SEMANTIC METHODS TOWARDS ADAPTIVE PRODUCT DEVELOPMENT ENVIRONMENTS
Paul Witherell and Sudarsan Rachuri
When addressing the ever-evolving needs of knowledge management in product development, ontologies and logical inferencing can serve as a basis for “intelligent” knowledge frameworks. Within these ontological frameworks, information interdependencies can occur due to domain interactions. These interdependencies, representing engineering relationships, provide a way to semi-automatically corroborate information. In earlier research, an aggregate semantic relatedness measure was developed for quantifying domain interactions between product development information models. Resulting quantifications provided a basis for focused efforts when manually identifying important engineering relationships.
Leveraging previous works in semantic relatedness, methods will be developed to enable “intelligent” knowledge frameworks to self-adapt to changes in knowledge structures. Semantic relatedness measures can be applied to identify newly created interdependencies. Towards the necessary categorization of interdependencies, a bottom-up approach will be taken when identifying domain interactions. A sustainable manufacturing domain model serves as an opportune environment for identifying and categorizing specific engineering relationships to later be abstracted. With new regulations such as REACH requiring unprecedented accountability, new methods are needed to capture, share, and track sustainable-related information during product development.