شناسایی و رتبه بندی عوامل مزیت رقابتی اثرگذار بر مسئله انتخاب مواد پلیمری با استفاده از رویکرد هیبریدی فازی.
محورهای موضوعی :
مدیریت صنعتی
morteza yousefi
1
(PhD Student in Management, Zanjan Branch, Islamic Azad University, Zanjan, Iran.)
Nabiollah Mohammadi
2
(Department of Management, Zanjan Branch, Islamic Azad University, Zanjan, Iran.)
Homa Doroudi
3
(Associate Professor in Management, Department of Management, Zanjan Branch, Islamic Azad University, Zanajan, Iran)
تاریخ دریافت : 1399/12/19
تاریخ پذیرش : 1400/07/24
تاریخ انتشار : 1400/09/10
کلید واژه:
"عوامل اثرگذار بر انتخاب مواد",
"مواد پلیمری خودرو",
" رویکرد فازی",
چکیده مقاله :
امروزه به دلیل پیچیدگی و دخیل بودن عوامل متعدد در بحث انتخاب مواد، تولیدکنندگان در عرصۀ رقابتی به ابزاری قوی و علمی نیازمندند که تمامی عوامل اثرگذار در انتخاب مواد را شناسایی و میزان اهمیت این عوامل را مشخص نموده و بین آن‌ها تعادل برقرار کنند. در این پژوهش سعی داریم یک رویکرد ترکیبی فازی در جهت شناسایی و اولویت‌بندی عوامل اثرگذار در انتخاب مواد پلیمری خودرو ارائه کنیم. بدین منظور پس از مرور سوابق تجربی با نظرسنجی از خبرگان سازمانی و به‌کارگیری تکنیک دلفی فازی، عوامل مزیت رقابتی اثرگذار در انتخاب مواد را شناسایی و غربال‌سازی کرده و با استفاده از تکنیک تحلیل سلسله مراتبی فازی، این عوامل را وزن دهی و اولویت‌بندی نمودیم. بر اساس نتایج به‌دست‌آمده با تکنیک دلفی فازی پنج شاخص: اقتصادی، فنی، زیست‌محیطی، اجتماعی و تکنولوژی مشتمل بر 29 زیر شاخص مرتبط شناسایی و غربال شدند. سپس میزان اهمیت شاخص‌ها و زیر شاخص‌ها را با تکنیک تحلیل سلسله مراتبی فازی محاسبه نمودیم. نتایج به‌دست‌آمده نشان داد که بیشترین میزان اهمیت مربوط به شاخص‌های فنی و اقتصادی و کمترین میزان اهمیت مربوط به شاخص تکنولوژی است. در ضمن از شاخص اقتصادی مؤلفه ارزش بازاری، از شاخص فنی مؤلفه وزن، از شاخص زیست‌محیطی مؤلفه قابلیت بازیافت و استفاده مجدد، از شاخص اجتماعی مؤلفه سلامت و ایمنی و از شاخص تکنولوژی مؤلفه امکانات فعلی، حائز بالاترین درجه اهمیت شدند.
چکیده انگلیسی:
Today, due to the complexity and involvement of various factors in the discussion of material selection, manufacturers in the field of competition need a strong and scientific tool that identify all the factors influencing the choice of materials, determine the importance these factors and balance them .In this research, we try to present a fuzzy hybrid approach to identify and prioritize the factors influencing the selection of automotive polymeric materials. For this purpose, after reviewing the experimental records by surveying organizational experts and using fuzzy Delphi technique, we identified and screened the factors of competitive advantage affecting the selection of materials and we weighted and prioritized these factors using fuzzy hierarchical analysis technique. Based on the results obtained by fuzzy Delphi technique, five indicators: economic, technical, environmental, social and technology inclusive of 29 related sub-indicators, identified and Sieved. Then we calculated the importance of indices and sub-indices using fuzzy hierarchical analysis technique. The results showed that the highest importance is related to technical and economic indicators and the least importance is related to technology index. In addition,from the economic index Sub-index the market value, From the technical index Sub-index the weight, From the environmental index Sub-index the recyclability, From the social index Sub-index the health and safety and from the technology index Sub-index the current facilities, obtained the highest degree of importance.
منابع و مأخذ:
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Ali, B. A., Sapuan, S. M., Zainudin, E. S., & Othman, M. (2015). Implementation of the expert decision system for environmental assessment in composite materials selection for automotive components. Journal of Cleaner Production, 107, 557-567.
Anojkumar, L., Ilangkumaran, M., & Sasirekha, V. (2014). Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Systems with Applications, 41(6), 2964-2980.
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Amiri, M., HadiNejad, F., & MalekKhoyan, S. (2017). Evaluation and Prioritization of Suppliers with a Combined Entropy Approach, Modified Hierarchical, and Primitive Analysis Process (Case Study: YouTube). Journal of Operations Research in its Applications. 14(4), 20-1. (In percian).
Ardakani, M., Ketabi. S., & Mohammad Shafiei, M. (2013). Employee Ranking and Supervisor Selection with a Fuzzy Hierarchical Fuzzy Hierarchy Process Analysis and Fuzzy Topsis Approach (Case Study, Ghadir Iranian Steel Factory). Production and Operations Management, 4(7), 1-22. [In Persian].
Azar, A., & Faraji, H. (2015). Fuzzy Management Science. Kind Book Institute. (In percian).
Bhosale, S. B., Bhowmik, S., & Ray, A. (2018). Multi Criteria Decision Making For Selection Of Material Composition For Powder Metallurgy Process. Materials Today: Proceedings, 5(2), 4615-4620.
Chaudhary, B., Ramkumar, P. L., & Abhishek, K. (2018). Material Selection for Rotational Moulding Process Using Grey Relational Analysis Approach. Materials Today: Proceedings, 5(9), 19224-19229.
Emovon, I., & Oghenenyerovwho, O. S. (2020). Application of MCDM method in material selection for optimal design: A review. Results in Materials, 7, 100115.
Farhadi, F., & Fayez, A. (2020). Identifying and prioritizing the factors affecting the evaluation of financing chain management (FSCM) using a mixed approach in Isfahan steel production industries. Journal of Industrial Management (Sanandaj Azad), 50 (14), pp148-157.
Gul, M., Celik, E., Gumus, A. T., & Guneri, A. F. (2018). A fuzzy logic based PROMETHEE method for material selection problems. Beni-Suef University Journal of Basic and Applied Sciences, 7(1), 68-79.
Hajipoor, B., & Momeni, K. (2009). Recognizing the Resource-Based Approach to Organizational Resources and Sustainable Competitive Advantage Study: Saran Production Company. Management Thought, 3(1), 77-102.
Hosseini,s. Dehghandehnavi,M., Ghorbanizadeh, V., & Rajai, M. (2018), Explaining the Effective Factor Model on Iranian Bank Credits by Fuzzy Delphi Approach. Perspectives on Financial Management, 6 (21), 115-131, [In Persian].
Hosseinzadeh, A., Pourzarandi, M., & Afshar Kazemi, M. (2020). Analysis of effective factors of organizational architecture in improving supply chain management by hierarchical analysis method (Case study: oil and gas exploitation). Journal of Industrial Management (Sanandaj Azad), 53 (15), 115-134.
Hsu, Y. L., Lee, C. H., & Kreng, V. B. (2010). The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection. Expert Systems with Applications, 37(1), 419-425.
Jayakrishna, K., Kar, V. R., Sultan, M. T., & Rajesh, M. (2018). Materials selection for aerospace components. In Sustainable Composites for Aerospace Applications (pp. 1-18). Woodhead Publishing.
Kardaras, D. K., Karakostas, B., & Mamakou, X. J. (2013). Content presentation personalisation and media adaptation in tourism web sites using Fuzzy Delphi Method and Fuzzy Cognitive Maps. Expert Systems with Applications, 40(6), 2331-2342.
Khajeh, M., Amiri, M., Ulfat, L., & Zandieh, M. (2020). Evaluation and selection of stable suppliers in intuitive fuzzy environment with a combined multi-criteria approach of the best worst and Vicor. Journal of Operations Research in its Applications. Seventeenth year, 1 (64 consecutive, spring 99),48-25. (In percian).
Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., & Bansal, R. C. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596-609.
Latifi, S., Raheli, H., Yadavar, H., sadi, H., & Shahrestani, S. (2018), Identifying and Explaining the Implementation Processes of Conservation Agricultural Development in Iran by Fuzzy Delphi Approach. Iranian Biosystems Engineering, 1, 107-120, [In Persian].
Loganathan, A., & Mani, I. (2018). A fuzzy based hybrid multi criteria decision making methodology for phase change material selection in electronics cooling system. Ain Shams Engineering Journal, 9(4), 2943-2950.
Mahmoudkelaye, S., Azari, K. T., Pourvaziri, M., & Asadian, E. (2018). Sustainable material selection for building enclosure through ANP method. Case Studies in Construction Materials, 9, e00200.
Mehmood, Z., Haneef, I., & Udrea, F. (2018). Material selection for Micro-Electro-Mechanical-Systems (MEMS) using Ashby's approach. Materials & Design, 157, 412-430.
Mehri, Ali. (2004), A Theoretical Look at Sustainable Competitive Advantage. Tadbir Journal, No. 140, 33-39, [In Persian].
Moradian, M., Modanloo, V., & Aghaiee, S. (2018). Comparative analysis of multi criteria decision making techniques for material selection of brake booster valve body. Journal of Traffic and Transportation Engineering (English Edition).
Okokpujie, I. P., Okonkwo, U. C., Bolu, C. A., Ohunakin, O. S., Agboola, M. G., & Atayero, A. A. (2020). Implementation of multi-criteria decision method for selection of suitable material for development of horizontal wind turbine blade for sustainable energy generation. Heliyon, 6(1), e03142.
Patnaik, P. K., Swain, P. T. R., Mishra, S. K., Purohit, A., & Biswas, S. (2020). Composite material selection for structural applications based on AHP-MOORA approach. Materials Today: Proceedings, 33, 5659-5663.
Perçin, S. (2008). Use of fuzzy AHP for evaluating the benefits of information-sharing decisions in a supply chain. Journal of Enterprise Information Management, 21(3), 263-284.
Rezaei, M., Tazesh, Y., Omidipour, M., & Moeinmehr, A. (2018), Finding Armestan Using Fuzzy Delphi Hierarchical Analysis and Geographic Information System (Case Study: Lake City). Regional Planning Quarterly, 7, 28, [In Persian].
Sanjay, M. R., Jawaid, M., Naidu, N. V. R., & Yogesha, B. (2019). TOPSIS method for selection of best composite laminate. In Modelling of Damage Processes in Biocomposites, Fibre-Reinforced Composites and Hybrid Composites (pp. 199-209). Woodhead Publishing.
Samadimiarkolai, H., Samadimiarkolai, H., & Bastami, M., (2017). Applying fuzzy Delphi method and fuzzy group hierarchy process in identifying and ranking indicators affecting the development of organizational entrepreneurship. Innovation and value creation. 6(11), 61-74. (In percian).
Sapuan, S. M., Kho, J. Y., Zainudin, E. S., Leman, Z., Ali, B. A., & Hambali, A. (2011). Materials selection for natural fiber reinforced polymer composites using analytical hierarchy process. NISCAIR-CSIR, India.
Singh, A. K., Avikal, S., Kumar, K. N., Kumar, M., & Thakura, P. (2020). A fuzzy-AHP and M− TOPSIS based approach for selection of composite materials used in structural applications. Materials Today: Proceedings.
Stoffels, P., Kaspar, J., Bähre, D., & Vielhaber, M. (2018). Integrated product and production engineering approach–a tool-based method for a holistic sustainable design, process and material selection. Procedia Manufacturing, 21, 790-797.
Sohrabi, R., Shawardi, M., & Bashiri, V. (2012). Model of using fuzzy AHP and balanced scorecard to select the appropriate ERP system (Case study: Company behpakhsh). Journal of Industrial Management (Sanandaj Azad), 19 (7), pp109-130.
Stoycheva, S., Marchese, D., Paul, C., Padoan, S., Juhmani, A. S., & Linkov, I. (2018). Multi-criteria decision analysis framework for sustainable manufacturing in automotive industry. Journal of Cleaner Production, 187, 257-272.
Tian, G., Zhang, H., Feng, Y., Wang, D., Peng, Y., & Jia, H. (2018). Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews, 81, 682-692.
Torfi, F., Farahani, R. Z., & Rezapour, S. (2010). Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives. Applied Soft Computing, 10(2), 520-528.
Xue, Y. X., You, J. X., Lai, X. D., & Liu, H. C. (2016). An interval-valued intuitionistic fuzzy MABAC approach for material selection with incomplete weight information. Applied Soft Computing, 38, 703-713.
Yang, S. S., Nasr, N., Ong, S. K., & Nee, A. Y. C. (2017). Designing automotive products for remanufacturing from material selection perspective. Journal of Cleaner Production, 153, 570-579.
Zabihilahremi, E. (2010), Processes and mechanisms for creating and maintaining sustainable competitive advantage. International Conference on Financial Services Marketing, 2, [In Persian].
Zhang, H., Wu, Y., Wang, K., Peng, Y., Wang, D., Yao, S., & Wang, J. (2020). Materials selection of 3D-printed continuous carbon fiber reinforced composites considering multiple criteria. Materials & Design, 196, 109140.
Zhang, Q., Hu, J., Feng, J., & Liu, A. (2020). A novel multiple criteria decision making method for material selection based on GGPFWA operator. Materials & Design, 195, 109038.
Zindani, D., & Kumar, K. (2018). Material Selection for Turbine Seal Strips using PROMETHEE-GAIA Method. Materials Today: Proceedings, 5(9), 17533-17539.
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Al-Oqla, F. M., & Sapuan, S. M. (2017). Materials selection for natural fiber composites. Woodhead Publishing.
Ali, B. A., Sapuan, S. M., Zainudin, E. S., & Othman, M. (2015). Implementation of the expert decision system for environmental assessment in composite materials selection for automotive components. Journal of Cleaner Production, 107, 557-567.
Anojkumar, L., Ilangkumaran, M., & Sasirekha, V. (2014). Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Systems with Applications, 41(6), 2964-2980.
ArbabShirani, B., Ahmadi, A., & Shahriari, M. (2013), Providing a Framework for Determining the Competitive Status of Organizational Resources Based on Competitive Advantage Criteria. Business Reviews. 85, Special Issue, [In Persian].
Amiri, M., HadiNejad, F., & MalekKhoyan, S. (2017). Evaluation and Prioritization of Suppliers with a Combined Entropy Approach, Modified Hierarchical, and Primitive Analysis Process (Case Study: YouTube). Journal of Operations Research in its Applications. 14(4), 20-1. (In percian).
Ardakani, M., Ketabi. S., & Mohammad Shafiei, M. (2013). Employee Ranking and Supervisor Selection with a Fuzzy Hierarchical Fuzzy Hierarchy Process Analysis and Fuzzy Topsis Approach (Case Study, Ghadir Iranian Steel Factory). Production and Operations Management, 4(7), 1-22. [In Persian].
Azar, A., & Faraji, H. (2015). Fuzzy Management Science. Kind Book Institute. (In percian).
Bhosale, S. B., Bhowmik, S., & Ray, A. (2018). Multi Criteria Decision Making For Selection Of Material Composition For Powder Metallurgy Process. Materials Today: Proceedings, 5(2), 4615-4620.
Chaudhary, B., Ramkumar, P. L., & Abhishek, K. (2018). Material Selection for Rotational Moulding Process Using Grey Relational Analysis Approach. Materials Today: Proceedings, 5(9), 19224-19229.
Emovon, I., & Oghenenyerovwho, O. S. (2020). Application of MCDM method in material selection for optimal design: A review. Results in Materials, 7, 100115.
Farhadi, F., & Fayez, A. (2020). Identifying and prioritizing the factors affecting the evaluation of financing chain management (FSCM) using a mixed approach in Isfahan steel production industries. Journal of Industrial Management (Sanandaj Azad), 50 (14), pp148-157.
Gul, M., Celik, E., Gumus, A. T., & Guneri, A. F. (2018). A fuzzy logic based PROMETHEE method for material selection problems. Beni-Suef University Journal of Basic and Applied Sciences, 7(1), 68-79.
Hajipoor, B., & Momeni, K. (2009). Recognizing the Resource-Based Approach to Organizational Resources and Sustainable Competitive Advantage Study: Saran Production Company. Management Thought, 3(1), 77-102.
Hosseini,s. Dehghandehnavi,M., Ghorbanizadeh, V., & Rajai, M. (2018), Explaining the Effective Factor Model on Iranian Bank Credits by Fuzzy Delphi Approach. Perspectives on Financial Management, 6 (21), 115-131, [In Persian].
Hosseinzadeh, A., Pourzarandi, M., & Afshar Kazemi, M. (2020). Analysis of effective factors of organizational architecture in improving supply chain management by hierarchical analysis method (Case study: oil and gas exploitation). Journal of Industrial Management (Sanandaj Azad), 53 (15), 115-134.
Hsu, Y. L., Lee, C. H., & Kreng, V. B. (2010). The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection. Expert Systems with Applications, 37(1), 419-425.
Jayakrishna, K., Kar, V. R., Sultan, M. T., & Rajesh, M. (2018). Materials selection for aerospace components. In Sustainable Composites for Aerospace Applications (pp. 1-18). Woodhead Publishing.
Kardaras, D. K., Karakostas, B., & Mamakou, X. J. (2013). Content presentation personalisation and media adaptation in tourism web sites using Fuzzy Delphi Method and Fuzzy Cognitive Maps. Expert Systems with Applications, 40(6), 2331-2342.
Khajeh, M., Amiri, M., Ulfat, L., & Zandieh, M. (2020). Evaluation and selection of stable suppliers in intuitive fuzzy environment with a combined multi-criteria approach of the best worst and Vicor. Journal of Operations Research in its Applications. Seventeenth year, 1 (64 consecutive, spring 99),48-25. (In percian).
Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., & Bansal, R. C. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596-609.
Latifi, S., Raheli, H., Yadavar, H., sadi, H., & Shahrestani, S. (2018), Identifying and Explaining the Implementation Processes of Conservation Agricultural Development in Iran by Fuzzy Delphi Approach. Iranian Biosystems Engineering, 1, 107-120, [In Persian].
Loganathan, A., & Mani, I. (2018). A fuzzy based hybrid multi criteria decision making methodology for phase change material selection in electronics cooling system. Ain Shams Engineering Journal, 9(4), 2943-2950.
Mahmoudkelaye, S., Azari, K. T., Pourvaziri, M., & Asadian, E. (2018). Sustainable material selection for building enclosure through ANP method. Case Studies in Construction Materials, 9, e00200.
Mehmood, Z., Haneef, I., & Udrea, F. (2018). Material selection for Micro-Electro-Mechanical-Systems (MEMS) using Ashby's approach. Materials & Design, 157, 412-430.
Mehri, Ali. (2004), A Theoretical Look at Sustainable Competitive Advantage. Tadbir Journal, No. 140, 33-39, [In Persian].
Moradian, M., Modanloo, V., & Aghaiee, S. (2018). Comparative analysis of multi criteria decision making techniques for material selection of brake booster valve body. Journal of Traffic and Transportation Engineering (English Edition).
Okokpujie, I. P., Okonkwo, U. C., Bolu, C. A., Ohunakin, O. S., Agboola, M. G., & Atayero, A. A. (2020). Implementation of multi-criteria decision method for selection of suitable material for development of horizontal wind turbine blade for sustainable energy generation. Heliyon, 6(1), e03142.
Patnaik, P. K., Swain, P. T. R., Mishra, S. K., Purohit, A., & Biswas, S. (2020). Composite material selection for structural applications based on AHP-MOORA approach. Materials Today: Proceedings, 33, 5659-5663.
Perçin, S. (2008). Use of fuzzy AHP for evaluating the benefits of information-sharing decisions in a supply chain. Journal of Enterprise Information Management, 21(3), 263-284.
Rezaei, M., Tazesh, Y., Omidipour, M., & Moeinmehr, A. (2018), Finding Armestan Using Fuzzy Delphi Hierarchical Analysis and Geographic Information System (Case Study: Lake City). Regional Planning Quarterly, 7, 28, [In Persian].
Sanjay, M. R., Jawaid, M., Naidu, N. V. R., & Yogesha, B. (2019). TOPSIS method for selection of best composite laminate. In Modelling of Damage Processes in Biocomposites, Fibre-Reinforced Composites and Hybrid Composites (pp. 199-209). Woodhead Publishing.
Samadimiarkolai, H., Samadimiarkolai, H., & Bastami, M., (2017). Applying fuzzy Delphi method and fuzzy group hierarchy process in identifying and ranking indicators affecting the development of organizational entrepreneurship. Innovation and value creation. 6(11), 61-74. (In percian).
Sapuan, S. M., Kho, J. Y., Zainudin, E. S., Leman, Z., Ali, B. A., & Hambali, A. (2011). Materials selection for natural fiber reinforced polymer composites using analytical hierarchy process. NISCAIR-CSIR, India.
Singh, A. K., Avikal, S., Kumar, K. N., Kumar, M., & Thakura, P. (2020). A fuzzy-AHP and M− TOPSIS based approach for selection of composite materials used in structural applications. Materials Today: Proceedings.
Stoffels, P., Kaspar, J., Bähre, D., & Vielhaber, M. (2018). Integrated product and production engineering approach–a tool-based method for a holistic sustainable design, process and material selection. Procedia Manufacturing, 21, 790-797.
Sohrabi, R., Shawardi, M., & Bashiri, V. (2012). Model of using fuzzy AHP and balanced scorecard to select the appropriate ERP system (Case study: Company behpakhsh). Journal of Industrial Management (Sanandaj Azad), 19 (7), pp109-130.
Stoycheva, S., Marchese, D., Paul, C., Padoan, S., Juhmani, A. S., & Linkov, I. (2018). Multi-criteria decision analysis framework for sustainable manufacturing in automotive industry. Journal of Cleaner Production, 187, 257-272.
Tian, G., Zhang, H., Feng, Y., Wang, D., Peng, Y., & Jia, H. (2018). Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews, 81, 682-692.
Torfi, F., Farahani, R. Z., & Rezapour, S. (2010). Fuzzy AHP to determine the relative weights of evaluation criteria and Fuzzy TOPSIS to rank the alternatives. Applied Soft Computing, 10(2), 520-528.
Xue, Y. X., You, J. X., Lai, X. D., & Liu, H. C. (2016). An interval-valued intuitionistic fuzzy MABAC approach for material selection with incomplete weight information. Applied Soft Computing, 38, 703-713.
Yang, S. S., Nasr, N., Ong, S. K., & Nee, A. Y. C. (2017). Designing automotive products for remanufacturing from material selection perspective. Journal of Cleaner Production, 153, 570-579.
Zabihilahremi, E. (2010), Processes and mechanisms for creating and maintaining sustainable competitive advantage. International Conference on Financial Services Marketing, 2, [In Persian].
Zhang, H., Wu, Y., Wang, K., Peng, Y., Wang, D., Yao, S., & Wang, J. (2020). Materials selection of 3D-printed continuous carbon fiber reinforced composites considering multiple criteria. Materials & Design, 196, 109140.
Zhang, Q., Hu, J., Feng, J., & Liu, A. (2020). A novel multiple criteria decision making method for material selection based on GGPFWA operator. Materials & Design, 195, 109038.
Zindani, D., & Kumar, K. (2018). Material Selection for Turbine Seal Strips using PROMETHEE-GAIA Method. Materials Today: Proceedings, 5(9), 17533-17539.
