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.
