Six sigma-based approach to optimize deep drawing operation variables

Anand, Raj Bardhan ; Shukla, Sanjay Kumar ; Ghorpade, Amol ; Tiwari, M. K. ; Shankar, Ravi (2007) Six sigma-based approach to optimize deep drawing operation variables International Journal of Production Research, 45 (10). pp. 2365-2385. ISSN 0020-7543

Full text not available from this repository.

Official URL: https://doi.org/10.1080/00207540600702308

Related URL: http://dx.doi.org/10.1080/00207540600702308

Abstract

The six sigma approach has been increasingly adopted worldwide in the manufacturing sector in order to enhance the productivity and quality performance and to make the process robust to quality variations. This paper deals with one such application of six sigma methodology to improve the yield of deep drawing operations. The deep drawing operation has found extensive application in producing automotive components and many household items. The main issue of concern of the deep drawn products involves different critical process parameters and governing responses, which influences the yield of the operation. The effects of these parameters are analysed by the DMAIC (Define, Measurement, Analyse, Improve, Control)-based six sigma approach. A multiple response optimization model is formulated using the fuzzy-rule-based system. The functional relationship between the process variables and the responses is established, and thereafter their optimum setting is explored with the aid of response surface methodology (RSM). Rigorous experimentations have been carried out, and it is observed that the process capability of processes is enhanced significantly, after the successful deployment of the six sigma methodology.

Item Type:Article
Source:Copyright of this article belongs to Informa UK Limited.
Keywords:Deep drawing; Six sigma; DMAIC; ANOVA; RSM.
ID Code:139651
Deposited On:27 Aug 2025 11:22
Last Modified:27 Aug 2025 11:22

Repository Staff Only: item control page