Search

The development of computer, internet and information technology puts forward higher demands for Computer Numerical Control (CNC) machine tools to improve the intelligence in many aspects. Among these aspects, intelligent process planning plays an important role in current changeable market and customized product promotion by shortening production cycle and providing more stable process planning ability. To realize intelligent process planning, a CNC controller with cloud knowledge base support is proposed with ability of making process planning autonomously based on workpiece design. Previous work of knowledge model and cloud knowledge base framework design is introduced, and then this paper focuses on the complete process planning method within the intelligent CNC controller. Both interactivity between knowledge base and CNC controller, and query/infer mechanism in knowledge base are illustrated in detail. A case study of two shafts process planning is shown to demonstrate the feasibility of the intelligent process planning method. [ABSTRACT FROM AUTHOR]

CNC machine tool plays a vital role in intelligent manufacturing, but up to now, CNC controller, which works as the "brain" of the machine tool, is just a loyal executor of machining command without intelligence. This paper is aimed to improve the intelligence of CNC controller from the aspect of machining process planning, which has a great effect on product quality and production efficiency. A STEP-compliant data model is adopted. Compared to previous STEP-NC controller, this paper presents a new paradigm to integrate the ability of autonomous process planning into CNC controller based on cloud knowledge base. A hierarchical and modular architecture is designed to obtain machining process planning from cloud knowledge base timely and to conduct the machining implementation on shop floor. Furthermore, efficient and matching operation mechanism is researched. It offers a proposal to use cloud knowledge to implement intelligent manufacturing. Finally, a case study is demonstrated to verify the feasibility of this intelligent CNC controller. [ABSTRACT FROM AUTHOR]