Document Type : Research Paper
Authors
Abstract
The volatile condition of today’s market is forcing the manufacturing managers to adapt the flexible manufacturing systems (FMS) to meet the challenges imposed by international competition, ever changing customer demands, rapid delivery to market and advancement in technology. Despite various barriers to implementation and development of FMS, there are enablers which facilitate this issue. One of the most important issues in this field and also the aim of this paper is to analysis the behavior of these enablers in order to effective utilization of them in the implementation and development of FMS. Enablers identified through literature review and industrial, and academic experts' opinion. Interpretive structural modelling (ISM) is used to develop a hierarchical structure for analyzing the interactions among enablers. Interpretive ranking process (IRP) is then used to examine the dominance relationship. ISM model highlights the importance of top management commitment and Financial investment over other enablers, whereas IRP model revealed supply chain management and operational and control techniques as the most important enablers due to performance areas. This study also gives a comparative account of ISM and IRP and shows that IRP is a more powerful tool, since it goes one-step further and considers the relationship of enablers with measurable performance indicators
Keywords
منابع
طلایی، حمیدرضا) 1366 (، " شناسایی و تبیین عوامل توانمندساز جهت توسعه سیستم تولید انعطاف
پذیر با رویکرد مدل سازی ساختاری تفسیری ISM در صنعت خودروسازی ایران"،پایان نامه
کارشناسی ارشد، دانشگاه شهید بهشتی، دانشکده مدیریت، تهران، ایران.
عالم تبریز،اکبر،سبحانی فر،یاسر ) 1366 (، مدیریت تولید و عملیات،کتاب دانشگاهی،تهران.
هوشمند،محمود،تقوی،محسن) 1332 (، " بررسی سیستم های حمل و نقل اتوماتیک مواد در مونتاژ
انعطاف پذیر )مطالعه موردی مونتاژ موتورسیکلت("، ، فصلنامه شریف ویژه علوم مهندسی، دوره 64
- . شماره 42 ، صفحات 31 43
Azevedo, S., Carvalho, H., & Cruz-Machado, V. (2013). Using interpretive structural modelling to identify and rank performance measures: An application in the automotive supply chain. Baltic Journal of Management, 8(2), 208–230.
Bag, S. (2014). Modeling the Enablers of Flexible Manufacturing Systems using Interpretive Structural Modeling. Journal of Supply Chain Management Systems, 3(3).
Başak, Ö., & Albayrak, Y. E. (2015). Petri net based decision system modeling in real-time scheduling and control of flexible automotive manufacturing systems. Computers & Industrial Engineering, 86, 116–126.
Boyle, T. A. (2006). Towards best management practices for implementing manufacturing flexibility. Journal of Manufacturing Technology Management, 17(1), 6–21.
Caggiano, A., Caiazzo, F., & Teti, R. (2015). Digital Factory Approach for Flexible and Efficient Manufacturing Systems in the Aerospace Industry. Procedia CIRP, 37, 122–127.
Chan, F.T.S. and Swarnkar, R. (2006). Ant colony optimisation approach to a fuzzy goal programming model for a machine tool selection and operation allocation problem in an FMS. Robot. & Comp.-Integ. Manuf, 22, 353–562.
Choe, P., Tew, J. D., & Tong, S. (2015). Effect of cognitive automation in a material handling system on manufacturing flexibility. International Journal of Production Economics, 170, 891–899.
Dhinesh, K., Karunamoorthy, L., Roth, H. and Miranlinee, T. . (2005). Computers in manufacturing: towards successful
تحلیل توانمندسازهای سیستم تولید انعطاف پذیر با رویکردهای مدل سازی ... 25
implementation of integrated automation system. Technovation, 25, 477–488.
Dubey, R., & Ali, S. S. (2014). Identification of flexible manufacturing system dimensions and their interrelationship using total interpretive structural modelling and fuzzy MICMAC analysis. Global Journal of Flexible Systems Management, 15(2), 131–143.
El-tamimi AM, Abidi MH, Mian SH, A. J. (2012). Analysis of performance measures of flexible manufacturing system. J King Saud Uni-Engineering Sci, 24, 115–129.
Erdin, M. E., & Atmaca, A. (2015). Implementation of an Overall Design of a Flexible Manufacturing System. Procedia Technology, 19, 185–192.
Jimenez, J.-F., Bekrar, A., Trentesaux, D., Rey, G. Z., & Leitao, P. (2015). Governance mechanism in control architectures for flexible manufacturing systems. IFAC-PapersOnLine, 48(3), 1093–1098.
Joshi, S., & Smith, J. (2012). Computer control of flexible manufacturing systems: research and development. Springer Science & Business Media.
Kost, G.G. and Zdanowicz, R. (2005). Modeling of manufacturing systems and robot motions. Journal of Materials Processing Technology, 164–165, 1369–1378.
Lal, R. and Haleem, A. (2009). A structural modelling for e-governance service delivery in rural India. International Journal of Electronic Governance, 2(1), 3–21.
Llorens, J.F., Molinaa, L.M. and Verdu, A. . (2005). Flexibility of manufacturing system, strategic change and performance. International Journal of Production Economics, 98, 273–89.
Mehrjerdi, Y. Z. (2009). A decision-making model for flexible manufacturing system. Assembly Automation, 29(1), 32–40.
Mital, A., & Anand, S. (2013). Handbook of expert systems applications in manufacturing structures and rules. Springer Science & Business Media.
Narain, R., Yadav, R.C. and Antony, J. (2004). Productivity gains from flexible manufacturing: experiences from India. Int. J. Prod. Perform. Manage, 53(2), 109–128.
Raj, T., Shankar, R. and Suhaib, M. (2007). A review of some issues and identification of some barriers in the implementation of FMS. International Journal of Flexible Manufacturing Systems, 19(1), 1–40.
69 مطالعات مدیریت صنعتی – سال پانزدهم، شماره 44 ، بهار 69
Raj, T., Shankar, R., & Suhaib, M. (2008). An ISM approach for modelling the enablers of flexible manufacturing system: the case for India. International Journal of Production Research (Vol. 46).
Saaty, T. L. (1977). The analytic hierarchy process. New York: McGraw Hill.
Singh, S. R., & Saxena, N. (2013). A closed loop supply chain system with flexible manufacturing and reverse logistics operation under shortages for deteriorating items. Procedia Technology, 10, 330–339.
Sushil. (2005). Interpretive Matrix: a tool to aid interpretation of management and social research. Global Journal of Flexible System Management, 6(2), 11–20.
Sushil. (2009). Interpretive ranking process. Global Journal of Flexible Systems Management, 10(4), 1–10.
Theodorou, P. and Florou, G. (2008). Manufacturing strategies and financial performance: the effect of advance information technology: CAD/CAM systems. Omega. Int. J. Manage. Sci., 36(1), 107–121.
Tilak Raj, Ravi Shankar, M. S. (2010). GTA-based framework for evaluating the feasibility of transition to FMS. Journal of Manufacturing Technology Management, 21(2), 160–187.
Trivedi, A., Singh, A., & Chauhan, A. (2015). Analysis of key factors for waste management in humanitarian response: An interpretive structural modelling approach. International Journal of Disaster Risk Reduction, 14, 527–535.
Tseng, M. L. (2013). Modeling sustainable production indicators with linguistic preferences. Journal of Cleaner Production, 40, 46–56.
Valmohammadi, C., & Dashti, S. (2016). Using interpretive structural modeling and fuzzy analytical process to identify and prioritize the interactive barriers of e-commerce implementation. Information & Management, 53(2), 157–168.
طلایی، حمیدرضا) 1366 (، " شناسایی و تبیین عوامل توانمندساز جهت توسعه سیستم تولید انعطاف
پذیر با رویکرد مدل سازی ساختاری تفسیری ISM در صنعت خودروسازی ایران"،پایان نامه
کارشناسی ارشد، دانشگاه شهید بهشتی، دانشکده مدیریت، تهران، ایران.
عالم تبریز،اکبر،سبحانی فر،یاسر ) 1366 (، مدیریت تولید و عملیات،کتاب دانشگاهی،تهران.
هوشمند،محمود،تقوی،محسن) 1332 (، " بررسی سیستم های حمل و نقل اتوماتیک مواد در مونتاژ
انعطاف پذیر )مطالعه موردی مونتاژ موتورسیکلت("، ، فصلنامه شریف ویژه علوم مهندسی، دوره 64
- . شماره 42 ، صفحات 31 43
Azevedo, S., Carvalho, H., & Cruz-Machado, V. (2013). Using interpretive structural modelling to identify and rank performance measures: An application in the automotive supply chain. Baltic Journal of Management, 8(2), 208–230.
Bag, S. (2014). Modeling the Enablers of Flexible Manufacturing Systems using Interpretive Structural Modeling. Journal of Supply Chain Management Systems, 3(3).
Başak, Ö., & Albayrak, Y. E. (2015). Petri net based decision system modeling in real-time scheduling and control of flexible automotive manufacturing systems. Computers & Industrial Engineering, 86, 116–126.
Boyle, T. A. (2006). Towards best management practices for implementing manufacturing flexibility. Journal of Manufacturing Technology Management, 17(1), 6–21.
Caggiano, A., Caiazzo, F., & Teti, R. (2015). Digital Factory Approach for Flexible and Efficient Manufacturing Systems in the Aerospace Industry. Procedia CIRP, 37, 122–127.
Chan, F.T.S. and Swarnkar, R. (2006). Ant colony optimisation approach to a fuzzy goal programming model for a machine tool selection and operation allocation problem in an FMS. Robot. & Comp.-Integ. Manuf, 22, 353–562.
Choe, P., Tew, J. D., & Tong, S. (2015). Effect of cognitive automation in a material handling system on manufacturing flexibility. International Journal of Production Economics, 170, 891–899.
Dhinesh, K., Karunamoorthy, L., Roth, H. and Miranlinee, T. . (2005). Computers in manufacturing: towards successful
تحلیل توانمندسازهای سیستم تولید انعطاف پذیر با رویکردهای مدل سازی ... 25
implementation of integrated automation system. Technovation, 25, 477–488.
Dubey, R., & Ali, S. S. (2014). Identification of flexible manufacturing system dimensions and their interrelationship using total interpretive structural modelling and fuzzy MICMAC analysis. Global Journal of Flexible Systems Management, 15(2), 131–143.
El-tamimi AM, Abidi MH, Mian SH, A. J. (2012). Analysis of performance measures of flexible manufacturing system. J King Saud Uni-Engineering Sci, 24, 115–129.
Erdin, M. E., & Atmaca, A. (2015). Implementation of an Overall Design of a Flexible Manufacturing System. Procedia Technology, 19, 185–192.
Jimenez, J.-F., Bekrar, A., Trentesaux, D., Rey, G. Z., & Leitao, P. (2015). Governance mechanism in control architectures for flexible manufacturing systems. IFAC-PapersOnLine, 48(3), 1093–1098.
Joshi, S., & Smith, J. (2012). Computer control of flexible manufacturing systems: research and development. Springer Science & Business Media.
Kost, G.G. and Zdanowicz, R. (2005). Modeling of manufacturing systems and robot motions. Journal of Materials Processing Technology, 164–165, 1369–1378.
Lal, R. and Haleem, A. (2009). A structural modelling for e-governance service delivery in rural India. International Journal of Electronic Governance, 2(1), 3–21.
Llorens, J.F., Molinaa, L.M. and Verdu, A. . (2005). Flexibility of manufacturing system, strategic change and performance. International Journal of Production Economics, 98, 273–89.
Mehrjerdi, Y. Z. (2009). A decision-making model for flexible manufacturing system. Assembly Automation, 29(1), 32–40.
Mital, A., & Anand, S. (2013). Handbook of expert systems applications in manufacturing structures and rules. Springer Science & Business Media.
Narain, R., Yadav, R.C. and Antony, J. (2004). Productivity gains from flexible manufacturing: experiences from India. Int. J. Prod. Perform. Manage, 53(2), 109–128.
Raj, T., Shankar, R. and Suhaib, M. (2007). A review of some issues and identification of some barriers in the implementation of FMS. International Journal of Flexible Manufacturing Systems, 19(1), 1–40.
69 مطالعات مدیریت صنعتی – سال پانزدهم، شماره 44 ، بهار 69
Raj, T., Shankar, R., & Suhaib, M. (2008). An ISM approach for modelling the enablers of flexible manufacturing system: the case for India. International Journal of Production Research (Vol. 46).
Saaty, T. L. (1977). The analytic hierarchy process. New York: McGraw Hill.
Singh, S. R., & Saxena, N. (2013). A closed loop supply chain system with flexible manufacturing and reverse logistics operation under shortages for deteriorating items. Procedia Technology, 10, 330–339.
Sushil. (2005). Interpretive Matrix: a tool to aid interpretation of management and social research. Global Journal of Flexible System Management, 6(2), 11–20.
Sushil. (2009). Interpretive ranking process. Global Journal of Flexible Systems Management, 10(4), 1–10.
Theodorou, P. and Florou, G. (2008). Manufacturing strategies and financial performance: the effect of advance information technology: CAD/CAM systems. Omega. Int. J. Manage. Sci., 36(1), 107–121.
Tilak Raj, Ravi Shankar, M. S. (2010). GTA-based framework for evaluating the feasibility of transition to FMS. Journal of Manufacturing Technology Management, 21(2), 160–187.
Trivedi, A., Singh, A., & Chauhan, A. (2015). Analysis of key factors for waste management in humanitarian response: An interpretive structural modelling approach. International Journal of Disaster Risk Reduction, 14, 527–535.
Tseng, M. L. (2013). Modeling sustainable production indicators with linguistic preferences. Journal of Cleaner Production, 40, 46–56.
Valmohammadi, C., & Dashti, S. (2016). Using interpretive structural modeling and fuzzy analytical process to identify and prioritize the interactive barriers of e-commerce implementation. Information & Management, 53(2), 157–168.
)