Design Optimization and Sensitivity Analysis of Manufacturing Errors for LED Edge-lit Integrated Light Guide Plates

碩士 === 國立高雄第一科技大學 === 機械與自動化工程所 === 98 === This study applies a novel fabrication process of molding stamper that combines anisotropic wet etching of silicon-on-insulator (SOI) wafers with electroforming for the molding of non-printed light guides. Because the geometry of the fabricated feature of S...

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Bibliographic Details
Main Authors: Shao-Tang Zhang, 張簡少棠
Other Authors: Jyh-Cheng Yu
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/95606244008332607968
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Summary:碩士 === 國立高雄第一科技大學 === 機械與自動化工程所 === 98 === This study applies a novel fabrication process of molding stamper that combines anisotropic wet etching of silicon-on-insulator (SOI) wafers with electroforming for the molding of non-printed light guides. Because the geometry of the fabricated feature of SOI using anisotropic wet etching is defined by [111] crystal planes and the etch stop, micro truncated pyramids with high dimensional accuracy and surface characteristics can be fabricated. The truncated square pyramidal features are orientated 45?a to the light of travel by mask design, which in combination with the 90° prisms on the light inlet surface of the LED edge-lit LGP provides an enhanced axial luminance intensity which is similar to the use of conventional two orthogonal prism sheets. A light tracing program, TracePro is applied to simulate the light intensity, illuminance, and luminance for a distribution of micro features. LGP is divided into smaller regions. The feature spacing of each region is adjusted by a fuzzy optimization scheme. A sinusoidal modulation of feature distribution is also introduced the fuzzy theory for optimal adjustment parameters according to simulated result. We analyze the sensitivities of the optical properties to possible manufacturing errors such as the dimensions of the micro features and the thickness of LGP.A modified distribution pattern is proposed according to the experiment result. The optimum result after fuzzy optimization search provides LGP design with much improved uniformity.