Dissertation (UNI Access Only)
Machine parts--Design and construction; Expansion (Heat);
In this research an effort was made to investigate and explore the heat treatment distortion effects in critical features of selected part families. Controlling heat treatment distortion has ever been challenging. Distortion control and prediction of pre-heat treatment sizes, especially for the parts with complex geometries therefore have become very critical for producing products with optimized cost and design requirements. The researcher used the quantitative data analysis approach to determine how different geometries and raw material grades / chemical composition behaved in different heat treatment processes. Critical features of selected parts family were measured before and after heat treatment to find the change in size. The geometrical shapes involved in this study had different surface areas, weights and sizes. Several relationships of heat treatment distortion in critical feature’s sizes like gear slope, gear profile, pitch diameter runout, internal diameter, outer diameter, gear tooth thickness, distance measurements, spline size over pins, dimension over ball with respect to raw materials used, and the geometrical shapes were investigated that could be used as a guideline for developing new products with reduced experimentation and to achieve consistency in the final product with a better knowledge of predicted changes. A hypothetical case study is also presented by creating a statistical model to illustrate the prediction of changes in response variable with respect to categorical variables and used the predicted response to adjust the pre-heat treatment size to produce new product in an effective way.
Year of Submission
Doctor of Industrial Technology
Department of Technology
Ali Kashef, Chair
Julie Zhe Zhang, Co-Chair
1 PDF file (xvii, 178 pages)
©2020 Akaff Diam
Diam, Akaff, "Prediction of heat treatment distortion and optimization of manufacturing tolerances for machined components" (2020). Dissertations and Theses @ UNI. 1020.