Understanding the Prime Factors Driving Distortion in Milled Aluminum Workpieces

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Rework or rejection of metallic components due to component shape errors resulting from machining distortion reflect a significant economic loss. The cost of machining distortion is estimated to be billions of dollars annually, with a large part borne in the aerospace sector, so the control of machining distortion is a significant industrial challenge. Existing engineering approaches address the problem, but provide only point solutions to specific circumstances and rely on empirical trials at high cost. The collaborative research between the University of California, Davis (USA) and the University of Kaiserslautern (Germany) focuses on understanding the main factors and mechanisms that drive machining distortion, and subsequently explores the use of models for prediction and control. Distortion will be analyzed by analytical and experimental methods across variations of its main drivers: initial residual stress and geometry of the workpiece and parameters used in machining. The work will advance sustainable manufacturing in aerospace and other metal working industries by studying approaches that can lead to reduced losses from rework and rejection of parts. Along with graduate students directly involved, graduate and undergraduate students working in research laboratories at the two partner institutions will benefit from the international communication and exchange. Research results will be used to educate undergraduate and graduate students at both universities in existing courses in manufacturing and engineering (mechanical and aerospace), and the general public will learn about machining distortion and compensation through publications, conferences, and institutional websites. New knowledge will be gained and shared on how part geometry, symmetry, and stress levels affect machining distortion. The main objective of this project is to understand how workpiece deformations can be forecast and controlled by predictive or compensative techniques for more economical and sustainable manufacturing. The research plan relies on unique expertise and facilities at two partner institutions, and synergizes metal-cutting experiments and residual stress measurements with analytical and numerical modeling. The deep understanding of residual stress at the University of California, Davis is complemented by the expertise in milling assessment at the University of Kaiserslautern. The hypothesis to be tested is: the effects of bulk residual stress (from material processing) and machining residual stress (from milling) each create distinct effects on workpiece deformation and can be separated. Therefore, bulk residual stress and machining residual stress are first analyzed separately. In work task 1 at UC Davis, different input models for bulk residual stress will be investigated, in particular process models from the University of Kaiserslautern and the eigenstrain model from UC Davis. Furthermore, different methods (simultaneous or incremental material removal) to simulate geometry changes in workpieces with bulk residual stress are analyzed. UC Davis is responsible for defining the bulk material stress levels and characterizing bulk residual stresses with established mechanical techniques. Complementary, work task 2 is performed at the University of Kaiserslautern and different input models and their quality for machining residual stress will be investigated. Comprehensive milling experiments will help to understand the distortion of thin-walled monolithic workpieces from machining residual stress and serve as a database for the combined bulk and machining residual stress distortion. At the University of Kaiserslautern, X-ray diffraction is used to characterize the surface residual stresses. Based on the new knowledge, in work task 3 both research partners will analyze how the machining residual stresses depend on the bulk residual stresses, for example by machining within different stress regimes. In addition, boundary conditions such as effects of workpiece setup and constraint and the geometric criteria for three regimes will be explored: where both types of residual stresses or one individually have major impact on machining distortion. Finally, in work task 4 compensation techniques will be investigated and summarized first in a best practice model. The possibility to compensate the bulk induced distortion via a deliberate machining induced distortion will be explored.