SUMMARY

Methods to connect manufacturing machines, processes, and sensors have rapidly developed through the fourth industrial revolution, known as Industry 4.0. Digital manufacturing technologies can be applied to computer numerical control (CNC) manufacturing processes to measure and improve component quality. This body of research evaluates the strategic combination and synchronization of information from multiple sensing modalities to improve the accuracy of digital twin models. A voxel modelling methodology is developed and investigated to create a digital twin of the component being produced. Information describing the machine’s current operations is strategically combined with information from additional sensing modalities to increase the accuracy of the in-situ digital twin model. This work results in (1) a method to geometrically compare features of in-situ components from multiple sensing modalities against desired specifications, (2) a multi-agent architecture to support efficient communication, storage, and use of this information, resulting in (3) feedback methodologies for commercial CNC systems to affect the in-situ manufacturing process and correct geometric deviations. Zoom Link: https://us02web.zoom.us/j/82553546888?pwd=V3lmbTEwdk90SW1MeTl1bUY0d0N3dz09