Computer-based information systems have become the nerve center of current manufacturing systems. Engineering information modeling in databases is thus essential. However, information imprecision and uncertainty extensively arise in engineering design and manufacturing. So contemporary engineering applications have put a requirement on imprecise and uncertain information modeling. Viewed from database systems, engineering information modeling can be identified at two levels: conceptual data modeling and logical database modeling and correspondingly we have conceptual data models and logical database models, respectively. In this paper, we first investigate information imprecision and uncertainty in engineering applications. Then EXPRESS-G, which is a graphical modeling tool of EXPRESS for conceptual data modeling of engineering information, and nested relational databases are extended based on possibility distribution theory, respectively, in order to model imprecise and uncertain engineering information. The formal methods to mapping fuzzy EXPRESS-G schema to fuzzy relational schema are developed.
Assessment of query execution performance using selected Business Intelligence tools and experimental agile oriented data modeling approach
