Currently, computer-based support tools are widely used to facilitate the design process and have the potential to reduce design time, decrease product cost and enhance product quality. PDM (Product Data Management) and PLM (Product Lifecycle Management) are two types of computer-based information systems that have been developed to manage product lifecycle and product related data. While promising, significant limitations still exist, where information required to make decisions may not be available, may be lacking consistency, and may not be expressed in a general way for sharing among systems. Moreover, it is difficult for designers to consider multiple complex technical and economical criteria, relations, and objectives in product design simultaneously. In recent years, ontology-based method is a new and promising approach to manage knowledge in engineering, integrate multiple data resources, and facilitate the consideration of the complex relations among concepts and slots in decision making. The purpose of this research is to explore an ontology-based method to solve the limitations in present computer-based information systems for product design. The field of Design for Manufacturing (DFM) is selected for this study, and three primary aspects are investigated. First, a generalized DFM ontology is proposed and developed. The ontology fulfills the mathematical and logical constraints needed in DFM, as well as ontology editor capabilities to support the continuous improvement of the ontology. Second, the means to guide users to the proper information and integrate heterogeneous data resources is investigated. Third, based on the ontology and information integration, a decision support tool is developed to help designers consider the design problem in a systematic way and make design decisions efficiently based on accurate and comprehensive data. The methods and tools developed in this research are refined using example cases provided by the CFSP (The NSF Center for Friction Stir Processing). This includes cost models and a decision support environment. Errors that may occur in the research are categorized with management methods. An error ontology is built to help root cause analysis of errors and further reduce possible errors in the ontology and decision support tool. An evaluation methodology for the research is also investigated.

Ph. D.