Skip to main content
SpringerLink
Log in

An integrated framework of interpretive structural modeling and graph theory matrix approach to fix the agility index of an automobile manufacturing organization

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

Abstract

Free trade policies, globalization of the economy, and continuous changes in technology have increased competition among the manufacturers. Identification of customers’ changing needs and its simultaneous fulfillment becomes more important for manufacturers as well as suppliers. The needs for flexible, rapid, cost effective and high quality product development have led to the concept of agile manufacturing. In this paper, some important variables of the agile manufacturing system that leads the agility of the systems have been analyzed and interrelationship has been developed using interpretive structural modeling. Finally, the weightage for the existing relations have been assigned by the executives of the case company. The agility index of the case company has been determined with the help of graph theory matrix approach. This paper may help the manufacturers identify its agility and compare with the agility of competitors’ organizations.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Avittathur B, Swamidass P (2007) Matching plant flexibility and supplier flexibility: lesson from small suppliers of U.S. manufacturing plants in India. J Oper Manag 25(3):717–735

    Article  Google Scholar 

  • Belay AM, Helo P, Takala J, Kasie FM (2011) Effects of quality management practices and concurrent engineering in business performance. Int J Bus Manag 6(3):45–62

    Google Scholar 

  • Bouzon M, Govindan K, Rodriguez CMT (2015) Reverse logistics barriers: an analysis using interpretive structural modeling, enhancing synergies in a collaborative environment. Lect Notes Manag Ind Eng 3:95–103

    Article  Google Scholar 

  • Cho H, Jung MY, Kim M (1996) Enabling technologies of agile manufacturing and its related activities in Korea. Comput Ind Eng 30:323–334

    Article  Google Scholar 

  • Christian I, Ismail H, Mooney J, Snowden S, Toward M, Zhang D (2001) Agile manufacturing transitional strategies, manufacturing information systems. In: Proceedings of the fourth SME international conference, pp 1–9

  • Darvish M, Yasaei M, Saeedi A (2009) Application of the graph theory and matrix methods to contractor ranking. Int J Proj Manag 27:610–619

    Article  Google Scholar 

  • De Vor R, Mills J (1995) Agile manufacturing. American Society of mechanical engineers, manufacturing engineering division. MED 2(2):977

    Google Scholar 

  • Dove R (1999) Knowledge management, response ability and the agile enterprise. J Knowl Manag 3(1):1–17

    Article  Google Scholar 

  • Dove R, Nagel R, Goldman S, Preiss K (1991) 21st century manufacturing enterprise strategy: an industry led view. Iacocca Institute, Lehigh University, Bethlehem

    Google Scholar 

  • Fernandes R, Gouveia JB, Pinho C (2012) Product mix strategy and manufacturing flexibility. J Manuf Syst 31:301–311

    Article  Google Scholar 

  • Ferreira KA, Tomasb RN, Alcântara RLC (2014) A theoretical framework for postponement concept in a supply chain. Int J Logist. doi:10.1080/13675567.2014.945403

    Google Scholar 

  • Gianesi IGN (1998) Implementing manufacturing strategy through strategic production planning. Int J Oper Prod Manag 18(3):286–299

    Article  Google Scholar 

  • Govindan K, Azevedo SG, Carvalho H, Cruz-Machado V (2015) Lean, green and resilient practices influence on supply chain performance: interpretive structural modeling approach. Int J Environ Sci Technol 12(1):15–34

    Article  Google Scholar 

  • Graham JH, Ragade RK (1994) Design support system for agile manufacturing. In: Proceedings of the IEEE international conference on systems, man and cybernetics, vol 1. pp 512–517

  • 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(6):1357–1385

    Article  Google Scholar 

  • Gupta UG, Mittal RO (1996) Quality, time, and innovation based performance measurement system for agile manufacturing. In: Proceedings—annual meeting of the decision sciences institute, vol 3. pp 1511–1513

  • Gupta YP, Somers TM (1996) Business strategy, manufacturing flexibility, and organizational performance relationships: a path analysis approach. Prod Oper Manag 5(3):204–233

    Article  Google Scholar 

  • He DW, Kusiak A (1995) The delayed product differentiation strategy in agile manufacturing. In: IERC proceedings 1995, 4th annual industrial engineering research conference. Norcross, pp 701–708

  • He Y, Lai KK, Sun H, Chen Y (2014) The impact of supplier integration on customer integration and new product performance: the mediating role of manufacturing flexibility under trust theory. Int J Prod Econ 147:260–270

    Article  Google Scholar 

  • Kampen TV, Donk DPV (2014) Coping with product variety in the food processing industry: the effect of form postponement. Int J Prod Res 52(2):353–367

    Article  Google Scholar 

  • Kannan D, Diabat A, Shankar KM (2014) Analyzing the drivers of end-of-life tire management using interpretive structural modeling (ISM). Int J Adv Manuf Technol 72(9–12):1603–1614

    Article  Google Scholar 

  • Katayama H, Bennett D (1999) Agility, adaptability and leanness: a comparison of concepts and a study of practice. Int J Prod Econ 60:43–51

    Article  Google Scholar 

  • Krause DR, Handfield RB, Typer BB (2007) The relationships between supplier development social capital accumulation and performance improvement. J Oper Manag 25(2):528–545

    Article  Google Scholar 

  • Kumar A, Kumar P (2006) Role of rapid prototyping in agile manufacturing. In: Proceedings of RDFTME-2006, pp 258–264

  • Kumar P, Shankar R, Yadav SS (2007) Flexibility in global supply chain: a review of perspectives. In: Proceedings of seventh global conference on flexible system management (GLOGIFT-07), pp 377–385

  • Kumar P, Shankar R, Yadav SS (2007b) Flexibility in global supply chain: modeling the enablers. J Model Manag 3(3):277–297

    Article  Google Scholar 

  • Kumar P, Shankar R, Yadav SS (2008) Modeling the enablers of agile manufacturing system. In: Proceedings of eighth global conference on flexible systems management (GLOGIFT-08), NJ, USA, pp 1–8

  • Liu Y-J, Lai K-L, Dai G, Yuen MM-F (2010) A semantic feature model in concurrent engineering. IEEE Trans Autom Sci Eng 7(3):659–665

    Article  Google Scholar 

  • Malhotra V, Raj T, Arora A (2012) Evaluation of barriers affecting reconfigurable manufacturing systems with graph theory and matrix approach. Mater Manuf Process 27(1):88–94

    Article  Google Scholar 

  • Medhat SS, Rook JL (1997) Concurrent engineering—processes and techniques for the agile manufacturing enterprise. IIE Conference Publication, vol 435. pp 9–14

  • Muduli K, Govindan K, Barve A, Geng Y (2013) Barriers to green supply chain management in Indian mining industries: a graph theoretic approach. J Clean Prod 47:335–344

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Oke A (2013) Linking manufacturing flexibility to innovation performance in manufacturing plants. Int J Prod Econ 143:242–247

    Article  Google Scholar 

  • Palvia PC (1997) Developing a model of the global and strategic impact of information technology. Inf Manag 32(5):229–244

    Article  Google Scholar 

  • Powell TC, Dent-Micallef A (1997) Information technology as competitive advantage: the role of human, business and technology resources. Strateg Manag J 18(5):375–405

    Article  Google Scholar 

  • Sage AP (1977) Interpretive structural modeling: methodology for large-scale systems. McGraw-Hill, New York, pp 91–164

    Google Scholar 

  • Saghiri S, Hill A (2014) Supplier relationship impacts on postponement strategies. Int J Prod Res 52(7):2134–2153

    Article  Google Scholar 

  • Sethi V, King WR (1994) Development of measures to assess the extent to which an information technology application provides competitive advantage. Manag Sci 40(12):1601–1627

    Article  MATH  Google Scholar 

  • Sethi AK, Sethi SP (1990) Flexibility in manufacturing: a survey. Int J Flex Manuf Syst 2(4):289–328

    Article  Google Scholar 

  • Simchi-Levi D, Kaminsky P, Simchi-Levi E (2002) Designing and managing the supply chain: concepts, strategies and case studies, 2nd edn. Irwin/McGraw-Hill, New York

    MATH  Google Scholar 

  • Swafford PM, Ghosh S, Murthy N (2006) The antecedents of supply chain agility of a firm: scale development and model testing. J Oper Manag 24(2):170–188

    Article  Google Scholar 

  • Tan KC, Kannan VR, Handfield RB (1996) Supply chain management: supplier performance and firm performance. Int J Purch Mater Manag 34:2–9

    Google Scholar 

  • Wang F, Mill JJ, Devarajan V (2002) A conceptual approach for managing design resources. Comput Ind 47:169–183

    Article  Google Scholar 

  • Warfield JN (1974) Developing interconnection matrices in structural modeling. IEEE Trans Syst Man Cybern 4(1):81–87

    Article  MathSciNet  Google Scholar 

  • Yusuf YY, Sarhadi MS, Gunasekaran A (1999) Agile manufacturing: the drivers, concepts and attributes. Int J Prod Econ 62(1–2):23–32

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Delhi Technological University, Bawana Road, Delhi, 110042, India

    Pravin Kumar, Rajesh K. Singh & Rakesh Kumar

Authors
  1. Pravin Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rajesh K. Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rakesh Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pravin Kumar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, P., Singh, R.K. & Kumar, R. An integrated framework of interpretive structural modeling and graph theory matrix approach to fix the agility index of an automobile manufacturing organization. Int J Syst Assur Eng Manag 8 (Suppl 1), 342–352 (2017). https://doi.org/10.1007/s13198-015-0350-x

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-015-0350-x

Keywords

Search

Navigation