In multiple operation forging processes, missing parts in some dies during production is a critical problem. The objective of this paper is to develop an effective missing part detection method through automatic classification of continuous production data. In the paper, a new feature extraction and sequential classification decision rule is developed, which aims to enhance the detection sensitivity and robustness. In the methodology development, the data segmentation is conducted at the first step based on an offline station-by-station test in a forging process. Then, PCA (Principal Component Analysis) is used as the data transform for the selected data segment of the training data sets under different missing part conditions. The effectiveness of the selected features is justified to minimize the misclassification probabilities among different classes. Finally, a decision rule is proposed for online classification of different missing parts conditions. A case study using a real-world forging process is provided to demonstrate the analysis procedures and effectiveness of the proposed methodology.
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ASME 2006 International Manufacturing Science and Engineering Conference
October 8–11, 2006
Ypsilanti, Michigan, USA
Conference Sponsors:
- Manufacturing Engineering Division
ISBN:
0-7918-4762-4
PROCEEDINGS PAPER
Automatic Feature Extraction for Missing Part Detection in Forging Processes
Zhisheng Zhang,
Zhisheng Zhang
Southeast University, Nanjing, China
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Gabrielle Tremblay,
Gabrielle Tremblay
University of Michigan, Ann Arbor, MI
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Jionghua Jin
Jionghua Jin
University of Michigan, Ann Arbor, MI
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Zhisheng Zhang
Southeast University, Nanjing, China
Gabrielle Tremblay
University of Michigan, Ann Arbor, MI
Jionghua Jin
University of Michigan, Ann Arbor, MI
Paper No:
MSEC2006-21081, pp. 683-692; 10 pages
Published Online:
October 2, 2008
Citation
Zhang, Z, Tremblay, G, & Jin, J. "Automatic Feature Extraction for Missing Part Detection in Forging Processes." Proceedings of the ASME 2006 International Manufacturing Science and Engineering Conference. Manufacturing Science and Engineering, Parts A and B. Ypsilanti, Michigan, USA. October 8–11, 2006. pp. 683-692. ASME. https://doi.org/10.1115/MSEC2006-21081
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