SUMMARY

To facilitate the transition of Stereolithography (SLA) into the manufacturing domain and to increase its appeal to the micro manufacturing industry, process repeatability and surface finish need to be improved. Researchers have mostly focused on improving SLA surface finish within the capabilities of commercially available SLA machines. The capabilities of these machines are limited and a machine-specific approach for improving surface finish is based purely on empirical data. In order to truly improve surface finish of SLA technology, a more systematic approach that will incorporate process parameters is needed. To achieve this, the contribution of different laser and process parameters, such as laser beam diameter, laser beam scan angle, irradiance distribution, and scan speed, to SLA resolution and indirectly to surface finish, need to be quantified and incorporated into an analytical model. In response, a dynamic analytical SLA cure model has been developed and applied to SLA geometries of interest. Using flat surfaces, the efficacy of the model has been computationally and experimentally demonstrated. The model has been applied to process planning as a computational inverse design method by using parameter estimation techniques, where surface finish improvement on slanted surfaces has been achieved. The efficacy of this model has been demonstrated computationally and experimentally. Based on the experimental results, use of the analytical model in process planning results in a significant reduction in surface roughness average of SLA parts. The intellectual contributions that result from this work are development of an analytical SLA cure model and application of inverse design techniques to a new field of SLA process planning. Application of the process planning approach to the design of rapid manufacturing machines, as well as development of process planning techniques and materials are identified as future research thrusts.