Skip to main content
SpringerLink
Log in

Selection of a Flexible Machining Centre Through a Knowledge Based Expert System

  • Original Article
  • Published:
Global Journal of Flexible Systems Management Aims and scope Submit manuscript

Abstract

A key task in the flexible manufacturing system (FMS) design is the selection and configuration of machining centers for machining and processing in time. Machining centre selection is a complex and tedious task. However, there are few tools other than checklists to assist engineers in the selection of appropriate, cost-effective manufacturing machining centers. This paper describes the development of an intelligent machining centre selection system called knowledge based flexible machining centre selection (kbFMC). The kbFMC is composed of three modules: a database to store machining centres; a knowledgebase for assisting machining centre selection; and an inference engine to choose the most appropriate machining centre type. The expert system approach proposed in this paper is expected to automate the machining centre selection process and serve as a decision making tool in design of a FMS.

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

Similar content being viewed by others

References

  • Balachandra, R. (2000). An expert system for new product development projects. Industrial Management and Data Systems, 100(7), 317–324.

    Article  Google Scholar 

  • Chan, F. T. S. (2002). Design of material handling equipment selection system: An integration of expert system with analytic hierarchy process approach. Integrated Manufacturing Systems, 13(1), 58–68.

    Article  Google Scholar 

  • Chowdary, B. V. (2001). Flexibility and related issues in evaluation and selection of technological systems. Global Journal of Flexible Systems Management, 2(2), 11–20.

    Google Scholar 

  • Chowdary, B. V. (2007). Back-propagation artificial neural network approach for machining centre selection. Journal of Manufacturing Technology Management, 18(3), 315–332.

    Article  Google Scholar 

  • Chowdary, B. V., & Kanda, A. (2003). A decision support system for flexibility in manufacturing. Global Journal of Flexible Systems Management, 4(3), 1–14.

    Google Scholar 

  • Kodali, R. (1997). Knowledgebased system for selection of cutting tool to be used in real-time control (on-line scheduling) of FMS. Industrial Engineering Journal, XXVI(7), 4–16.

    Google Scholar 

  • Kunnathur, A. S., Sundararaghavan, P. S., & Sampath, S. (2004). Dynamic rescheduling using a simulation-based expert system. Journal of Manufacturing Technology Management, 15(2), 199–212.

    Article  Google Scholar 

  • Maksoud, T. M. A., Atia, M. R., & Koura, M. M. (2003). Applications of artificial intelligence to grinding operations via neural networks. Machining Science and Technology: An International Journal, 7(3), 361–387.

    Article  Google Scholar 

  • Masmoudi, W., Chtourou, H., & Maalej, A. Y. (2006). A simulation-expert-system-based approach for machine sizing of production systems. Journal of Manufacturing Technology Management, 17(2), 187–198.

    Article  Google Scholar 

  • Mehdi, K., & Zghal, A. (2005). A hybrid system for component selection experience with bearing selection. International Journal of Vehicle Design, 39(1/2), 80–92.

    Article  Google Scholar 

  • Min, H. (2010). Artificial intelligence in supply chain management: Theory and applications. International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management, 13(1), 13–39.

    Article  Google Scholar 

  • Peter, K. (1990). Machining centres. Machinery and Production Engineering, 148, 81–90.

    Google Scholar 

  • Preci-Tech Information Reports. (2009). Indian Machine Tool Manufacturers’ Association, Vol. 23, No. 1, April–June 2009.

  • Sanders, D., Tan, Y. C., Rogers, I., & Tewkesbury, G. E. (2009). An expert system for automatic design-for-assembly. Assembly Automation, 29(4), 378–388.

    Article  Google Scholar 

  • Shivathaya, S. S., & Fang, X. D. (1993). Expert scheduling system for tool room operations. International Journal of Computer Integrated Manufacturing, 8(4), 247–254.

    Article  Google Scholar 

  • St-Pierre, J., & Delisle, S. (2006). An expert diagnosis system for the benchmarking of SMEs’ performance. Benchmarking: An International Journal, 13(1/2), 106–119.

    Article  Google Scholar 

  • Sushil, (1993). Systems dynamics and methodology—A practical approach for managerial problems. New Delhi: Wiley Eastern Limited.

    Google Scholar 

  • Unahabhokha, C., Platts, K., & Tan, K. H. (2007). Predictive performance measurement system: A fuzzy expert system approach. Benchmarking: An International Journal, 14(1), 77–91.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical and Manufacturing Engineering, The University of the West Indies, St. Augustine, Trinidad and Tobago

    Boppana V. Chowdary

  2. Sciquest Inc., 18 Campus Boulvevard, Newtown Square, PA, 19073, USA

    Srinivasarao Muthineni

Authors
  1. Boppana V. Chowdary
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Srinivasarao Muthineni
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Boppana V. Chowdary.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 11 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chowdary, B.V., Muthineni, S. Selection of a Flexible Machining Centre Through a Knowledge Based Expert System. Glob J Flex Syst Manag 13, 3–10 (2012). https://doi.org/10.1007/s40171-012-0001-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40171-012-0001-x

Keywords

Search

Navigation