CYBER-SECURITY ASSURANCE
Smart Hybrid Machine Tool Platform
Enabling smart manufacturing through interfacing, connectivity and streaming process data collection and storage
The Smart hybrid Machine tool along with the abilities provided by the Data Acquisition and the CAD/CAM Interface allows for material discovery through autonomous experimentation.
Real time sensor fusion and data curation has been achieved. It is important to have access to real time data from all the sensors on board in order to be able to make sense out of the data. The goal has been achieved by using NI LabView extensively, integrating it with the tools available in OSISoft PI System and the NI DAQ.
Integrating the on board controller to be able to perform data analytics, without compromising security. In this case SIEMENS Sinumeric 828D has been integrated to achieve the goal.
Scale of Implementation
The Smart Hybrid Machining tool at Texas A&M University has an ability to simultaneously perform additive in the form of directed energy deposition (DED) 3D printing, heat treatment, and subtractive manufacturing in form of machining (milling and turning) and polishing for industry-grade surface finish, saving crucial time spent on setup, transport, and inspection of a manufactured product. The machine tool can print a large portfolio of alloys from combining alloy powders and depositing them under different process conditions.
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Smart hybrid machine tool is integrated with multiple sensors and imaging instruments (chiefly, a high-speed camera, IR camera, dynamometer, accelerometers, and an acoustic emission sensor) to characterize and monitor the multi-material directed energy deposition (DED) based AM, as well as the subsequent machining and surface finishing processes. A novel sensor wrapper scheme is devised to assure monitoring of the key thermo-mechanical state variables during the material deposition and phase transformation stages of the DED process and the subsequent heat treatment, as well as in situ testing of the resulting microstructure, all within a single machine platform.
Close control of heat input also helps with creating a near-net microstructure along with controlling the shape, material composition, and surface morphology. The sensor wrapper can also synchronize the signals and video streams to with 0.1 msec, and associate force signal pattern to a specific location of the workpiece to within 10 µm, vibrations to within 0.5 µm, AE < 0.1 µm resolution. Subsequently, a diamond grinding pin is employed to finish the surface to Sa < 1µm. The final step of the process chain uses wool felt polishing pad to create a near-mirror finish with Ra ~ 10 nm.
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The above figure illustrates the capabilities of the hybrid machine tool to realize a polished surface from a printed surface in the same setup.
References
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Transformation of discrete part manufacturing industries to sm platform - Bhaskar Botcha
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https://www.sciencedirect.com/science/article/pii/S2213846319300951 - Ashif Sikandar Iquebal