوره 35.1، شماره 1.1، پاییز و زمستان 1398، صفحه 53- 67.
[55] L. Rodriguez-Repiso, R. Setchi, and J. L. Salmeron, "Modelling IT projects success with Fuzzy Cognitive Maps", Expert Systems with Applications, Vol. 32, 2007, pp. 543–559.
[56] W. P. Cheah, Y. S. Kim, K. Y. Kim, and H. J. Yang, "Systematic causal knowledge acquisition using FCM constructor for product design decision support", Expert Systems with Applications, Vol. 38, No. 12, 2011, pp. 15316–15331.
[57] Hugin Expert Available at http://www.hugin.com/ ,2019.