Knowledge-based program generation approach for robotic manufacturing systems

In recent decades, robotic manufacturing systems have been considered as effective solutions for providing more productive processes, but with less cost and risk. However, the programming is a time-consuming task, hinders implementation of in today's industry. This paper proposes knowledge-based program-generation approach systems. The proposed provides support standardization rules knowledge related to programs that proven successful previous cases; this can not only increase efficiency, also improve stability production quality. First, an ontological model developed provide explicit semantic description relevant concepts system, basic instruction units program, product models workpieces. Second, rule-based reasoning mechanism established infer implicit relationships between program. Finally, based on descriptions model, program are instantiated data extracted from integrated according inferred by mechanism, thereby generating