Renishaw launches InfiniAM Spectral onto the market.
Global engineering firm, Renishaw has announced the release of its InfiniAM Spectral additive manufacturing (AM) process monitoring software.
First seen at formnext in 2017, the package is designed to help users of its metal AM systems to overcome the barriers in critical applications, process stability and part quality through data capture and analysis.
During the laser powder-bed fusion (LPBF) process, several sources of variation can occur which can produce anomalies that impact part longevity. Real-time spectral monitoring technology enables manufacturers to gather melt-pool data to enable traceable production and process optimisation.
“For additive manufacturing to become a truly ubiquitous manufacturing technology, users and practitioners require a deep understanding of the process,” explained Robin Weston, Marketing Manager at Renishaw’s Additive Manufacturing Products Division. “The software will be hugely beneficial to manufacturers looking to achieve consistent processing with AM.”
The new software offers two measurement functions in the sensor modules. The first module, LaserVIEW, uses a photosensitive diode to measure the intensity of the laser energy. The second module, MeltVIEW, captures emissions from the melt pool in the near-infrared and infrared spectral ranges. These two sensor signals can be compared to help identify discrepancies.
MeltVIEW and LaserVIEW stream live data on a layer-by-layer basis, so manufacturers can analyse process monitoring data in real-time. The engineer can compare the data from each sensor to identify any deviations, which may indicate the presence of anomalies that could lead to defects.
“The amount of process data generated during an AM build is immense, which means it can be difficult to make practical use of it without the correct interpretation tools,” continued Weston. “InfiniAM Spectral enables manufacturers to easily interpret data and gain a more detailed understanding of their AM processes. Access to real-time data opens the door to future developments in process control – detecting and correcting problems in real-time.”
