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Multi-Scale Surface Characterization and Control Based High Density Measurements

[+] Author Affiliations
Xin Weng, Xiaoning Jin, Jun Ni

University of Michigan, Ann Arbor, MI

Paper No. MSEC2014-4122, pp. V001T04A044; 11 pages
  • 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


It is widely observed that today’s engineering products demand increasingly strict tolerances. The shape of a machined surface plays a critical role to the desired functionality of a product. Even a small error can be the difference between a successful product launch and a major delay. Thus, it is important to develop measurement tools to ensure the quality and accuracy of products’ machined surfaces. The key to assessing the quality is robust measurement and inspection techniques combined with advanced analysis. However, conventional Geometrical Dimensioning and Tolerancing (GD&T) such as flatness falls short of characterizing the surface shape. With the advancements in metrology methodology utilizing digital holographic interferometry, large amount of surface data can be captured at high resolution and accuracy without changing platform or technique. This captured High Definition Data (HDD) enables the mining of more valuable information from machined surfaces that most current industry practice cannot achieve in a timely manner. Such new metrology system opens the torrent of observable events at plant floor and increases the transparency of machining processes. This presents great opportunities to characterize machined surface into a new level of details, which can be applied in production quality evaluation and process condition monitoring and control. This research work proposes a framework of a multi-scale surface characterization for surface quality evaluation and process monitoring. Case studies are presented to show how proposed metrics could be applied in surface quality evaluation and process monitoring.

Copyright © 2014 by ASME



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