Utilizing Knowledge Based Mechanisms in Automated Feature Recognition Processes

Modern engineering design, analysis and manufacturing activities rely heavily on software to handle increasing volumes of data and model complexity. Automated Feature Recognition (AFR) technologies are highly demanded by manufacturing sectors since AFR can efficiently improve the performance of Computer-Aided Design (CAD) processes and reduce costs. Nevertheless, most existing FR applications are confronting various problems of processing CAD models in the manufacturing industry, such as aerospace and automobile industries. The missing link between CAD models and knowledge-based tools is one of the major obstacles. This research project investigates the feasibility and benefits of bridging the gap between knowledge based mechanisms and CAD models, and suggests a knowledge-based AFR approach for tackling AFR problems occurring in the computer-aid manufacturing design process. The AFR system significantly reduces time and costs of analysing CAD models for downstream design processes.