Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Evaluating key performance indicators of leagile manufacturing using fuzzy TISM approach

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

Leagile manufacturing strategy has emerged as one of the important strategy adopted by most of manufacturing organizations now a days. It has advantages of both lean as well as agile manufacturing system. Lean manufacturing tries to eliminate all different types of wastages like overproduction, inventory, unnecessary motion etc., while agile manufacturing focus on changing the production system as per the requirements of the customer and provide customized products within short span of time. Lean manufacturing focuses on no inventory and try to implement Just in Time methodology but for the system to be agile, there should be at least some inventory in store so that production can be started as soon as customer order is achieved. In this paper, key performance indicators (KPI) of leagile manufacturing are found by literature review and in consultation of experts and academicians working in the concerned field. Fuzzy TISM approach has been applied to find levels of different KPI’S. MICMAC analysis has been made to analyze the KPI’S and categorize them as autonomous, dependent, linkage, independent etc. on the basis of driving and dependence power. Finally, digraph is drawn to show relationship between various KPI’s.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Agarda B, Bassetto S (2013) Modular design of product families for quality and cost. Int J Prod Res 51(6):1648–1667

    Article  Google Scholar 

  • Agarwal A, Shankar R, Tiwari MK (2006) Modelling agility of supply chain. Ind Mark Manag 36(4):443–457

    Article  Google Scholar 

  • Agarwal A, Shankar R, Tiwari M (2007) Modeling agility of supply chain. Ind Mark Manag 36(4):443–457

    Article  Google Scholar 

  • Anand G, Kodali R (2010) Analysis of lean manufacturing frameworks. J Adv Manuf Syst 9(1):1–30

    Article  Google Scholar 

  • Anvari A, Norzima Z, Rosnay M, Hojjati M, Ismail Y (2010) A comparative study on journey of lean manufacturing implementation. AIJSTPME 3:77–85

    Google Scholar 

  • Borissova A, Fairweather M, Goltz GE (2006) Combinatorial process and plant design for agile manufacture. Res Eng Des 17(1):1–12

    Article  Google Scholar 

  • Bortolotti T, Boscari S, Danese P (2014) Successful lean implementation: organizational culture and soft lean practices. Int J Prod Econ 160:182–201

    Article  Google Scholar 

  • Chavez R, Gimenez C, Fynes B, Wiengarten F, Yu W (2013) Internal lean practices and operational performance: the contingency perspective of industry clock speed. Int J Oper Prod Manag 33(5):562–588

    Article  Google Scholar 

  • Christopher M, Towill D (2000) Supply chain migration from lean and functional to agile and customized. Supply Chain Manag 5(4):206–213

    Article  Google Scholar 

  • Devadasan SR, Goshteeswaran S, Gokulachandran J (2005) Design for quality in agile manufacturing environment through modified orthogonal array-based experimentation. J Manuf Technol Manag 16(6):576–597

    Article  Google Scholar 

  • Dubey R, Ali SS (2014) Identification of flexible manufacturing system dimensions and their interrelationship using total interpretive structural modeling and fuzzy MICMAC analysis. Glob J Flex Syst Manag 15(2):131–143

    Article  Google Scholar 

  • Eroglu C, Hoffer C (2011) Lean, leaner, too lean? The inventory performance link revised. J Oper Manag 29(4):356–369

    Article  Google Scholar 

  • Fan Z, Liu Y (2010) A method for group decision-making based on multi-granularity uncertain linguistic information. Expert Syst Appl 37(5):4000–4008

    Article  Google Scholar 

  • Gothwal S, Raj T (2016) Analyzing the factors affecting the flexibility in FMS using weighted interpretive structural modeling (WISM) approach. Int J Syst Assur Eng Manag 8(2):408–422

    Article  Google Scholar 

  • Gunasekaran A (1998) Agile manufacturing: enablers and an implementation framework. Int J Prod Res 36(5):1223–1247

    Article  MATH  Google Scholar 

  • Gunasekaran A, Yusuf YY (2002) Agile manufacturing: a taxonomy of strategic and technological imperatives. Int J Prod Res 40(3):1357–1385

    Article  Google Scholar 

  • Haleem A, Sushil (2012) Analysis of critical success factors of world-class manufacturing practices: an application of interpretative structural modelling and interpretative ranking process. Prod Plan Control 23(10–11):722–734

    Article  Google Scholar 

  • Jain V, Raj T (2013) Ranking of flexibility in flexible manufacturing system by using a combined multiple attribute decision making method. Global J Flexible Syst Manag 14(3):125–141

    Article  Google Scholar 

  • Jayaram J, Vickery S, Droge C (2008) Relationship building, lean strategy and firm performance: an exploratory study in the automotive supplier industry. Int J Prod Econ 46(20):5633–5649

    Article  MATH  Google Scholar 

  • Jharkharia S, Shankar R (2005) IT-enablement of supply chains: understanding the barriers. J Enterp Inf Manag 18(1):11–27

    Article  Google Scholar 

  • Khatwani G, Singh SP, Trivedi A, Chauhan A (2015) Fuzzy TISM: a fuzzy extension of TISM for group decision making. Glob J Flex Syst Manag 16(1):97–112

    Article  Google Scholar 

  • Krafcik J (1988) Triumph of the lean production system. Sloan Manag Rev 30:41–52

    Google Scholar 

  • Krishnamurthy R, Yauch CA (2007) Leagile manufacturing: a proposed corporate infrastructure. Int J Prod Opeartions Manag 27(6):588–604

    Article  Google Scholar 

  • Mangla SK, Kumar P, Barua MK (2014) Flexible decision approach for analyzing performance of sustainable supply chains under risks/uncertainty. Glob J Flex Syst Manag 15(2):113–130

    Article  Google Scholar 

  • Mason Jones R, Naylor R, Towill DR (2000) Engineering the leagile supply chain. Int J Agile Manuf Syst 2(1):54–61

    Article  Google Scholar 

  • Meredith S, Francis D (2000) Journey towards agility: the agile wheel explored. TQM Mag 12(2):137–143

    Article  Google Scholar 

  • Mohager A, Karbasian S (2014) A grey-based approach for integration of lean and agile supply chain. Int J Bus Manag Econ 1(1):40–48

    Google Scholar 

  • Nasim S (2011) Total interpretive structural modeling of continuity and change forces in e-government. J Enterp Transf 1(2):147–168

    Google Scholar 

  • Naylor JB, Naim MM, Berry D (1999) Leaglity: integrating the lean and agile manufacturing paradigm in the total supply chain. Int J Prod Econ 62:107–118

    Article  Google Scholar 

  • Panwar A, Nepal BP, Jain R, Rathore APS (2015) On the adoption of lean manufacturing principles in process industries. Prod Plan Control 26(7):564–587

    Article  Google Scholar 

  • Powell D, Alfnes E, Strandhagen JO, Dreyer H (2013) The concurrent application of lean production and ERP: towards an ERP-based lean implementation process. Comput Ind 64:324–335

    Article  Google Scholar 

  • Prasad U, Suri R (2011) Modeling of continuity and change forces in private higher technical education using total interpretive structural modeling (TISM). Glob J Flex Syst Manag 12(3–4):31–40

    Article  Google Scholar 

  • Sarkis J (2001) Benchmarking for agility. Benchmarking 8(2):88–107

    Article  Google Scholar 

  • Shah R, Ward PT (2003) Lean manufacturing: context, practice bundles, and performance. J Oper Manag 21(5):129–149

    Article  Google Scholar 

  • Shah R, Ward PT (2007) Defining and developing measures of lean production. J Oper Manag 25:785–805

    Article  Google Scholar 

  • Sharifi H, Colquhoun G, Barclay I (2001) Agile manufacturing: a management and operational framework. Proc Inst Mech Eng 215:857–869

    Article  Google Scholar 

  • Sharma HD, Gupta AD, Sushil (1995) The objectives of waste management in India: a future inquiry. Technol Forecast Soc Change 48(3):285–309

    Article  Google Scholar 

  • Swink M, Narasimhan R, Kim SW (2005) Manufacturing practices and strategy integration:effects on cost efficiency, flexibility, and market-based performance. Decis Sci 36(3):427–457

    Article  Google Scholar 

  • Talib F, Rahman Z, Qureshi MN (2011) An interpretive structural modelling approach for modeling the practices of total quality management in service sector. Int J Model Oper Manag 1(3):223–250

    Google Scholar 

  • Trkman P, McCormack K (2009) Supply chain risk turbulent environments-A conceptual model for managing supply chain network risk. Int J Prod Econ 119(2):247–258

    Article  Google Scholar 

  • Vinodh S, Aravindraj S (2012) Agility evaluation using the IF–THEN approach. Int J Prod Res 50(24):7100–7109

    Article  Google Scholar 

  • Womack J, Jones D (2003) Lean thinking: banish waste and create wealth in your corporation. London Press, London

    Google Scholar 

  • Womack JP, Jones DT, Roos D (1991) The machine that changed the world: how Japan’s secret weapon in the global auto wars will revolutionize western industr, 1st edn. Harper Perennial, New York

    Google Scholar 

  • Yadav N, Kumar S (2013) Total interpretive structural modelling (TISM) of strategic performance management for Indian telecom service providers. Int J Prod Perform Manag 63(4):421–445

    Article  Google Scholar 

  • Yadav OP, Nepal BP, Rahaman MM, Lal V (2017) Lean implementation and organizational transformation: a literature review. Eng Manag J 29(1):2–16

    Article  Google Scholar 

  • Yang MGM, Hong P, Modi BS (2011) Impact of lean manufacturing and environmental management on business performance: an empirical study of manufacturing firms. Int J Prod Econ 129:251–261

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Naveen Virmani.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Virmani, N., Saha, R. & Sahai, R. Evaluating key performance indicators of leagile manufacturing using fuzzy TISM approach. Int J Syst Assur Eng Manag 9, 427–439 (2018). https://doi.org/10.1007/s13198-017-0687-4

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-017-0687-4

Keywords

Navigation