Application of Taguchi Method with Fuzzy Logic to Determine the Optimal Parameters of Spray-Painting Process

Virojana Tantibadaro

Authors

Virojana Tantibadaro Faculty of Engineering and Technology, Punyapiwat Institute of Management, Nonthaburi, Thailand

Keywords:

Spray painting, Multiple Quality Characteristics, Taguchi Method, Fuzzy Logic, Multi- Quality Characteristic Index

Abstract

The spray painting process exhibits a high level of variation in terms of process settings, which represents a very important issue for quality control of a painting job. Parameters involving in the painting process include the paint viscosity, paint flow rate, gun air pressure, gun-to-surface distance, and the number of coats. The parameters can be determined based on multiple quality characteristics in terms of the difference in paint thickness from the target value as well as on the surface roughness; these two characteristics must indeed be concurrently evaluated. The purpose of the present research was to determine the optimal spray painting process parameters to improve the quality of a painting job via the application of the Taguchi method and fuzzy logic. L₈ orthogonal array, signal-to-noise ratio, multi-quality characteristic index and analysis of variance were used to evaluate the quality characteristics of the painting process. The key performance indicator was the multi-quality characteristic index whose higher value indicates higher quality characteristics of the painting process. The experimental results revealed that the paint flow rate and gun-to-surface distance were the significant parameters affecting the multiple quality characteristics, with the paint flow rate seemed to be the most significant. A confirmation test was then conducted; the results showed that the difference in the paint thickness from the target value as well as the surface roughness could be simultaneously considered and improved through the approach introduced in this article.

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