NDLI: Application of genetic algorithm and Taguchi method in dynamic robust parameter design for unknown problems

Content Provider	Springer Nature Link
Author	Chatsirirungruang, Pisvimol
Copyright Year	2009
Abstract	Taguchi method was known in many industries as an off-line quality control methodology to improve the performance of products or processes at low cost. Although it was effective at improving quality, the statisticians pointed to inefficiencies in the method for highly nonlinear problems and complexity of the product design, the results were often less than satisfactory. Therefore, recently mathematical model and computer simulation are the other alternatives for robust design. However, Taguchi method and computer simulation have their own advantages and disadvantages. So, this idea motivates the approach of combining both advantages together to promote the more effectiveness of robust design. This paper proposes the approach to apply computer-aided engineering (CAE) with genetic algorithm (GA) and Taguchi method in dynamic robust parameter design. Firstly, we use computer simulation, CAE, to obtain the data instead of conducting whole real experiment. Next, a statistical approach, linear regression is used to model the unknown functions, and then GA, heuristics search approach, is employed to find the appropriate setting of controllable factors on the basis of the quality loss function. The effect of noise factors which is the important philosophy of robust design is also considered by utilizing the outer orthogonal array. The objective is to minimize the average quality loss instead of maximizing SN ratio. In addition, to enhance the capability of the proposed approach, the two-step method is applied to screen out the dispersion factors significantly affecting the quality variation and the adjustment factors significantly affecting the sensitivity of the Taguchi’s dynamic system for the case of changing products or processes’ requirements in the future. This proposed is applied to the example “Foam design of automobile’s dashboard”.
Starting Page	993
Ending Page	1002
Page Count	10
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	47
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2009-08-19
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Robust parameter design Computer-aided engineering Genetic algorithm Quality engineering Two-step method Foam design of automobile’s dashboard Computer-Aided Engineering (CAD, CAE) and Design Mechanical Engineering Production/Logistics Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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