In-situ Process Monitoring for Series Production of Titanium Parts by Mark Cola, Sigma Labs
Abstract: Today the time and cost associated with validation of the manufacturing process for aerospace quality components can be on the order of 15 years and $200MM. The “make and break” qualification approach is too costly. For metal Additive Manufacturing (AM) to transition to production there is a need for a rapid process qualification of metal AM components that achieves part specific performance and affordability goals. In this presentation, an In-Process Quality Assurance™ (IPQA®)-based approach is proposed that demonstrates that in-situ probabilistic sensing and routine data-capture capabilities can be transferred to the manufacturing environment to reduce qualification costs.
Experiments were performed to characterize an aerospace titanium alloy using a state-of-the-art, Directed Metal Laser Sintering (DMLS®) AM system and non-contact, in-situ sensors. Quantitative, digital In-Process Quality Metric™ (IPQM®s) aka, Quality Signature™ data, and Thermal Energy Density™ (TED™) images were generated from optical and thermal sensor data collected at 50,000 samples per second channel and correlated with process conditions selected to stress the process. Worst-case conditions were selected that challenged the process to discover how post-process quality metrics and in-process quality metrics™ changed as process input variables were varied. These process capability studies were used to define acceptable in-situ, digital Quality Signature™s that were correlated to post-process testing results (part density) and used to define an alloy-specific AM process map.
These studies demonstrated that it is possible to use in-situ monitoring to rapidly qualify engineering alloys using an AM process map made using quantitative, digital IPQM® data or Quality Signature™s coupled with conventional, post-process testing results, for example part density. Such alloy-specific AM process maps allow process engineers to develop confidence in an IPQA®-based approach to process qualification using in-situ Quality Signature™s and traditional statistical process control techniques.
