Risk Analysis for Monitoring and Diagnosis of Problems in the Automotive Industry 2004-21-0007
The automotive industry designs, manufactures and maintains systems in which malfunctions or defects can be detected at different stages of a vehicle’s lifecycle, e.g., the R&D process, manufacturing, or operations. Warnings of possible defects or malfunctions are based on test results as well as on-board and off-board signals. Effective diagnosis systems can help the driver in a single incident, and the vehicle manufacturer in the long-term. In all cases, data need to be gathered and communicated, and measures need to be taken on a timely basis to avoid expensive recalls, accidents, and/or commercial failures. Risk analysis models based on engineering systems analysis, probability, and human and management factors, can support the design of efficient warning systems. We present here some characteristics of effective signals, lessons learned from past failures in different industries, and analytical approaches to the design of monitoring systems that can beneficial in the automotive industry.
M. Elisabeth Paté-Cornell, B. Christopher Han
Department of Management Science and Engineering, Stanford University
Convergence International Congress & Exposition On Transportation Electronics