Abstract
The presence of a number of available non-traditional machining (NTM) processes has brought out the idea of selecting the most suitable NTM process for generating a desired shape feature on a given work material. This paper presents a digraph-based approach to ease out the appropriate NTM process selection problem. It includes the design and development of an expert system that can automate this decision-making process with the help of graphical user interface and visual aids. The proposed approach employs the use of pair-wise comparison matrices to calculate the relative importance of different attributes affecting the NTM process selection decision. Based on the characteristics and capabilities of the available NTM processes to machine the required shape feature on a given work material, the permanent values of the matrices related to those processes are computed. Finally, if some of the NTM processes satisfy a certain threshold value, those are shortlisted as the acceptable processes for the given shape feature and work material combination. The digraph-based expert system not only segregates the accepted NTM processes from the list of the available processes but also ranks them in decreasing order of preference. It also helps the user as a responsible guide to select the most suitable NTM process by incorporating all the possible error trapping mechanisms. This paper takes into account some new work materials, shape features and NTM processes that have not been considered by the earlier researchers. It is further observed that the developed expert system is quite flexible and versatile as the results of the cited examples totally corroborate with those obtained by the past researchers.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Jain VK (2005) Advanced machining processes. Allied, New Delhi
Pandey PC, Shan HS (1981) Modern machining processes. Tata McGraw-Hill, New Delhi
Cogun C (1993) Computer-aided system for selection of nontraditional machining operations. Comput Ind 22(2):169–179. doi:10.1016/0166-3615(93)90063-7
Cogun C (1994) Computer aided preliminary selection of non-traditional machining processes. Int J Mach Tools Manuf 34:315–326. doi:10.1016/0890-6955(94)90002-7
Yurdakul M, Cogun C (2003) Development of a multi-attribute selection procedure for non-traditional machining processes. Proc IMechE J Eng Manuf 217:993–1009
Chakroborty S, Dey S (2006) Design of an analytic-hierarchy-process-based expert system for non-traditional machining process selection. Int J Adv Manuf Technol 31(5–6):490–500. doi:10.1007/s00170-005-0216-5
Chakroborty S, Dey S (2007) QFD-based expert system for non-traditional machining processes selection. Expert Syst Appl 32(4):1208–1217. doi:10.1016/j.eswa.2006.02.010
McGeough JA (1988) Advanced methods of machining. Chapman and Hall, London
Rao VR, Gandhi OP (2002) Digraph and matrix methods for the machinability evaluation of work materials. Int J Mach Tools Manuf 42(3):321–330. doi:10.1016/S0890-6955(01)00133-X
Rao VR, Gandhi OP (2002) Failure cause analysis of machine tools using digraph and matrix methods. Int J Mach Tools Manuf 42(4):521–528. doi:10.1016/S0890-6955(01)00135-3
Rao VR, Padmanabhan KK (2006) Selection, identification and comparison of industrial robots using digraph and matrix methods. Robot Comput-Integr Manuf 22(4):373–383. doi:10.1016/j.rcim.2005.08.003
Rao VR (2006) A material selection model using graph theory and matrix methods. Mater Sci Eng A 431(1–2):248–255. doi:10.1016/j.msea.2006.06.006
Rao VR (2006) A decision-making framework model for evaluating flexible manufacturing systems using digraph and matrix methods. Int J Adv Manuf Technol 30(11–12):1101–1110. doi:10.1007/s00170-005-0150-6
Rao VR, Padmanabhan KK (2007) Rapid prototyping process selection using graph theory and matrix approach. J Mater Process Technol 194:81–88. doi:10.1016/j.jmatprotec.2007.04.003
Rao VR (2006) Selection of a non-traditional machining process using digraph and matrix method. In: Proceedings of the 1st International and 22nd AIMTDR Conference, IIT, Roorkee, 21–23 December 2006, pp 979–983
Jense JB, Gutin G (2000) Digraph theory, algorithms and applications. Springer, London
Rao VR (2007) Decision making in the manufacturing environment using graph theory and fuzzy multiple attribute decision making methods. Springer, London
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chakladar, N.D., Das, R. & Chakraborty, S. A digraph-based expert system for non-traditional machining processes selection. Int J Adv Manuf Technol 43, 226–237 (2009). https://doi.org/10.1007/s00170-008-1713-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-008-1713-0