Development of an Optimization Methodology for the Aluminum Alloy Wheel Casting Process
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E aluminum wheel manufacturing industry is very competitive, and manufacturers are constantly under pressure to improve quality and reduce cost. This is generally done by improving the design and manufacturing processes. Conventionally, these improvements have been realized by trial-and-error, building on past practice or experience. With this approach, each idea must be trialed in the plant resulting in significant costs for process improvement. Overall, the trial-and-error approach typically results in long design lead times, high scrap rates, and less than optimal production rates. The use of Computer-Aided-Engineering (CAE) tools has become standard practice in manufacturing industries. For cast products, CAE tools are first used to design the product to meet performance requirements and then to design the casting process. Casting process models are now routinely used to compliment the trialand-error design process by simulating the casting process prior to committing to plant trials and by seeking solutions to production issues. The work presented in this study seeks to reduce the reliance on trialand-error techniques by developing a method to optimize the wheel casting process using a casting process JIANGLAN DUAN, Ph.D. Candidate, CARL REILLY, Research Associate, DAAN MAIJER and STEVE COCKCROFT, Professors, are with the Department of Materials Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada. Contact e-mails: [email protected]; [email protected] ANDRE PHILLION, Assistant Professor, is with the School of Engineering, the University of British Columbia (Okanagan), Kelowna, BC V1V 1V7, Canada. Manuscript submitted December 30, 2014. METALLURGICAL AND MATERIALS TRANSACTIONS B
model and open-source numerical optimization tools. This initial work is focused on optimizing the cooling conditions in a low-pressure die casting (LPDC) process used to produce automotive wheels. More specifically, cooling channel timing was selected as the focus area because of the critical role heat extraction plays on casting quality, both in terms of dendrite cell size[1] and the formation and growth of porosity.[2–4] For example, higher cooling rates lead to improved fatigue performance and reduced cycle times. In the current work, a methodology that has been developed to optimize the cooling conditions in an LPDC wheel casting process will be introduced. The application of the optimization tool to a geometrically simplified wheel and die (L-shaped geometry) will be presented as a verification example. Finally, an industrially relevant application to a 2-D axisymmetric wheel and die geometry will be presented.
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BACKGROUND
The two major techniques used in developing the optimization methodology in this study are (1) casting process modeling and (2) numerical optimization. These techniques must be coupled to enable casting process numerical optimization. A. Casting Process Modeling Casting process models have been used extensively to study the filling practice and solidification behavior in a wide vari
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