Optimal coordinate sensor placements for estimating mean and variance components of variation sources

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Title: Optimal coordinate sensor placements for estimating mean and variance components of variation sources
Author: Liu, Qinyan
Abstract: In -process Optical Coordinate Measuring Machine (OCMM ) offers the potential of diagnosing in a timely manner variation sources that are responsible for product quality defects . Such a sensor system can help manufacturers improve product quality and reduce process downtime . Effective use of sensory data in diagnosing variation sources depends on the optimal design of a sensor system , which is often known as the problem of sensor placements . This thesis addresses coordinate sensor placement in diagnosing dimensional variation sources in assembly processes . Sensitivity indices of detecting process mean and variance components are defined as the design criteria and are derived in terms of process layout and sensor deployment information . Exchange algorithms , originally developed in the research of optimal experiment deign , are employed and revised to maximize the detection sensitivity . A sort -and -cut procedure is used , which remarkably improve the algorithm efficiency of the current exchange routine . The resulting optimal sensor layouts and its implications are illustrated in the specific context of a panel assembly process .
URI: http : / /hdl .handle .net /1969 .1 /2238
Date: 2005-08-29

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Optimal coordinate sensor placements for estimating mean and variance components of variation sources. Available electronically from http : / /hdl .handle .net /1969 .1 /2238 .

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