USING MDM AND RANDOM WALK FOR ANALYZING THE COMBINED INFLUENCING STRENGTH OF RISK-DSM
DS 96: The 20th International DSM Conference
Year: 2018
Editor: Leardi, Carlo; Browning, Tyson R.; Eppinger, Steven D.; Becerril, Lucia
Author: Zou, XingQi; Yang, Qing
Series: DSM
Institution: School of Economics and Management, University of Science & Technology Beijing
Section: Managing Risk
Page(s): 015-021
ISBN: 978-3-00-057492-4
Abstract
In the complex R&D process, changes from function and component may cause uncertainties. To solve the problem, the paper builds Multi-domain Matrix (MDM) of “function-component-risk” to identify risk factors and its potential relationship. Taking the results of MDM as input, the paper uses random walk algorithm to analyze the influencing strength between different risk factors. Further, the paper calculates the combined influencing strength based on direct and indirect risk propagation. An industrial example is provided to illustrate the proposed model. Results indicate that the change of function and component can discover the risk factors and its potential relationship, and the indirect influencing is very important when measuring the combined influencing strength.
Keywords: Multi-Domain Matrix (Mdm), Random Walk Algorithm, Change Propagation, Risk- DSM