Predictive and Adaptive Machine Control for Additive Manufacturing

The metal laser powder bed fusion market has an amazing projected compound annual growth rate of 22.5% to 28% over the next 5 years, which is driven by the aerospace and biomedical industries. However, part certification remains an arduous process due to the numerous rouge defects and anomalies which can occur. In situ sensors have promised and been shown to be capable of spotting these defects; however, this comes at the cost of significant portions of data which is unreadable to the average technician for quality control purposes. Furthermore, once a potential defect is spotted, the ability to heal is non-existent in the industry. A proposed solution incorporating intelligent prediction, machine learning, and adaptive machine control is proposed as a reasonable solution to the problem.