Abstract
Current industrial practice in automated manufacturing operations relies on low fidelity data transmission methods between computer numerical control (CNC) machine tools and the computer-aided manufacturing (CAM) systems used to program them. The typical language used to program CNC machines, known as G-Code, has been in existence for nearly sixty years and offers limited resolution for command data. In addition, the proprietary nature of industrial CNC systems hampers the ability of manufacturers to expand and improve upon the capability of existing machine tools. G-Code was not designed to support transmission of feedback data, and thus both the CAM system and higher level organizational control systems are frequently blind to the state of the production process; in response, separate standards that enable data exchange with machine tools have been used by industry, such as MTConnect and Open Platform Communications Unified Architecture (OPC UA). However, these standards enable data pathways that are independent of the G-Code command data pathway, and thus provide practically no means to affect the state of a process on receipt of feedback data. As a result, control and data acquisition exist in separate realms, which makes the implementation of self-optimizing smart CNC systems challenging. This state-of-the-art review surveys existing methods for data transmission to and from machine tools and explores the current state of so-called integrated CAM/CNC systems that enable more thorough control of the machining process using intelligence built in to the CAM system. The literature survey reveals that integrated CAM/CNC systems are impeded both by the data exchange methods used to interface with CNC systems in addition to the proprietary and closed architecture of the CNC systems themselves. Future directions in integrated CAM/CNC research are identified based on the requirements identified for such systems.
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