SBIR Phase I: Residual Stress and Part Distortion Prediction in Machined Workpiece Surfaces

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This Small Business Innovative Research Phase I project will develop and validate a three-dimensional finite element modeling capability to predict machining induced residual stresses. This project will significantly extend the current state-of-the-art that is limited to 2D residual stress analysis and recently, 3D oblique cutting models of single cutting edge geometries. Residual stress has become increasingly important because of its effects upon surface quality, fatigue, and workpiece distortion. Residual stress has high economic impact to industry since the cost of manufacture is incurred prior to any measurement or detection. Testing methods are very expensive, difficult, and not developed for production purposes. Industry and government testing has determined that machining induced residual stresses can be significant enough in magnitude to induce part distortion and out-of tolerance conditions on completed workpieces. This project will demonstrate an integrated approach to predicting residual stress effects upon completely manufactured parts. Workpiece residual stress due to machining parameters will be modeled, verified, and then integrated into a complete part analysis to determine the final state of stress and distortion for a complete workpiece part prior to any manufacture.The commercial applications include large, thin walled aerospace parts (such as wing spars), structural components, and parts susceptible to high rates of fatigue (rotor wing hubs and load carrying parts, spindles, structural, and powertrain components). The economic impact to predict and control part distortion induced by machining processes is very high. The cost of rejection of one part due to out-of-tolerance conditions can easily exceed $100,000 and routinely create weeks in production delay and scrap. The automotive sector, primarily within engine block manufacture, piston liners, bearings, spindles, and hard turning applications (generally) could also benefit from this technology.