Manufacturing methods and procedures are advancing through research and development, to optimize machine tools, machining strategies, and the overall manufacturing system, where higher quality products have higher tolerances. In all industries part distortion occurs. In the aerospace industry, machining distortion, or the deviation of part shape from the original intent after being machined and released from a fixture, occur, reducing productivity and increasing costs, waste and scrap materials. Although machining distortion has been a challenge in the aerospace industry for many years, several of the current approaches to this problem provide point solutions for specific circumstances while relying on empirical trials at excessive cost. Modern analysis and computing resources as well as synergistic approaches from multiple disciplines are needed to tackle this problem.
In the distortion literature, basic information is missing about how distortion is practically characterized and therefore the results of experiments or modeling approaches are not easy to transfer. To fully understand part and machining distortion, a transparent way to quantify distortion data collection and analysis is needed and will enhance the transferability of experimental and analytical results. This research therefore aims at bridging the gap of part and machining distortion data collection and analysis to understand how workpiece deformations can be characterized, and manufacturing parameters optimized to reduce overall part distortion for a more economical and sustainable manufacturing method.
The presented research focuses on a detailed investigation of machining distortion characterization techniques that are used to create a uniform method for analyzing machining distortion data used in the aerospace industry. The research objectives of this study are divided into three specific objectives including: understand measurement machine capabilities and data collection methods for machining distortion, develop a clear methodology for analyzing distortion data, develop an algorithm for distortion data collection and analysis, and characterize part and machining distortion for specific manufacturing operations and geometries. The final results of this dissertation include a state of the art review on machining distortion, an initial machining distortion characterization method using pre and post z-height deviation for overall distortion, an updated 3D characterization tool incorporating Gaussian surface curvature via Bernstein basis function surface fitting and analysis, an initial case study of micro-scale distortion in a molecular dynamics simulations of a single grain pure Al in a vice structure for nanomanufacturing applications, a case study on a process planning tool that regards part quality for sustainability research and teaching, and an overall conclusion and future work.
|Advisor:||Linke, Barbara S, Farouki, Rida T|
|School:||University of California, Davis|
|Department:||Mechanical and Aerospace Engineering|
|School Location:||United States -- California|
|Source:||DAI-B 81/8(E), Dissertation Abstracts International|
|Subjects:||Mechanical engineering, Aerospace engineering, Engineering|
|Keywords:||Deformation, Distortion, Machining distortion, Metrology, Process planning, Quality|
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