International Journal of Advanced and Applied Sciences
Int. j. adv. appl. sci.
Print ISSN: 2313-626X
Volume 4, Issue 8 (August 2017), Pages: 104-111
Title: What derives lean manufacturing effectiveness: An interpretive structural model
Author(s): TanChing NG 1, *, Morteza Ghobakhloo 2
1Department of Mechanical and Material Engineering, Universiti Tunku Abdul Rahman, Selangor, Malaysia
2Department of Management and Economics, Tarbiat Modares University, Tehran, Iran
Full Text - PDF XML
This research aims to model the processes through which manufacturing firms can increase the effectiveness of lean manufacturing practices. To achieve its objective this research benefits from the interactive structural modelling technique to first capture the opinions of lean experts and further map the interrelationships between determents of lean manufacturing effectiveness. Findings revealed that employees empowerment, employees involvement, implementation cost, teamwork, managerial leadership and support, awareness of latest lean information and information technology are key determinants of lean manufacturing effectiveness. Findings explain that the precedence relationships between the determining factors identified, and the order of their implementation is crucial to the achievement of highest degrees of lean manufacturing effectiveness. Utility of the proposed interpretive structural modelling methodology imposing order, direction and significance of the relationships among elements of lean manufacturing effectiveness are expected to offer considerable value to the decision makers and lean practitioners.
© 2017 The Authors. Published by IASE.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Lean manufacturing, Effectiveness, ISM
Article History: Received 17 April 2017, Received in revised form 13 July 2017, Accepted 14 July 2017
Digital Object Identifier:
NG T and Ghobakhloo M (2017). What derives lean manufacturing effectiveness: An interpretive structural model. International Journal of Advanced and Applied Sciences, 4(8): 104-111
- Al-Aomar R (2011). Handling multi-lean measures with simulation and simulated annealing. Journal of the Franklin Institute, 348(7): 1506-1522. https://doi.org/10.1016/j.jfranklin.2010.05.002
- Anand G and Kodali R (2009). Simulation model for the design of lean manufacturing systems-a case study. International Journal of Productivity and Quality Management, 4(5-6): 691-714 https://doi.org/10.1504/IJPQM.2009.025192
- Attri R, Dev N, and Sharma V (2013). Interpretive structural modelling (ISM) approach: An overview. Research Journal of Management Sciences, 2(2): 3-8.
- Busch J (2010). Did Toyota's lean supply chain go bad? Available online at: http://spendmatters.com/2010/03/25/did-toyotas-lean-supply-chain-go-bad/
- Dev KN, Shankar R, and Kumar Dey P (2014). Reconfiguration of supply chain network: An ISM-based roadmap to performance. Benchmarking: An International Journal, 21(3): 386-411.
- Fliedner G and Majeske K (2010). Sustainability: the new lean frontier. Production and Inventory Management Journal, 46(1): 6-13.
- Govindan K, Palaniappan M, Zhu Q, and Kannan D (2012). Analysis of third party reverse logistics provider using interpretive structural modeling. International Journal of Production Economics, 140(1): 204-211. https://doi.org/10.1016/j.ijpe.2012.01.043
- Holweg M (2007). The genealogy of lean production. Journal of Operations Management, 25(2): 420-437. https://doi.org/10.1016/j.jom.2006.04.001
- Kannan G and Haq AN (2007). Analysis of interactions of criteria and sub-criteria for the selection of supplier in the built-in-order supply chain environment. International Journal of Production Research, 45(17): 3831-3852. https://doi.org/10.1080/00207540600676676
- Kannan VR and Choon Tan K (2006). Buyer-supplier relationships: The impact of supplier selection and buyer-supplier engagement on relationship and firm performance. International Journal of Physical Distribution and Logistics Management, 36(10): 755-775. https://doi.org/10.1108/09600030610714580
- Lapinski AR, Horman MJ, and Riley DR (2006). Lean processes for sustainable project delivery. Journal of Construction Engineering and Management, 132(10): 1083-1091. https://doi.org/10.1061/(ASCE)0733-9364(2006)132:10(1083)
- Luthra S, Garg D, and Haleem A (2014). Green supply chain management: Implementation and performance–a literature review and some issues. Journal of Advances in Management Research, 11(1): 20-46. https://doi.org/10.1108/JAMR-07-2012-0027
- Luthra S, Kumar V, Kumar S, and Haleem A (2011). Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique: An Indian perspective. Journal of Industrial Engineering and Management, 4(2): 231-257. https://doi.org/10.3926/jiem.2011.v4n2.p231-257
- Moyano-Fuentes J, Sacristán-Díaz M, and José Martínez-Jurado P (2012). Cooperation in the supply chain and lean production adoption: Evidence from the Spanish automotive industry. International Journal of Operations and Production Management, 32(9): 1075-1096. https://doi.org/10.1108/01443571211265701
- Nordin N, Deros BM, and Wahab DA (2010). A survey on lean manufacturing implementation in Malaysian automotive industry. International Journal of Innovation, Management and Technology, 1(4): 374-380.
- Pfohl HC, Gallus P, and Thomas D (2011). Interpretive structural modeling of supply chain risks. International Journal of Physical Distribution and Logistics Management, 41(9): 839-859. https://doi.org/10.1108/09600031111175816
- Poduval PS and Pramod VR (2015). Interpretive Structural Modeling (ISM) and its application in analyzing factors inhibiting implementation of Total Productive Maintenance (TPM). International Journal of Quality and Reliability Management, 32(3): 308-331. https://doi.org/10.1108/IJQRM-06-2013-0090
- Ravi V and Shankar R (2005). Analysis of interactions among the barriers of reverse logistics. Technological Forecasting and Social Change, 72(8): 1011-1029. https://doi.org/10.1016/j.techfore.2004.07.002
- Sage AP (1997). Interpreting Structural Modeling: Methodology for large scale systems. McGraw-Hill, New York, USA.
- Shah R and Ward PT (2003). Lean manufacturing: context, practice bundles, and performance. Journal of Operations Management, 21(2): 129-149. https://doi.org/10.1016/S0272-6963(02)00108-0
- Shah R and Ward PT (2007). Defining and developing measures of lean production. Journal of Operations Management, 25(4): 785-805. https://doi.org/10.1016/j.jom.2007.01.019
- Warfield JN (1974). Developing subsystem matrices in structural modeling. IEEE Transactions on Systems, Man and Cybernetics, 4(1): 74-80. https://doi.org/10.1109/TSMC.1974.5408523
- Womack JP and Jones DT (2010). Lean thinking: banish waste and create wealth in your corporation. Simon and Schuster, New York, USA.
- Womack JP, Jones DT, and Roos D (1990). Machine that changed the world. Simon and Schuster, New York, USA.
- Wong YC and Wong KY (2011). Approaches and practices of lean manufacturing: The case of electrical and electronics companies. African Journal of Business Management, 5(6): 2164-2174.
- Yang MGM, Hong P, and Modi SB (2011). Impact of lean manufacturing and environmental management on business performance: An empirical study of manufacturing firms. International Journal of Production Economics, 129(2): 251-261. https://doi.org/10.1016/j.ijpe.2010.10.017