| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | March 15, 2013 |
| Latest Amendment Date: | January 23, 2015 |
| Award Number: | 1266225 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Diwakar Gupta
CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | July 1, 2013 |
| End Date: | September 30, 2016 (Estimated) |
| Total Intended Award Amount: | $142,223.00 |
| Total Awarded Amount to Date: | $147,223.00 |
| Funds Obligated to Date: |
FY 2015 = $0.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
701 S NEDDERMAN DR ARLINGTON TX US 76019-9800 (817)272-2105 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
500 West First Street Arlington TX US 76019-0170 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | MANFG ENTERPRISE SYSTEMS |
| Primary Program Source: |
01001516DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
The objective of this collaborative research is to develop a generic and systematic methodology for the modeling and control of quality profiles through the integration of advanced statistical techniques and expert knowledge of manufacturing processes. There is an increasingly common situation in industry practices where the quality of a process or product is characterized by a relationship between a response variable and an explanatory variable, called profiles. This research will build appropriate statistical models to characterize the effect of process parameters on the resulting quality profiles, and conduct process control, including spatial uniformity control and change detection, based on the process-profile models. A hierarchical modeling approach will be used in building the models, and advanced Bayesian approaches will be developed for model estimation and change detection. Expert knowledge of the process will be incorporated in the methodology development. The proposed approaches will be validated using degradation profiles in tissue-engineered scaffold fabrication processes.
The results of this research will fill the gap in the state-of-art manufacturing by providing a scientific base and a coherent set of quality engineering tools for quality profiles. A unique contribution of this work is the characterization of the effect of process parameters on quality profiles, which will establish a foundation for process design, monitoring and optimization based on quality profiles. Moreover, the application of the results in the control of degradation profiles in tissue-engineered scaffold fabrication will make it possible to produce tissue-engineered scaffold products that satisfy different requirements for human uses, and thus overcome critical barriers in developing engineered tissues/organs such as bone, liver, blood vessel, and heart valve to meet the vast need for tissue grafts in our nation.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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