Laser Powder Deposition (LPD) for additive fabrication is a relatively new technology that is currently being qualified for use in the manufacturing industry. Although this technology has significant advantages over conventional manufacturing processes, such as the reduced need for post-production part machining, the resulting component material properties (strength, ductility, etc.) are affected by process operating parameters such as laser power, head (manipulator) speed, and powder flow rate. Set points for these parameters are often based upon trial and error with process control requiring the oversight of a system operator. Additionally, thermal stresses that build up in the part and the substrate can lead to warping and separation of the part from the substrate. Although this latter effect has been investigated, no robust process control has been identified that will solve the problem. Therefore, to assure component part quality and to minimize residual stresses and attendant deformation, an intelligent laser deposition path planning control algorithm needs to be developed. Such control requires knowledge of the part thermal history. The process, however, is not amenable to direct experimental measurement, which has led to the need to develop accurate and reliable thermal models. Preliminary multi-dimensional results from one such model, discussed herein, show the need for process control and how such a model is central to developing an intelligent laser powder deposition path planning strategy.

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