One of these problems is a shortage of knowledgeable experienced manufacturing engineers who can actually generate the code for the CNC machines in the most optimized manner to maximize profitability. This is due to an aging workforce and a lack of experienced engineers. The logical solution is to capture the current knowledge and to automate the output. This is where CAM software with knowledge-based machining can provide a solution. Engineers can identify best processes and lock them in.
Knowledge-Based Machining and Automatic Feature Recognition.

Knowledge-based machining (KBM) represents an effort among CAM developers to automate and streamline CNC programming to produce more consistent and accurate programs and to make CNC programmers more productive. Many of these CAM systems are feature-based and provide automatic feature recognition (AFR)—an automated method that analyzes the solid model geometry and identifies regions to be machined.

For example, AFR can define features such as pockets, bosses, holes and slots for milling operations. For turning operations, features such as the OD and ID of the part, front face and grooves can be defined automatically. Semi-automatic methods also are provided for features that are not found by AFR. This combination of automatic and semi-automatic feature definition eliminates the time-consuming process of manually identifying regions to be machined.

Once machinable features have been identified, KBM technology can associate the machining processes, tooling and cutting conditions to the features. Typically, a database stores the machining information. This database can be customized to represent your company’s current machining best practices. For example, you may stock specific tools in your tool crib or you may have an older machine that requires special considerations or you may have a specific way to machine holes. Once you have set up the database for your processes and requirements, it’s locked in and incremental improvements can be made to that baseline.

The net result of feature recognition and KBM is automation that increases productivity and provides a shorter time-to-market. Repetitive programming tasks are automated easing overworked and understaffed CNC programming departments. Tooling and methodology are more consistent and reliable from programmer to programmer and from job to job. Job costs can be substantially reduced.