An assembly sensitivity analysis method based on state space model
Abstract
Purpose
This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins and inertial navigation system (INSs), and establish the assembly process state space model for their assembly sensitivity research.
Design/methodology/approach
To date, the process-related errors that cause large variations in key product characteristics remains one of the most critical research topics in assembly sensitivity analysis. This paper focuses on the unique challenges brought about by the multi-station system: a system-level model for characterizing the variation propagation in the entire process, and the necessity of describing the system response to variation inputs at both station-level and single fixture-level scales. State space representation is used to describe the propagation of variation in such a multi-station process, incorporating assembly process parameters such as fixture-locating layout at individual stations and station-to-station locating layout change.
Findings
Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given assembly process parameters.
Originality/value
A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.
Keywords
Acknowledgements
This work is supported by the NSFC (Natural Science Foundation of China): 51175505, National Ministries and Commissions Project: 51318010406, and the National University of Defense Technology Project (NUDTP): No. JC14-03-03 to Dr Zhuo Wang.
Citation
Li, X., Shang, J. and Zhu, H. (2017), "An assembly sensitivity analysis method based on state space model", Assembly Automation, Vol. 37 No. 2, pp. 249-259. https://doi.org/10.1108/AA-04-2016-033
Publisher
:Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited