Sensor optimization for fault diagnosis in multi-fixture assembly systems with distributed sensing
Khan, A. and Ceglarek, Darek. (2000) Sensor optimization for fault diagnosis in multi-fixture assembly systems with distributed sensing. Journal of Manufacturing Science and Engineering, Vol.122 (No.1). pp. 215-226. ISSN 1087-1357Full text not available from this repository.
Official URL: http://dx.doi.org/10.1115/1.538917
Sensing for the system-wide diagnosis of dimensional faults in multi-fixture sheet metal assembly presents significant issues of complexity due to the number of levels of assembly and the number of possible faults at each level. The traditional allocation of sensing at a single measurement station is no longer sufficient to guarantee adequate fault diagnostic information for the increased parts and levels of a complex assembly system architecture. This creates a need for an efficient distribution of limited sensing resources to multiple measurement locations in assembly. The proposed methodology achieves adequate diagnostic performance by configuring sensing to provide an optimally distinctive signature for each fault in assembly. A multi-level, two-step, hierarchical optimization procedure using problem decomposition, based on assembly structure data derived directly from CAD files, is used to obtain such a novel, distributed sensor configuration. Diagnosability performance is quantified in the form of a defined index, which serves the dual purpose of guiding the optimization and establishing the diagnostic worth of any candidate sensor distribution. Examples, using a multi-fixture layout, are presented to illustrate the methodology.
|Item Type:||Journal Article|
|Divisions:||Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)|
|Journal or Publication Title:||Journal of Manufacturing Science and Engineering|
|Publisher:||A S M E International|
|Official Date:||February 2000|
|Page Range:||pp. 215-226|
|Access rights to Published version:||Restricted or Subscription Access|
Actions (login required)