Towards an Intelligent Digital Machine Twin for CAM Process Optimization

The Computer-Aided Manufacturing (CAM) programming process for bus floor component production encounters significant challenges due to dependence on two-dimensional designs and the lack of 3D visualization, which restricts the programmer’s ability to thoroughly assess the parts. This often results in issues such as missing features, production oversights, or dimensional discrepancies, which require manual verification against physical components and reduce efficiency, while errors during the machining process can further complicate production and impact overall quality. To address these issues, our research introduces the development of an intelligent digital machine twin (IDMT) to assist CAM programmers in both Design for Manufacturability (DfM) and production setup. The proposed solution integrates detailed manufacturing data with virtual simulations of the machining process, built upon NC Code, utilizing AI methodologies to optimize the production of new components, provide feedback, and take corrective action to prevent errors throughout the manufacturing operations.