Journal article
A Comparison of Process Variation Estimators for In-Process Dimensional Measurements and Control
Journal of dynamic systems, measurement, and control, Vol.127(1), pp.69-79
03/01/2005
DOI: 10.1115/1.1870041
Abstract
Dimensional variation reduction is critical to assure high product quality in discrete-part manufacturing. Recent innovations in sensor technology enable in-process implementation of laser-optical coordinate sensors and continuous monitoring of product dimensional quality. The abundance of measurement data provides an opportunity to develop next generation process control technologies that not only detect process change, but also provide guidelines respective of root cause identification. Given continuous product dimensional measurements, a critical step leading to root cause identification is the variance estimation of process variation sources. A few on-line variance estimators are available. The focus of this paper is to study the interrelationships and properties of the available variance estimators and compare their performance. An operating characteristics curve is developed as a convenient tool to guide the appropriate use of on-line variance estimators under specific circumstances. The method is illustrated using examples of dimensional control for a panel assembly process.
Details
- Title: Subtitle
- A Comparison of Process Variation Estimators for In-Process Dimensional Measurements and Control
- Creators
- Yu Ding - Department of Industrial Engineering, Texas A&M University, College Station, TX 77843-3131Shiyu Zhou - Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706-1572Yong Chen - Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242
- Resource Type
- Journal article
- Publication Details
- Journal of dynamic systems, measurement, and control, Vol.127(1), pp.69-79
- Publisher
- ASME
- DOI
- 10.1115/1.1870041
- ISSN
- 0022-0434
- eISSN
- 1528-9028
- Language
- English
- Date published
- 03/01/2005
- Academic Unit
- Industrial and Systems Engineering
- Record Identifier
- 9984064114402771
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