Modeling: Product and production system decomposition and analysis using the concepts of product/process key characteristics, their relationship and causalities

Design: Application of the developed models towards:  (i) manufacturing system design evaluation and optimization/synthesis in early design phases; and (ii) distributed sensing system/network optimization. Information and models developed are further applied to study reusable/reconfigurable multistage manufacturing systems convertibility, scalability and diagnosability.

Manufacturing:  Application of the developed models towards: (i) root cause diagnosis of manufacturing variability by integrating models of data sets with efficient CAD/CAM models of manufacturing systems instead of identifying model(s) of data set alone as in the traditional Statistical Process Control (SPC); and, ( ii) manufacturing system diagnosability.

Field Life: The objective of the research is to develop and implement a generic Data-driven Design-Service Lifecycle methodology for analysis, diagnosis and control of product field performance by integrating field data (service and warranty) with manufacturing measurements and design information. Such integration will address the following needs: (1) Service: Methodology for monitoring, diagnosis and prediction of product field failures based on in-situ event measurements; (2) Warranty: Methodology for diagnosis and control of warranty based on manufacturing and field information; and (3) Feedback-to-Design: Model developed in (1) & (2) identifies interactions which cause the failure which will be used as feedback-to-design to improve product robustness.