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Abstract

This paper explores the design of a water jet nozzle for cleaning the glass surface of a thin film transistor liquid crystal display. The theoretical background in this study is based on cavitation theory, main factors of cavitation, and bubble theory in determining the dominant design parameters (DPs) associated with nozzle design. From the bubble dynamics theory, three functional requirements (FRs) are extracted to maximize the cleaning effects in the context of axiomatic design. Based on the independence design axiom, the decoupled design matrix between FRs and DPs is developed. In this study, the sensitivity of the design matrix is evaluated via both design of experiments (DOEs) based analysis of means and back-propagation neural network-based causality analysis. Axiomatic design solutions are further compared with those obtained from a formal optimization method. This study shows that the axiomatic design with DOE is efficient since it does not require any mathematical formulation of design problem and its solution is easily obtained when the decoupled design matrix is quantitatively described.

Keywords

water jet nozzle bubble dynamics axiomatic design analysis of means,back-propagation neural network causality analysis

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Parameter design of water jet nozzle utilizing independence axiom

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