Production
https://prod.org.br/article/doi/10.1590/0103-6513.20180092
Production
Research Article

Implementation of a Flexible Manufacturing System in a production cell of the automotive industry: decision and choice

Miguel Afonso Sellitto; Vagner Gerhardt Mancio

Downloads: 8
Views: 1648

Abstract

Abstract: Paper aims: The purpose is to decide on the technology for the implementation of an FMS in a manufacturing cell that produces the coil for starting engines in a company of the Brazilian automotive industry.

Originality: The mixed use of structured methods to support a semi-structured decision-making problem.

Research method: The qualitative-quantitative modeling, relying on four competitive priorities of the manufacturing, cost, quality, flexibility, and delivery. The method considered three technological alternatives A1, a ladder-type layout, conveyor and pneumatic devices, A2, an open field layout and automatic guided vehicles, and A3, a robot-centered layout and robotic arms.

Main findings: Two different methods arrived at the same conclusion. The best alternative is A3, which is also better than doing nothing.

Implications for theory and practice: The complete description of a real-world case, embracing the decision-making process and the final choice and the difficulties faced by a decision analyst in supporting practitioners in solving a complex problem.

Keywords

Flexible Manufacturing System, Automation, Manufacturing strategy, Industrial robots, Analytical hierarchy process

References

Achimugu, P., Selamat, A., Ibrahim, R., & Mahrin, M. (2014). A systematic literature review of software requirements prioritization research. Information and Software Technology, 56(6), 568-585. http://dx.doi.org/10.1016/j.infsof.2014.02.001.

Bagozzi, R., Yi, Y., & Phillips, L. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36(3), 421-458. http://dx.doi.org/10.2307/2393203.

Baykasoğlu, A., & Ozsoydan, F. (2017). Minimizing tool switching and indexing times with tool duplications in automatic machines. The International Journal of Advanced Manufacturing Technology, 89(5-8), 1775-1789. http://dx.doi.org/10.1007/s00170-016-9194-z.

Beach, R., Muhlemann, A., Price, D., Paterson, A., & Sharp, J. (2000). A review of manufacturing flexibility. European Journal of Operational Research, 122(1), 41-57. http://dx.doi.org/10.1016/S0377-2217(99)00062-4.

Bi, Z., & Kang, B. (2014). Sensing and responding to the changes of geometric surfaces in flexible manufacturing and assembly. Enterprise Information Systems, 8(2), 225-245. http://dx.doi.org/10.1080/17517575.2012.654826.

Boyer, K. (1998). Longitudinal linkages between intended and realized operations strategies. International Journal of Operations & Production Management, 18(4), 356-373. http://dx.doi.org/10.1108/01443579810199739.

Browne, J., Dubois, D., Rathmill, K., Sethi, S., & Stecke, K. (1984). Classification of flexible manufacturing systems. The FMS Magazine, 2(1), 114-116.

Bulut, E., Duru, O., & Koçak, G. (2015). Rotational priority investigation in fuzzy analytic hierarchy process design: An empirical study on the marine engine selection problem. Applied Mathematical Modelling, 39(2), 913-923. http://dx.doi.org/10.1016/j.apm.2014.07.018.

Deif, A., & ElMaraghy, H. (2017). Variety and volume dynamic management for value creation in changeable manufacturing systems. International Journal of Production Research, 55(5), 1516-1529. http://dx.doi.org/10.1080/00207543.2016.1222088.

Drohomeretski, E., Gouvea da Costa, S. E., Pinheiro de Lima, E., & Garbuio, P. A. R. (2014). Lean, Six Sigma and Lean Six Sigma: an analysis based on operations strategy. International Journal of Production Research, 52(3), 804-824. http://dx.doi.org/10.1080/00207543.2013.842015.

Ghasemzadeh, F. & Archer, N. (2000). Project portfolio selection through decision support. Decision Support Systems, 29, 73-88. http://dx.doi.org/10.1016/S0167-9236(00)00065-8

Gibbert, M., Ruigrok, W., & Wicki, B. (2008). What passes as a rigorous case study? Strategic Management Journal, 29(13), 1465-1474. http://dx.doi.org/10.1002/smj.722.

Gothwal, S., & Raj, T. (2018). Optimisation of AGVs path layout in flexible manufacturing system using 0–1 linear integer programming. International Journal of Process Management and Benchmarking, 8(2), 182-205. http://dx.doi.org/10.1504/IJPMB.2018.090796.

Guasch, A., Piera, M., & Figueras, J. (2011). Automatic warehouse modelling and simulation. International Journal of Simulation & Process Modelling, 6(4), 288-296. http://dx.doi.org/10.1504/IJSPM.2011.048008.

Handfield, R., & Pagell, M. (1995). An analysis of the diffusion of flexible manufacturing systems. International Journal of Production Economics, 39(3), 243-253. http://dx.doi.org/10.1016/0925-5273(95)00026-K.

Javid, R., Nejat, A., & Hayhoe, K. (2014). Selection of CO2 mitigation strategies for road transportation in the United States using a multi-criteria approach. Renewable & Sustainable Energy Reviews, 38(8), 960-972. http://dx.doi.org/10.1016/j.rser.2014.07.005.

Kakati, M., & Dhar, U. (1991). Investment justification in flexible manufacturing systems. Engineering Costs and Production Economics, 21(3), 203-209. http://dx.doi.org/10.1016/0167-188X(91)90001-I.

Karsak, E., & Kuzgunkaya, O. (2002). A fuzzy multiple objective programming approach for the selection of a flexible manufacturing system. International Journal of Production Economics, 79(1), 101-111. http://dx.doi.org/10.1016/S0925-5273(00)00157-2.

Kumar, R., & Mishra, M. (2017). Manufacturing and supply chain flexibility: an integrated viewpoint. International Journal of Services and Operations Management, 27(3), 384-407. http://dx.doi.org/10.1504/IJSOM.2017.084447.

Leong, G., Snyder, D., & Ward, P. (1990). Research in the process and content of manufacturing strategy. Omega, 18(2), 109-122. http://dx.doi.org/10.1016/0305-0483(90)90058-H.

Liesio, J., Mild, P., & Salo, A. (2007). Preference programming for robust portfolio modeling and project selection. European Journal of Operational Research, 181(3), 1488-1505. http://dx.doi.org/10.1016/j.ejor.2005.12.041.

Loch, C., Pich, M., Terwiesch, C., & Urbschat, M. (2001). Selecting R&D projects at BMW: a case study of adopting mathematical programming models. IEEE Transactions on Engineering Management, 48(1), 70-80. http://dx.doi.org/10.1109/17.913167.

Mahmood, K., Karaulova, T., Otto, T., & Shevtshenko, E. (2017). Performance Analysis of a Flexible Manufacturing System (FMS). Procedia CIRP, 63(1), 424-429. http://dx.doi.org/10.1016/j.procir.2017.03.123.

Martínez-Barberá, H., & Herrero-Pérez, D. (2010). Autonomous navigation of an automated guided vehicle in industrial environments. Robotics and Computer-integrated Manufacturing, 26(4), 296-311. http://dx.doi.org/10.1016/j.rcim.2009.10.003.

Monaham, G. E., & Smunt, T. L. (1987). A multilevel decision support system for the financial justification of automated flexible manufacturing systems. Interfaces, 17(1), 29-40. http://dx.doi.org/10.1287/inte.17.6.29.

Myint, S., & Tabucanon, M. (1994). A multiple-criteria approach to machine selection for flexible manufacturing systems. International Journal of Production Economics, 33(1), 121-131. http://dx.doi.org/10.1016/0925-5273(94)90125-2.

Parsaei, H., Karwowski, W., Wilhelm, M., & Walsh, A. (1988). A methodology for economic justification of flexible manufacturing systems. Computers & Industrial Engineering, 15(1), 117-122. http://dx.doi.org/10.1016/0360-8352(88)90073-3.

Prakash, R., Singhal, S., & Agarwal, A. (2017). Modelling manufacturing system effectiveness: an integration of analytical hierarchy process and linear programming. International Journal of Intelligent Enterprise, 4(3), 227-242. http://dx.doi.org/10.1504/IJIE.2017.087627.

Rahman, A., Muhamad, E., Abdullah, S., Rahman, M., Osman, M., Mohamad, N., & Noridan, N. (2017). A concept of physical reconfigurable conveyor system. Journal of Advanced Manufacturing Technology, 11(1), 29-36.

Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53(1), 49-57. http://dx.doi.org/10.1016/j.omega.2014.11.009.

Rezaie, K., & Ostadi, B. (2007). A mathematical model for optimal and phased implementation of flexible manufacturing systems. Applied Mathematics and Computation, 184(2), 729-736. http://dx.doi.org/10.1016/j.amc.2006.05.179.

Roh, J., Hong, P., & Min, H. (2014). Implementation of a responsive supply chain strategy in global complexity: the case of manufacturing firms. International Journal of Production Economics, 147(1), 198-210. http://dx.doi.org/10.1016/j.ijpe.2013.04.013.

Rose-Anderssen, C., Baldwin, J., & Ridgway, K. (2017). Manufacturing systematics and cladistics: state of the art and generic classification. Journal of Manufacturing Technology Management, 28(5), 655-685. http://dx.doi.org/10.1108/JMTM-08-2016-0115.

Rudd, J., Greenley, G., Beatson, A., & Lings, I. (2008). Strategic planning and performance: extending the debate. Journal of Business Research, 61(1), 99-108. http://dx.doi.org/10.1016/j.jbusres.2007.06.014.

Saaty, T. (1983). Priority setting in complex problems. IEEE Transactions on Engineering Management, 30(1), 140-155. http://dx.doi.org/10.1109/TEM.1983.6448606.

Saaty, T. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98. http://dx.doi.org/10.1504/IJSSCI.2008.017590.

Sabattini, L., Cardarelli, E., Digani, V., Secchi, C., Fantuzzi, C., & Fuerstenberg, K. (2015). Advanced sensing and control techniques for multi AGV systems in shared industrial environments. In Emerging Technologies & Factory Automation 2015 proceedings of the international conference in Luxembourg (pp. 1-7). USA: IEEE Piscataway. http://dx.doi.org/10.1109/ETFA.2015.7301488.

Sellitto, M. A. (2018). Assessment of the effectiveness of green practices in the management of two supply chains. Business Process Management Journal, 24(1), 23-48. http://dx.doi.org/10.1108/BPMJ-03-2016-0067. http://dx.doi.org/10.1108/BPMJ-03-2016-0067.

Sellitto, M., Borchardt, M., Pereira, G., & Gomes, L. (2012). Environmental performance assessment of a provider of logistical services in an industrial supply chain. Theoretical Foundations of Chemical Engineering, 46(6), 691-703. http://dx.doi.org/10.1134/S0040579512060206.

Shivanand, H., Benal, M., & Koti, V. (2006). Flexible manufacturing system. Bangalore: New Age International Publishers.

Stevenson, M., & Spring, M. (2007). Flexibility from a supply chain perspective: definition and review. International Journal of Operations & Production Management, 27(7), 685-713. http://dx.doi.org/10.1108/01443570710756956.

Tao, F., Cheng, Y., Zhang, L., & Nee, A. (2017). Advanced manufacturing systems: socialization characteristics and trends. Journal of Intelligent Manufacturing, 28(5), 1079-1094. http://dx.doi.org/10.1007/s10845-015-1042-8.

Tracey, M., Vonderembse, M., & Lim, J. (1999). Manufacturing technology and strategy formulation: keys to enhancing competitiveness and improving performance. Journal of Operations Management, 17(4), 411-428. http://dx.doi.org/10.1016/S0272-6963(98)00045-X.

Tzeng, G., & Huang, C. (2012). Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing & logistics systems. Annals of Operations Research, 197(1), 159-190. http://dx.doi.org/10.1007/s10479-010-0829-4.

Vargas, L. (1982). Reciprocal matrices with random coefficients. Mathematical Modelling, 3(1), 69-81. http://dx.doi.org/10.1016/0270-0255(82)90013-6.

Voss, C., Tsikriktsis, N., & Frohlich, M. (2002). Case research in operations management. International Journal of Operations & Production Management, 22(2), 195-219. http://dx.doi.org/10.1108/01443570210414329.

Wabalickis, R. (1988). Justification of FMS with the analytic hierarchy process. Journal of Manufacturing Systems, 7(3), 175-182. http://dx.doi.org/10.1016/0278-6125(88)90002-7.

Wang, X., Wang, L., Mohammed, A., & Givehchi, M. (2017). Ubiquitous manufacturing system based on cloud: a robotics application. Robotics and Computer-integrated Manufacturing, 45(1), 116-125. http://dx.doi.org/10.1016/j.rcim.2016.01.007.

Ward, P., McCreery, J., Ritzman, L., & Sharma, D. (1998). Competitive priorities in operations management. Decision Sciences, 29(4), 1035-1046. http://dx.doi.org/10.1111/j.1540-5915.1998.tb00886.x.

Yamamoto, H., Yamada, T., & Tanaka, S. (2016). Moving robots lies and their minds with degree of confidence in a decentralized autonomous FMS. Journal of Robotics Networking and Artificial Life, 3(1), 61-64. http://dx.doi.org/10.2991/jrnal.2016.3.1.14.

Yazdani, M., Zarate, P., Coulibaly, A., & Zavadskas, E. (2017). A group decision making support system in logistics and supply chain management. Expert Systems with Applications, 88(1), 376-392. http://dx.doi.org/10.1016/j.eswa.2017.07.014.

Zavadskas, E., & Turskis, Z. (2011). Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 17(2), 397-427. http://dx.doi.org/10.3846/20294913.2011.593291.

Zhang, Q., Vonderembse, M., & Cao, M. (2009). Product concept and prototype flexibility in manufacturing: implications for customer satisfaction. European Journal of Operational Research, 194(1), 143-154. http://dx.doi.org/10.1016/j.ejor.2007.12.013.
 

5cec19810e8825a00ba63c11 production Articles
Links & Downloads

Production

Share this page
Page Sections