Six sigma-based approach to optimize deep drawing operation variables

被引:25
作者
Anand, Raj Bardhan
Shukla, Sanjay Kumar
Ghorpade, Amol
Tiwari, M. K. [1 ]
Shankar, Ravi
机构
[1] Natl Inst Foundry & Forge Technol, Dept Forge Technol, Ranchi 834003, Bihar, India
[2] Univ Cincinnati, Dept Mech Ind & Nucl Engn, Comp Aided Mfg Lab, Cincinnati, OH 45221 USA
[3] Natl Inst Foundry & Forge Technol, Dept Mfg Engn, Ranchi 834003, Bihar, India
[4] Indian Inst Technol, Dept Management Studies, New Delhi 110016, India
关键词
deep drawing; six sigma; DMAIC; ANOVA; RSM;
D O I
10.1080/00207540600702308
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:2365 / 2385
页数:21
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