Project #1
Monitoring and Diagnosis of Surface Defects of Hot Rolling Processes
Source: SME Education Foundation
PI/PD: S. Zhou
Duration: 06/2003 - 07/2004
Abstract:
Hot rolling is among the key manufacturing processes that
convert cast or semi-finished steel into finished products. The surface
integrity is an extremely important quality characteristic of the hot rolled products.
The proposed project focuses on the monitoring and diagnosis of surface defects in hot
rolling process. The basic approach is to apply advanced image processing and statistical
analysis to the hot surface images collected in real-time by using an innovative imaging
system. Unlike other quality assurance techniques, the proposed methodology can quickly
detect the process abnormal change.
Project #2
Modeling, Analysis, and Control of Variation Propagation in Manufacturing Processes
Source: NSF
PI/PD: S. Zhou
Duration: 09/2003 - 08/2006
Abstract:
This grant provides funding for the development of a
methodology for modeling, analysis, and control of variation propagation
in complicated manufacturing processes. A quantitative variation propagation
model will be developed. Both analytical and empirical methods based on product/process
design and engineering knowledge are used to link the key process variation sources
and key product quality characteristics in this model. This quantitative model allows
system theory and advanced statistical techniques (e.g., variance component analysis
of linear mixed models) to be adopted in quality and productivity improvement.
Project #3
Sensors and Sensor Networks: Design, Fabrication and Application of Distributed Micro Sensors Embedded in Metal Tooling
Source: NSF
PI/PD: Li
Co-PI: Zhou, Jiang
Duration: 08/2003 - 07/2006
Abstract:
The objective of this award is to develop a sensing methodology
that enables highly reliable and accurate monitoring and diagnosis for manufacturing
processes. This proposed research is to use a system approach to study the design,
fabrication, optimization, assessment, and applications of distributed micro sensors
embedded in metal tooling that is fabricated by Rapid Tooling manufacturing processes.
The challenging issues involve the embeding process, the control and improvement of
the embeding process, and huge dataset processing for both process and sensor failure diagnosis.
Project #4
Stream-of-Variation Analysis System for Multistage Assembly Processes
Source: NIST-ATP
PI/PD: D. Ceglarek
Co-PI: S. Zhou
Duration: 10/2003 - 11/2006
Abstract:
This project is to develop a widely applicable computer
simulation system for modeling, analyzing, predicting, and optimizing
the performance of multistage manufacturing processes requiring accurate parts
alignment to improve production and product quality. ATP aims at bridging
the gap between research labs, technology and business, and awards are made
strictly on the basis of peer-reviewed competitions.
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