نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، پژوهشگاه علوم و فناوری اطلاعات ایران (ایرانداک)، تهران، ایران

2 استادیار، دانشگاه آزاد اسلامی واحد علوم و تحقیقات، تهران، ایران

3 کارشناسی‌ارشد، دانشگاه آزاد اسلامی واحد علوم و تحقیقات، تهران، ایران

10.22054/jims.2022.59120.2617

چکیده

یکی از چالش های مهم در صنایع خودرو سازی مواجه با ریسک های متفاوت است به ویژه زمانی که به علت پاسخگویی به نیاز مشتریان محصولات جدید ارایه می شود ﮐﻪ باعث ﻋﺪم ﺷﻨﺎﺳﺎﯾﯽ دﻗﯿﻖ و درست در ﺗﻐﯿﯿﺮ روش و طراحی، ﻣﺎﺷﯿﻦ آﻻت و ﻣﻮاد جدید، میزان تقاضا و ﺳﺮﻋﺖ ﺗﻮﻟﯿﺪ و موارد دیگر می شود. این موارد می تواند آسیب ها و خطرات جدی به بار آورد. ﺑﺮای ﺑﻪ ﺣﺪاﻗﻞ رﺳﺎﻧﺪن اﺛﺮات ﻧﺎﻣﻄﻠﻮب این ریسک ها ﺑﺮ روﻧﺪ ﺗﻮﻟﯿﺪ، باید به دنبال روش های درست برای شناسایی ریسک ها و اولویت بندی ریسک ها برای اعمال کنترل ریسک های پر اهمیت بود. از این رو در این مقاله ، پس از شناسایی حوزه های اصلی ریسک های شناسایی شده ریسک های خطوط تولید گرید بندی شدند و بر اساس آن رویکرد نقشه های شناختی فازی توسعه داده شد و 13 ریسک در سه گروه ریسک تکنیکی ، استراتژیکی و عملیاتی شناسایی شده مورد تجزیه و تحلیل قرار گرفتند. سپس با استفاده از رویکرد مدل سازی ساختاری تفسیری، همبستگی ریسک ها ارزیابی شدند و مهمترین ریسک ها با استفاده از فرآیند تحلیل شبکه ای مشخص شدند. در نهایت نتایج نشان می دهد که ریسک های خطا در طراحی، پایین بودن انگیزه ، کمبود منابع مالی، کمبود قطعات و بهره وری پایین جزو پنج ریسک اصلی در زنجیره تامین قطعات خودرو ایساکو می باشند.

کلیدواژه‌ها

عنوان مقاله [English]

Auto parts supply chain risk assessment and rating models using fuzzy cognitive map and Interpretive Structural Modeling

نویسندگان [English]

  • Mohamad javad Ershadi 1
  • Amir Azizi 2
  • Majid Mohajeri 3

1 Associate Professor, Iranian Research Institute for Information Science and Technology (IranDoc), Tehran, Iran

2 Assistant Professor, Science and Research Branch, Islamic Azad University, Tehran, Iran .

3 M.A., Science and Research Branch, Islamic Azad University, Tehran, Iran

چکیده [English]

One of the major challenges in the automotive industry is facing different risks, especially when new products are offered due to meeting the needs of customers, which leads to a lack of accurate identification in changing methods and design, new machinery and materials, demand, production speed ,and so on. These can cause serious injuries and risks. To recognizing these risks, you need to look for the right ways to identify risks and prioritize them to exercise control over critical risks. Therefore, in this paper, after identifying the main areas of identified risks, production line risks were graded and based on that, the fuzzy cognitive maps approach was developed and 13 risks were identified in three groups of technical, strategic and operational risks were analyzed. Then, using interpretive structural modeling approach, the correlation of risks was evaluated and the most important risks were identified using the network analysis process. Finally, the results show that the risks of design errors, low motivation, lack of financial resources, lack of parts and low productivity are among the five main risks in the Isaco auto parts supply chain.

کلیدواژه‌ها [English]

  • " Risk analysis"
  • " Ranking "
  • "Fuzzy cognitive map "
  • " Interpretive structural modeling "
  • "Network analysis process "
Abdali. Abdallah, Valian. Siamak et al. (2018), Conceptualization of the structural-interpretive model of ISM in the accounting profession based on the critical evaluation method: Danesh Scientific Research Journal, Volume 8, Number 30, Pages 148-129.
Ahmadi, S., Yeh, C. H., Martin, R., & Papageorgiou, E. (2015). Optimizing ERP readiness improvements under budgetary constraints: International Journal of Production.
Alfat.Ahmed, Shahriari Niya.Ali (2013), structural interpretative modeling of factors influencing the selection of partners in agile supply chain: Journal of Production and Operations Management, Volume 5, Number 2, Pages 128-109.
Ali Pournilash.Skineh, Sanei Far.Majid, Karimnejad.Mohammed, Islami.Ali, Kazemi.Moharram, Tariqat Zamir.Mohammed (2018), Assessment and Management of Environmental Risks of Technical and Engineering Units of Pegah Pasteurized Milk Company, Gilan: The 4th Congress International Development of Agriculture, Natural Resources, Environment and Tourism of Iran, Tabriz, Islamic Art University of Tabriz, Permanent Secretariat-Miad University and in cooperation with Shiraz University, Yasouj University and Mazandaran University.
Alizadeh.Davoud, Irajpour.Alireza (2017), identification and analysis of process damages with P-FMEA method and prioritization of the executive solutions of damages with MADM method: a case study of Qazvin Marinasan factory, the fifth national conference of applied researches in management and Accounting, Tehran, Iran Management Association.
Arvanitoyannis, I. S., & Varzakas, T. H. (2008). Application of ISO 22000 and Failure Mode and Effect Analysis (FMEA) for industrial processing of salmon: A case study.Critical Reviews in Food Science and Nutrition, 48(5), 411–429.
Bağdatlı, M. E. C., Akbıyıklı, R., & Papageorgiou, E. I. (2017). A fuzzy cognitive map approach applied in cost– benefit analysis for highway projects: International Journal of Fuzzy Systems, 19(5), 1512–1527.
Baghbani.Mohammed, Iranzadeh.Soliman, Baqerzadeh Khajeh.Majid (2017), necessary steps and tools for the effective implementation of PFMEA in production organizations: Standard and Quality Management Quarterly.
Baynal, K., Sarı, T., & Akpınar, B. (2018). Risk management in automotive manufacturing process based on FMEA and grey relational analysis: A case study. Advances in Production Engineering & Management, 13(1), 69–80.
Berjis, N., Shirouyehzad, H., & Tavakoli, M. M. (2015). Considering the effect of critical success factors of knowledge management on safety management and determining the principle components of both attitudes in Isfahan car industry: International Journal of Process Management and Benchmarking, 5(4), 515–532.
Bhuvanesh Kumar, M., & Parameshwaran, R. (2018). Fuzzy integrated QFD, FMEA framework for the selection of lean tools in a manufacturing organization: Production Planning & Control. https://doi.org/10.1080/09537287.2018.1434253.
Bowles, J. B., & Peláez, C. E. (1995). Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis: Reliability Engineering & System Safety,50(2), 203–213.
Case, D. M., & Stylios, C. D (2016, December) Introducing a Fuzzy Cognitive Map for modeling power market auction behavior: In 2016 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-8), IEEE.
Certa, A., Enea, M., Galante, G. M., & La Fata, C. M. (2017). ELECTRE TRI-based approach to the failure modes classification on the basis of risk parameters: An alternative to the risk priority number. Computers & Industrial Engineering, 108, 100–110.
Chanamool, N., & Naenna, T. (2016). Fuzzy FMEA application to improve decisionmaking process in an emergency department: Applied Soft Computing, 43, 441–453.
Chang, K. H., & Cheng, C. H. (2011). Evaluating the risk of failure using the fuzzy OWA and DEMATEL method: Journal of Intelligent Manufacturing, 22(2), 113–129.
Chin, K. S., Wang, Y. M., Poon, G. K. K., & Yang, J. B. (2009). Failure mode and effects analysis by data envelopment analysis: Decision Support Systems, 48(1), 246–256.
Cornejo, E. J. R. (2019). Productivity Enhancement Using Process Failure Mode and Effect Analysis (PFMEA) At Z Company Philippines Corporation: Journal of Recent Innovations in Academic Research, 3(1), 161-171.
Dabbagh, R., & Yousefi, S. (2019). A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis: Journal of safety research, 71, 111-123.
Dogu, E., & Albayrak, Y. E. (2018). Criteria evaluation for pricing decisions in strategic marketing management using an intuitionistic cognitive map approach. Soft Economics, 161, 105–115.
El Hassan, A., Dina, S., Elsherpieny, E. A., Kholif, A. M., & Khorshid, M. A. (2017). The role of failure mode and effects analysis in improving the quality performance of dairy laboratories: Journal of Food Safety, 37(4), https://doi.org/10.1111/jfs.12364.
Erbay, B., & Özkan, C (2018) Fuzzy FMEA Application Combined with Fuzzy Cognitive Maps to Manage the Risks of a Software Project. European Journal of Engineering and Formal Sciences, 2(2), 7-22.
Esfahanipour. Akbar, Fakhrabadi. Mehnaz (2014), risk analysis with the combined model of failure mode and effects analysis (FMEA) and fuzzy cognitive map (FCM): the third international accounting and management conference, Tehran, Mehr Eshraq conference institute.
Ferreira, F. A., Ferreira, J. J., Fernandes, C. I., Meidutė-Kavaliauskienė, I., & Jalali, M. S. (2017). Enhancing knowledge and strategic planning of bank customer loyalty using fuzzy cognitive maps: Technological and Economic Development of Economy, 23(6), 860–876.
Gao, M., Shao, X., & Chi, H. (2013).Safety risk assessment and improvement in a food production process. Human and Ecological Risk Assessment: An International Journal, 19(5), 1359–1371.
Garcia, P. A. D. A., Junior, L., Curty, I., & Oliveira, M. A. (2013). A weight restricted DEA model for FMEA risk prioritization: Production, 23(3), 500–507.
Hemad Hamedi and Amir Mehdiabadi (2020) Entrepreneurship resilience and Iranian organizations: application of the fuzzy DANP technique. Asia Pacific Journal of Innovation and Entrepreneurship Vol. 14 No. 3, 2020 pp. 231-247 Emerald Publishing Limited e-ISSN: 2398-7812 p-ISSN: 2071-1395 DOI 10.1108/APJIE-10-2019-0074.
Höfig, K., Klein, C., Rothbauer, S., Zeller, M., Vorderer, M., & Koo, C. H. (2019, September). A Meta-model for Process Failure Mode and Effects Analysis (PFMEA): In 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1199-1202). IEEE.
Jitesh Thakkar, S.G. Veshmukh, A.V. Gupta anV Ravi Shankar, (2017). “Vevelopment of a balanceV scorecarV An integrateV approach of Interpretive Structural MoVeling (ISM) anV Analytic Network Process (ANP)”: International Journal of ProVuctivity anV Performance Management, 56 (1), 25-59.
Jodki. Maryam, Hasanpour. Hosseinali (2017), Prioritization of effective factors on improving employee productivity using the Network Analysis Process (ANP) technique: a case study of Iran's National Standards Organization, Scientific and Promotional Quarterly of Standard and Quality Management, 8th year, number 2, consecutive 29, autumn 2017.
Kardaras, D., & Karakostas, B. (1999). The use of fuzzy cognitive maps to simulate the information systems strategic planning process: Information and Software Technology,41(4), 197–210.
Kosko, B. (1986).Fuzzy cognitive maps: International Journal of Man-machine Studies,24(1), 65–75.
Mashhadi Keshtiban, P., Onari, M. A., Shokri, K., & Jahangoshai Rezaee, M. (2022). Enhancing risk assessment of manufacturing production process integrating failure modes and sequential fuzzy cognitive map. Quality Engineering, 1-14.
Mehri.Dariush, Zamani.Reza, Vathouqi.Abdallah, Namdar.Hossein (2018), Presenting a model for identifying human capital indicators in a military university with the combined approach of ISM ANP: Scientific Journal of Human Resource Management Research of Imam Hossein University (AS)
Moinzad Hossein (2012), risk analysis in information technology management using fuzzy cognitive maps: 10th International Industrial Engineering Conference, Tehran, Iran Industrial Engineering Association, Amir Kabir University of Technology.
Nik Pishe Kouh Jahri. Fatemeh, Maruti. Maryam, Sadeghi Nia. Majid, Amanat Yazdi. Leila (2017), Investigating EFMEA Method Capability in Environmental Risk Assessment and Management: Third International Conference on Civil Engineering, Architecture and Urban Design, Tabriz, Secretariat Permanent Conference, Miyad University in collaboration with Tabriz University of Islamic Art, Khwarazmi University, Shahrekord University.
Peter Madzık, Arash Shahin (2020). QUALITY PAPER Customer categorization using a three-dimensional loyalty matrix analogous to FMEA: International Journal of Quality & Reliability Management Emerald Publishing Limited 0265-671X DOI 10.1108/IJQRM-05-2020-0179.
Razi.Ali, Hosseini.Mohammed (2017), Proposing a new model of failure mode and effect analysis for clustering and ranking the production process: International Journal of Productivity and Quality Management, Volume 21, Number 1, pp. 71-45.
Rezaee, M. J., Yousefi, S., Eshkevari, M., Valipour, M., & Saberi, M. (2020) Risk analysis of health, safety and environment in chemical industry integrating linguistic FMEA, fuzzy inference system and fuzzy DEA: Stochastic Environmental Research and Risk Assessment, 34(1), 201-218.
Rezaei. Alireza, Yousefi. Habib Elah (2018), An intelligent decision-making method to identify and analyze airport risks: Aviation Management Journal, No. 68, pp. 27-14.
Rezaei.Alireza, Salimi.Younes, Yousefi.Ebrahim (2017), Identifying and managing failures in the stone processing industry using cost-based FMEA: International Journal of Advanced Manufacturing Technology, Volume 88, Number 9-12, Pages 3339-3349.
Safdari.Shayan, Mansour.Mohammed Amin, Azami.Ali (2013), Prioritization and interaction analysis between factors affecting the success of new product development projects through ISM and DEMATEL methods: Journal of Production and Industrial Operations Management, Volume 6, Number 1. Page 149-170.
Talebpour. Mohammad, Ahmadi. Sina (2008), intelligent evaluation of FCM fuzzy cognitive map: Eye magazine. Management style, volume 8, number 30, page 28-9.
Thi Quynh Mai Pham, Gyei Kark Park and Kyoung-Hoon Choi. (2020). The efficiency analysis of world top container ports using two-stage uncertainty DEA model and FCM: Maritime Business Review Emerald Publishing Limited 2397-3757 DOI 10.1108/MABR-11-2019-0052.
Visi.Ali, Khodabakhshian.Rosoul, Rohani.Abbas (2017), Rating and Failure Analysis of CNC Machine Lubrication System Based on FFMEA Technique: Fourth International Conference on Industrial and Systems Engineering, Mashhad, Ferdowsi University of Mashhad.
Yousefi Hanumorur.Ahmed, Rafogarzadeh.Mahdieh, Ibni.Mohsen, Khoza E.Syed Amir (2018), Identifying and evaluating the impact of project risks based on the PMBOK standard with FCM approach: The 4th International Industrial Management Conference, Yazd, Yazd University, Anjuman Iranian Industrial Management Science.
Yousefi. Habib Elah, Hojat Panah. Shayan, Mahoud. Mohammad, Mohammad Khani. Mohsen (2018), Investigating the impact of risk management in the construction of a cement factory with a sustainable development approach: a case study of the Nizar cement factory in Qom, the third national conference on strategies to achieve development Sustainable in Iran's Architecture and Urban Planning Sciences, Tehran-Center, Sustainable Development Conferences of Iran, Center for Sustainable Development Solutions.