Skip to main content

A matrix-based framework for assessing machine tool reconfiguration alternatives


Reconfigurable manufacturing machines are designed to allow manufacturers to readily adapt to changing circumstances. This adds a new dimension to the process-planning problem, as the machine structure is not constant. A comprehensive set of reconfiguration management assessment tools and methods must be introduced to assist in developing the most appropriate process change strategies for a given set of circumstances based on the machine structures, control capabilities, and the skill levels and availability of shop personnel. Therefore, the goal of this research is to develop methods to assess the machine configuration/reconfiguration compatibility characteristics for alternative process strategies. The methods must be adaptable to suit a variety of environments and present results that are readily understood by all actors. Systematic, matrix-based techniques for assessing product and process complexity are introduced as well as a methodology to assess the suitability for CNC machine tool configurations with respect to a process plan, which considers the candidate machines’ physical and functional characteristics to determine its suitability. The resulting candidate machines are subsequently assessed to consider the process transition complexity issues utilizing an extension of a manufacturing complexity analysis framework used to evaluate product and process complexity. Case studies are presented to illustrate the merits of the proposed methodology.

This is a preview of subscription content, access via your institution.


  1. 1.

    Urbanic RJ, Hedrick RW, ElMaraghy WH (2008) A process transition complexity assessment tool for managing reconfigurable machine tools. Proceedings of the 5th International Conference on Digital Enterprise Technology in Nantes, paper 74

  2. 2.

    Feldman K, Slama S (2001) Highly flexible assembly—scope and justification. Ann CIRP 50(2):489–498

    Article  Google Scholar 

  3. 3.

    Renzi C, Leali F, Cavazzuti M, Andrisano AO (2014) A review on artificial intelligence applications to the optimal design of dedicated and reconfigurable manufacturing systems. Int J Adv Manuf Technol 72(1–4):403–418

    Article  Google Scholar 

  4. 4.

    Koren Y, Heisel U, Jovane F, Moriwaki T, Pritschow G, Ulsoy G, Van Brussel H (1999) Reconfigurable manufacturing systems. Ann CIRP 48(2):527–540

    Article  Google Scholar 

  5. 5.

    Wiendahl H-P, Heger CL (2004) Justifying changeability: a methodical approach to achieving cost effectiveness. Int J Manuf Sci Prod 6(1,2):33–39

    Google Scholar 

  6. 6.

    Nakase N, Yamada T, Matsui M (2002) A management design approach to a simple flexible assembly system. Int J Prod Econ 76(3):281–292

    Article  Google Scholar 

  7. 7.

    Tolio T, Terkaj A, Valente A (2007) Focused flexibility and production system evaluation, 2nd International Conference on Changeable, Agile, Reonfigurable and Virtual Production: 17–41

  8. 8.

    ElMaraghy HA (2005) Flexible and reconfigurable manufacturing systems paradigms. Int J Flex Manuf Syst Spec Issue Reconfig Manuf Syst 17:261–276

    Article  Google Scholar 

  9. 9.

    Carlo HJ, Spicer JP, Rivera-Silva A (2012) Simultaneous consideration of scalable-reconfigurable manufacturing system investment and operating costs. J Manuf Sci Eng 134(1):011003–011003

    Article  Google Scholar 

  10. 10.

    Flowers M, Kai C (2011) Reconfiguration as a responsive tool for the agile-centric global manufacturing complexity domain. Int J Internet Manuf Serv 3(1):1–15

    Google Scholar 

  11. 11.

    Chen L, Xi F, Macwan A (2005) Optimal module selection for preliminary design of reconfigurable machine tools. J Manuf Sci Eng 127(1):104–115

    Article  Google Scholar 

  12. 12.

    Goyal K, Jain P, Jain M (2013) A novel methodology to measure the responsiveness of RMTs in reconfigurable manufacturing system. J Manuf Syst 32(4):724–730

    Article  Google Scholar 

  13. 13.

    Goyal K, Jain P, Jain M (2012) Optimal configuration selection for reconfigurable manufacturing system using NSGA II and TOPSIS. Int J Prod Res 50(15):4175–4191

    Article  Google Scholar 

  14. 14.

    Wiendahl H-P, Scholtissek P (1994) Management and control of complexity in manufacturing. Ann CIRP 43(2):533–540

    Article  Google Scholar 

  15. 15.

    Anosike A, Zhang D (2006) Dynamic reconfiguration and simulation of manufacturing systems using agents. J Manuf Technol Manag 17(4):435–447

    Article  Google Scholar 

  16. 16.

    Kuhnle H (2001) A state-time model to measure the reconfigurability of manufacturing areas-key to performance. Integr Manuf Syst 12(17):493–499

    Article  Google Scholar 

  17. 17.

    Lee G (1997) Reconfigurability consideration design of components and manufacturing systems. Int J Adv Manuf Technol (IJAMT) 13:376–386

    Article  Google Scholar 

  18. 18.

    LaVie D (2006) Capability reconfiguration: an analysis of incumbent responses to technological change. Acad Manag Rev 31(1):153–174

    Article  Google Scholar 

  19. 19.

    Bruccoleri M, Pasek Z, Koren Y (2006) Operation management in reconfigurable manufacturing systems: reconfiguration for error handling. Int J Prod Econ 100:87–100

    Article  Google Scholar 

  20. 20.

    Abdi M, Labib A (2003) A design strategy for reconfigurable manufacturing systems (RMSs) using analytical hierarchical process (AHP): a case study. Int J Prod Res 41(10):2273–2279

    Article  Google Scholar 

  21. 21.

    Du J, Jiao Y, Jiao Y (2006) A real-option approach to flexibility planning in reconfigurable manufacturing systems. Int J Adv Manuf Technol 28:1202–1210

    Article  Google Scholar 

  22. 22.

    Katz R (2007) Design principles of reconfigurable machines. Int J Adv Manuf Technol 34:430–439

    Article  Google Scholar 

  23. 23.

    Youssef A, ElMaraghy HA (2006) Assessment of manufacturing systems reconfiguration smoothness. Int J Adv Manuf Technol (IJAMT) 30:174–193

    Article  Google Scholar 

  24. 24.

    Kim Y (1999) A system complexity approach for the integration of product development and production system design. MSc., MIT, USA

    Google Scholar 

  25. 25.

    Frizelle G (1996) Getting the measure of complexity. Manuf Eng 1996:268–270

    Google Scholar 

  26. 26.

    Sarkis J (1996) An empirical analysis of productivity and complexity for flexible manufacturing systems. Int J Prod Econ 48:39–48

    Article  Google Scholar 

  27. 27.

    Cooper W, Sinha K, Sullivan R (1992) Measuring complexity in high technology manufacturing: indexes for evaluation. Interfaces 4(22):38–48

    Article  Google Scholar 

  28. 28.

    Guenov M (2005) Complexity and cost effectiveness measures for systems design, 2nd International Conference of the Manufacturing Complexity Network: 455–466

  29. 29.

    Deshmukh A, Talavage J, Barash M (1998) Complexity in manufacturing systems, part 1: analysis of static complexity. IIE Trans 30:645–655

    Google Scholar 

  30. 30.

    Windt K, Philipp T, Böse F (2007) Complexity cube for the characterization of complex production systems. Int J Comput Integr Manuf 21(2):195–200

    Article  Google Scholar 

  31. 31.

    Calinescu A, Efstathiou J, Schirn J, Bermejo J (1998) Applying and assessing two methods for measuring complexity in manufacturing. J Oper Res Soc 49(7):723–733

    Article  MATH  Google Scholar 

  32. 32.

    ElMaraghy WH, Urbanic RJ (2003) Modelling of manufacturing systems complexity. Ann CIRP 52(1):363–366

    Article  Google Scholar 

  33. 33.

    ElMaraghy WH, Urbanic RJU (2004) Assessment of manufacturing operational complexity. Ann CIRP 53(1):401–406

    Article  Google Scholar 

  34. 34.

    ElMaraghy HA, Kuzgunkaya O, Urbanic RJ (2005) Manufacturing systems configuration complexity. Ann CIRP 54(1):261–276

    Article  Google Scholar 

  35. 35.

    Hedrick RW, Urbanic RJ (2009) Managing change and reconfigurations of CNC machine tools. In: H. ElMaraghy (Ed) Changeable and reconfigurable manufacturing systems changeable and reconfigurable manufacturing systems. Springer-Verlag: 285–300

  36. 36.

    Çimren E, Çatay B, Budak E (2007) Development of a machine tool selection system using AHP. Int J Adv Manuf Technol 35:363–376

    Article  Google Scholar 

  37. 37.

    Bayazit O (2004) Use of AHP in decision-making for flexible manufacturing systems. J Manuf Technol Manag 16(7):808–819

    Article  Google Scholar 

  38. 38.

    Hedrick RW, Urbanic RJ, ElMaraghy HA (2004) Multi-tasking machine tools and their impact on process planning. Proceeding of the CIRP Design Conference, CD ROM

Download references

Author information



Corresponding authors

Correspondence to R. J. Urbanic or R. W. Hedrick.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Urbanic, R.J., Hedrick, R.W. A matrix-based framework for assessing machine tool reconfiguration alternatives. Int J Adv Manuf Technol 81, 1893–1919 (2015).

Download citation


  • Reconfiguration management
  • Change management
  • Process planning
  • Complexity
  • CNC machines