This paper presents a novel dynamic optimization framework for the grinding process in batch production. The grinding process exhibits time-varying characteristics due to the progressive wear of the grinding wheel. Nevertheless, many existing frameworks for the grinding process can optimize only 1 cycle at a time, thereby generating suboptimal solutions. Moreover, dynamic scheduling of dressing operations in response to process feedback would require significant human intervention with existing methods. We propose a unique dynamic programming–evolution strategy framework to optimize a series of grinding cycles depending on the wheel condition and batch size. In the proposed framework, a dynamic programming module dynamically determines the frequency and parameter of wheel dressing while the evolution strategy locates the optimal operating parameters of each cycle subject to the constraints on the operating ranges and part quality. Case studies based on experimental data are conducted to demonstrate the advantages of the proposed method over conventional approaches.
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April 2009
Research Papers
Dynamic Optimization of the Grinding Process in Batch Production
Cheol W. Lee
Cheol W. Lee
Department of Industrial and Manufacturing Systems Engineering,
e-mail: cheol@umich.edu
University of Michigan–Dearborn
, 4901 Evergreen Road, Dearborn, MI 48128
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Cheol W. Lee
Department of Industrial and Manufacturing Systems Engineering,
University of Michigan–Dearborn
, 4901 Evergreen Road, Dearborn, MI 48128e-mail: cheol@umich.edu
J. Manuf. Sci. Eng. Apr 2009, 131(2): 021006 (9 pages)
Published Online: March 17, 2009
Article history
Received:
August 8, 2007
Revised:
January 10, 2009
Published:
March 17, 2009
Citation
Lee, C. W. (March 17, 2009). "Dynamic Optimization of the Grinding Process in Batch Production." ASME. J. Manuf. Sci. Eng. April 2009; 131(2): 021006. https://doi.org/10.1115/1.3090880
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