Integration of Fast Predictive Model and SLM Process Development Chamber

Period of Performance: 06/17/2015 - 06/17/2016


Phase 1 STTR

Recipient Firm

Mound Laser & Photonics Center, Inc.
2941 College Drive
Kettering, OH 45420
Firm POC
Principal Investigator

Research Institution

Wright State University
134 Oelman Hall 3640 Colonel Glenn Highway
Dayton, OH 45435
Institution POC


This STTR project seeks to develop a fast predictive model for selective laser melting (SLM) processes and then integrate that model with an SLM chamber that allows full control of process variables and is equipped with in-process sensors. The combination will create a closed loop in which the model suggests process parameter settings for test builds and the sensors provide feedback to the model. This creates a powerful tool for iterative process development far faster than is currently possible by standard simulation methods and accessible to a wide range of potential SLM innovators who are not simulation specialists. The key innovation will be the development of a simple set of empirical equations that relate SLM process inputs to actual build results. This is accomplished by a combination of finite element simulations and verification experiments whose process parameters are selected by a design-of-experiments methodology. The resulting easily calculable empirical functions (a.k.a. the fast predictive model) will replace arduous simulation and undirected trial-and-error as methods of SLM process development. A user-friendly interface will be written that links the fast predictive model to sensorized SLM chamber to allow easy, rapid and flexible SLM process development. The simplicity of the system, and relatively low cost of the SLM chamber will allow large numbers of new innovators and industries to enter the field of SLM and develop novel processes that meet their application needs, as well as help solve specific problems of NASA interest. Phase I activities include 1) development of the fast predictive model, 2) development of a control algorithm and user interface linking the model to the SLM chamber, and 3) demonstration of the integrated system for rapid development of novel SLM processes.