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Improving the electromagnetic compatibility of electronic products by using response surface methodology and artificial neural network

Ching-Hsiang Chen (Department of Industrial Management, Tungnan University, Shenkeng, Taiwan)
Chien-Yi Huang (Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan)
Yan-Ci Huang (Quality Control Division, SYSTEX Corporation, Taipei, Taiwan)

Microelectronics International

ISSN: 1356-5362

Article publication date: 3 November 2021

Issue publication date: 3 January 2022

148

Abstract

Purpose

The purpose of this study is to use the Taguchi Method for parametric design in the early stages of product development. electromagnetic compatibility (EMC) issues can be considered in the early stages of product design to reduce counter-measure components, product cost and labor consumption increases due to a number of design changes in the R&D cycle and to accelerate the R&D process.

Design/methodology/approach

The three EMC characteristics, including radiated emission, conducted emission and fast transient impulse immunity of power, are considered response values; control factors are determined with respect to the relevant parameters for printed circuit board and mechanical design of the product and peripheral devices used in conjunction with the product are considered as noise factors. The optimal parameter set is determined by using the principal component gray relational analysis in conjunction with both response surface methodology and artificial neural network.

Findings

Market specifications and cost of components are considered to propose an optimal parameter design set with the number of grounded screw holes being 14, the size of the shell heat dissipation holes being 3 mm and the arrangement angle of shell heat dissipation holes being 45 degrees, to dispose of 390 O filters on the noise source.

Originality/value

The optimal parameter set can improve EMC effectively to accommodate the design specifications required by customers and pass test regulations.

Keywords

Citation

Chen, C.-H., Huang, C.-Y. and Huang, Y.-C. (2022), "Improving the electromagnetic compatibility of electronic products by using response surface methodology and artificial neural network", Microelectronics International, Vol. 39 No. 1, pp. 1-13. https://doi.org/10.1108/MI-06-2021-0052

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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