Leanness assessment of automobile industry using fuzzy based integrated approach
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Abstract
The manufacturing industries are converting their production systems from mass to lean manufacturing. The lean techniques were described by the elimination of waste occurring during manufacturing, thereby moving towards a reduction in overall cost. The quantification of leanness is one of the contemporary research agendas of lean manufacturing. The main goal of this paper was to propose a scale for the measurement of the degree of leanness for an industry using fuzzy based approach. The data was collected from the Indian automobile industry. The Tukey’s honestly significant difference test was implemented for verification of the final outcome. The final outcome demonstrated that value stream mapping came out to be the most significant lean manufacturing technique. It was also noticed that supplier partnership and 5S systems were found to have the least influence on the overall leanness index of automobile industry, which was facing low production issues and wanted to enhance their overall performance.
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References
Ali, M. N., Mahmoud, K., Lehtonen, M., and Darwish, M. M. F. (2021a). An efficient fuzzy-logic based variable-step incremental conductance MPPT method for grid-connected PV systems. IEEE Access, 9, 26420-26430.
Ali, M. N., Mahmoud, K., Lehtonen, M., and Darwish, M. M. F. (2021b). Promising MPPT methods combining metaheuristic, fuzzy-logic and ANN techniques for grid-connected photovoltaic. Sensors, 21(4), 1244.
Baykasoğlu, A., Kaplanoğlu, V., DurmuşOğlu, Z. D. U., and Şahin, C. (2013). Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection. Expert Systems with Applications, 40(3), 899-907.
Büyüközkan, G., and Çifçi, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 39(3), 3000-3011.
Dabestani, R., Baerz, A. M., Azar, A., and Shahin, A. (2017). Proposing a model for evaluating lean project management performance using grounded theory. International Journal of Productivity and Quality Management, 22(4), 521-535.
Dai, B., and Chen, H. (2012). Mathematical model and solution approach for carriers’ collaborative transportation planning in less than truckload transportation. International Journal of Advanced Operations Management, 4(1-2), 62-84.
Dalalah, D., Hayajneh, M., and Batieha, F. (2011). A fuzzy multi-criteria decision making model for supplier selection. Expert Systems with Applications, 38(7), 8384-8391.
Elsisi, M., Tran, M. Q., Mahmoud, K., Mansour, D. E. A., Lehtonen, M., and Darwish, M. M. F. (2021a). Towards secured online monitoring for digitalized GIS against cyber-attacks based on IoT and machine learning. IEEE Access, 9, 78415-78427.
Elsisi, M., Tran, M. Q., Mahmoud, K., Lehtonen, M., and Darwish, M. M. F. (2021b). Deep learning-based industry 4.0 and internet of things towards effective energy management for smart buildings. Sensors, 21(4), 1038.
Kumar, N., Mathiyazhagan, K., and Mathivathanan, D. (2020). Modelling the interrelationship between factors for adoption of sustainable lean manufacturing: A business case from the Indian automobile industry. International Journal of Sustainable Engineering, 13(2), 93-107.
McDonald, T., Van Aken, E. M., and Rentes, A. F. (2002). Utilising simulation to enhance value stream mapping: A manufacturing case application. International Journal of Logistics, 5(2), 213-232.
Mumani, A. A., Magableh, G. M., and Mistarihi, M. Z. (2022). Decision making process in lean assessment and implementation: A review. Management Review Quarterly, 72, 1089-1128.
Rother, M., and Shook, J. (2003). Learning to See: Value Stream Mapping to Add Value and Eliminate MUDA, Boston, MA: The Lean Enterprise Institute, pp. 144-173.
Shahin, A., and Alinavaz, M. (2008). Integrative approaches and frameworks of lean Six Sigma: A literature perspective. International Journal of Process Management and Benchmarking, 2(4), 323-337.
Shahin, A., and Jaberi, R. (2011). Designing an integrative model of leagile production and analyzing its influence on the quality of auto parts based on Six Sigma approach with a case study in a manufacturing company. International Journal of Lean Six Sigma, 2(3), 215-240.
Shahin, A., and Rezaei, M. (2018). An integrated approach for prioritizing lean and agile production factors based on costs of quality with a case study in the home appliance industry. Benchmarking: An International Journal, 25(2), 660-676.
Shahin, A., Malekzadeh, N., and Wood, L. C. (2021). Developing a decision making grid for selecting innovation strategies - the case of knowledge-based companies. Technology Analysis & Strategic Management, 1-17.
Sharma, P., and Singhal, S. (2017). Implementation of fuzzy TOPSIS methodology in selection of procedural approach for facility layout planning. The International Journal of Advanced Manufacturing Technology, 88, 1485-1493.
Silvério, L., Trabasso, L. G., and Pessôa, M. V. P. (2020). Performance measurement and improvement of lean manufacturing operations: A leanness assessment literature review for the product development industry. IOP Conference Series: Materials Science and Engineering, 859, 012017.
Tran, M. Q., Elsisi, M., Mahmoud, K., Liu, M. K., Lehtonen, M., and Darwish, M. M. F. (2021). Experimental setup for online fault diagnosis of induction machines via promising IoT and machine learning: Towards industry 4.0 empowerment. IEEE Access, 9, 115429-115441.
Vimal, K. E. K., and Vinodh, S. (2013). Application of artificial neural network for fuzzy logic based leanness assessment. Journal of Manufacturing Technology Management, 24(2), 274-292.
Vinodh, S., and Balaji, S. R. (2011). Fuzzy logic based leanness assessment and its decision support system. International Journal of Production Research, 49(13), 4027-4041.
Womack, J. P., Jones, D. T., and Roos, D. (1990). The Machine That Changed the World, New York: Simon & Schuster, pp. 273-287.
Womack, J. P., and Jones, D. T. (1997). Lean thinking-banish waste and create wealth in your corporation. Journal of the Operational Research Society, 48(11), 1148.
Yadav, V., Khandelwal, G., Jain, R., and Mittal, M. L. (2019). Development of leanness index for SMEs. International Journal of Lean Six Sigma, 10(1), 397-410.
Zahraee, S. M, (2016). A survey on lean manufacturing implementation in a selected manufacturing industry in Iran. International Journal of Lean Six Sigma, 7(2), 136-148.
Zahraee, S. M, Tolooie, A., Abrishami, S. J., Shiwakoti, N., and Stasinopoulos, P. (2020). Lean manufacturing analysis of a heater industry based on value stream mapping and computer simulation. Procedia Manufacturing, 51, 1379-1386.
Zahraee, S. M., Esrafilian, R., Kardan, R., Shiwakoti, N., and Stasinopoulos, P. (2021). Lean construction analysis of concrete pouring process using value stream mapping and Arena based simulation model. Materials Today: Proceedings, 42(2), 1279-1286.