In-situ sensing and monitoring of metal additive manufacturing processes
Metal additive manufacturing (AM) has a great potential for the development of innovative industrial applications in different domains, e.g., aerospace, bio-medical, tooling and moulding, and automotive. Indeed, it enables the production of complex shapes, topologically optimized structures and high-value-added components with novel embedded functionalities and material properties that are difficult or even impossible to produce with traditional technologies. However, stringent quality standards and qualification requirements impose defect-free and first-time-right capabilities that are still challenging to achieve with state-of-the-art AM systems. On the other hand, the layerwise nature of the process allows one to acquire big data streams during the process itself, to keep it under continuous control and provide the final product with a sort of digital ID card based on in-situ gathered information.
This talk presents an overview of the current state of research on the development of novel methods for in-situ monitoring of metal AM processes towards next-generation smart AM systems. Typical process defects and available sensing approaches, e.g., video-imaging and thermography, will be reviewed and novel statistical data mining techniques for quick and robust in-situ and in-line defect detection will be presented.
References:
Caltanissetta F., Grasso M., Petrò S., Colosimo, B. M. (2018). Characterization of In-Situ Measurements based on Layerwise Imaging in Laser Powder Bed Fusion, Additive Manufacturing, 24, 183-199
Grasso, M., Colosimo, B.M. (2018), A Statistical Learning Method for Image-based Monitoring of the Plume Signature in Laser Powder Bed Fusion, Robotics and Computer-Integrated Manufacturing, 57, 103-115
He, L., Grasso, M., Colosimo, B.M., Huang, Q., (2018), Prescriptive Data-Analytical Modeling of Laser Powder Bed Fusion Processes, Journal of Manufacturing Science and Technology, 141(1), 011008, doi:10.1115/1.4041709
Colosimo, B.M., Grasso, M. (2018), Spatially weighted PCA for monitoring video image data with application to additive manufacturing, Journal of Quality Technology, 50(4), 391-417
Grasso, M., Demir, A.G., Previtali, B., Colosimo, B.M. (2018), In-situ Monitoring of Selective Laser Melting of Zinc Powder via Infrared Imaging of the Process Plume, Robotics and Computer-Integrated Manufacturing, 49, 229-239. https://doi.org/10.1016/j.rcim.2017.07.001
Repossini G., Laguzza V., Grasso M., Colosimo B.M., (2018), On the use of spatter signature for in-situ monitoring of Laser Powder Bed Fusion, Additive Manufacturing, 16, 35-48. https://doi.org/10.1016 /j.addma.2017.05.004.
Grasso M., Colosimo B.M., (2017), Process Defects and In-situ Monitoring Methods in Metal Powder Bed Fusion: a Review, Measurement Science and Technology, 28(4), 1-25, DOI: 10.1088/1361-6501/aa5c4f
Grasso M., Laguzza V., Semeraro Q., Colosimo B.M., (2017), In-process Monitoring of Selective Laser Melting: Spatial Detection of Defects via Image Data Analysis, Journal of Manufacturing Science and Engineering, 139(5), 051001-1 - 051001-16.
Prof. Bianca Maria Colosimo
Politecnico di Milano
Department of Mechanical Engineering
Via Giuseppe La Masa, 1
20156 Milano MI
Italy
| Phone | +39 02 2399 8522 |
| Prof. B.M.Colosimo | |
| Http | Department of Mechanical Engineering |
| Prof. B. M. Colosimo |