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Online Eccentricity Monitoring of Seamless Tubes in Cross-Roll Piercing Mill

[+] Author Affiliations
Rui Chen, Weihong Guo, Jionghua (Judy) Jin

University of Michigan, Ann Arbor, MI

Paper No. MSEC2014-4147, pp. V001T04A010; 10 pages
doi:10.1115/MSEC2014-4147
From:
  • ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference
  • Volume 1: Materials; Micro and Nano Technologies; Properties, Applications and Systems; Sustainable Manufacturing
  • Detroit, Michigan, USA, June 9–13, 2014
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-4580-6
  • Copyright © 2014 by ASME

abstract

Wall thickness eccentricity is a major dimensional deviation problem in seamless steel tube production. Although eccentricity is mainly caused by abnormal process conditions in the cross-roll piercing mill, most seamless tube plants lack the monitoring at the hot piercing stage but only inspect the quality of finished tubes using ultrasonic testing at the end of all manufacturing processes. This paper develops an online monitoring technique to detect abnormal conditions in the cross-roll piercing mill. Based on an image-sensing technique, process operation condition can be extracted from the vibration signals. Optimal frequency features that are sensitive to tube wall thickness variation are then selected through the formulation and solution of a set-covering optimization problem. Hotelling T2 control charts are constructed using the selected features for online monitoring. The developed monitoring technique enables early detection of eccentricity problems at the hot piercing stage, which can facilitate timely adjustment and defect prevention. The monitoring technique developed in this paper is generic and can be widely applied to the hot piercing process of various products. This paper also provides a general framework for effectively analyzing image-based sensing data and establishing the linkage between product quality information and process information.

Copyright © 2014 by ASME

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