A Density-Based Potential Mission Risk Assessment Approach for Aerospace Products

Mi Kai; Yun Hu

doi:10.4028/www.scientific.net/AMM.397-400.3

Paper Titles

Preface and Conference Organization

A Density-Based Potential Mission Risk Assessment Approach for Aerospace Products
p.3

A New Value Stream Mapping Technique Based on Material Flow, Information Flow and Knowledge Flow
p.8

A Rapid Simulation and Optimization Study of Production Line
p.12

Research on Trusted Manufacturing
p.16

Software Framework for Advanced Error Troubleshooting in Flexible Manufacturing System
p.21

Application of Cleaning Technology in the Remanufacturing for Loader's Axles and Transmission Box Components
p.25

The Study of Production Process System of New Multi-Feature Continuous Reel Soft Pack Trademarks
p.29

Tabu Search-Based Formation of Reconfigurable Manufacturing Cells
p.34

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 397-400A Density-Based Potential Mission Risk Assessment...

A Density-Based Potential Mission Risk Assessment Approach for Aerospace Products

Abstract:

Assessing the potential risk of mission via analyzing the product life cycle data (APRPD) is a useful aerospace product quality assurance tool. The structure of aerospace product parameters has become increasingly complex and correlations exist among the multi-dimensional parameters. It is necessary to take the correlation into account when deriving an effective APRPD analysis. In this article, a density-based APRPD approach for multi-dimensional is proposed. The local outlier factor (LOF) of the observation is investigated and according to the LOF value the potential risk are assessed. This non-parametric APRPD approach can be used to analyze non-linear correlated data and does not require any data distribution assumption. The performance of the approach is demonstrated via a numerical case.

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Periodical:

Applied Mechanics and Materials (Volumes 397-400)

Pages:

3-7

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.397-400.3

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Online since:

September 2013

Authors:

Mi Kai*, Yun Hu

Keywords:

Data Density, Potential Risk Assessment, Product Data Analysis

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