Artificial Neural Network and the Taguchi Method Application for Optimum Ultrasonic Welding Process Design

Abstract

In quality engineering, and in most experimental design cases, understanding the relationship between design factors and product or process performance is essential for improving quality. Because most manufacturing conditions are so complicated, a large number of experiments are generally required Taguchi's approach can systematically reduce the number of experiments required. But in certain case, where interaction exist between design factors, the level average analysis will not select optimum condition. To overcome this weakness after orthogonal array experiments are performed, an artificial neural network is used to select the optimum conditions instead of traditional level average analysis Actual application, ultrasonic plastic welding process design, proved that this approach can select real optimum point both within and between factor levels.

Department(s)

Civil, Architectural and Environmental Engineering

Second Department

Engineering Management and Systems Engineering

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 The Authors, All rights reserved.

Publication Date

01 Dec 1996

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