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This project
focuses on the development and implementation of a methodology
for the analysis and optimization of a distributed sensor
system in electronics assembly processes for the purpose of
process fault diagnosis. The proposed modeling tool will
integrate product quality information and process
characteristics in a multi-station assembly system framework
using a station-indexed state space model. Then, the
diagnosability of a generic distributed sensor system will be
explored by expending the concept of observability in control
theory. This will further lead to development of the fault
diagnosis method for fault feature extraction based on the
multivariate data analysis. The understanding of the
transformation of quality information, offered by the state
space quality-fault model and diagnosability analysis, will
guide the optimal design of a sensing system. This project
will be carried out through a close collaboration partnered by
he University of Wisconsin-Madison, Texas A&M University, and
Motorola Florida Research Labs (MFRL). The methodology
development will be based on, and the resulting technology
will be tested and implemented in, the Motorola radio assembly
process. If successful, the results of this project will
contribute to sensing and information technology in
manufacturing: new concepts and criteria regarding the
performance of sensor systems will be defined and effective
algorithms for sensing optimization and data analysis will be
developed. Details in
Poster. |
