Notes on:
Automotive Electronics Reliability SP-696, SAE (Marvin Hartz, Organizer), Warrendale PA, 1987. (67 pages).
This is a collection of SAE papers that together form a design manual for automotive reliability. In particular it addresses the differences between automotive applications and defense/aerospace approaches such as MIL-HDBK-217. Topics include reliability prediction for electrical components, electronics, wiring harnesses, and mechanical components.
The various papers can also be obtained from SAE Transactions, 1987, Vol. 86, Section 1, which may be more likely to be in libraries than this particular publication.
Topic coverage: (*** = emphasized; ** = discussed with some detail; * = mention)
| *** | Dependability | *** | Electronic Hardware | Requirements | |||||
| Safety | Software | *** | Design | ||||||
| Security | ** | Electro-Mechanical Hardware | ** | Manufacturing | |||||
| Scalability | Control Algorithms | ** | Deployment | ||||||
| Latency | Humans | * | Logistics | ||||||
| ** | Affordability | Society/Institutions | Retirement |
Other topics: automotive-specific issues.
Preface:
"The implementation of on board electronics has enabled the automotive industry to make dramatic improvements in function, cost, weight reduction, and reliability of present day vehicles. Electronic controls have been applied to virtually all vehicle functions. This rapid escalation in the number of automotive electronic systems requires a need for methods and effective procedures to control and predict the reliability of electronic systems.
"In 1978 an Electronic Reliability Subcommittee was formed within the structure of the SAE Electronic Systems Committee. This committee recognized the limited usefulness of the industry standard component reliability prediction methodology of MIL-HDBK-217 for application to the environmental exposure and service requirements of the modern automobile. In 1983 the Electronic Reliability Subcommittee authored SAE paper 840486 which provides a predictive model for automotive components and systems based on failure rate information of automotive components. This year, 1987, SAE, with the support of the Electronic Reliability Subcommittee, is publishing'a comprehensive design manual which presents the methodology procedures and technical references needed by designers to make capable electronic system reliability predictions.
"The eight papers presented in this session augment the preceding work of the Reliability Subcommittee. The topics of discussion include update information on previously developed prediction models, case studies of given system prediction, analysis of the efficacity of prediction methodology, economic issues related to reliability prediction, and discussions of applicability of electronics reliability prediction methodology to other vehicle systems, i.e., in this case, automotive electrical wire networks. "
Marvin E. Hartz
870050 Automotive Electronic Reliability Prediction 1
William K. Denson and Mary G. Priore
IIT Research Institute
870051 Reliability Prediction Techniques-Electrical/Electronic
Products 13
William Kerscher
Product Assurance
AC Spark Plug Div.
General Motors Corp.
870052 Reliability Analysis of Mechanical Components 21
James A. Davis and Sandeep Johri
Product Assurance
AC Spark Plug Div.
General Motors Corp.
870053 Defining the Uncertainty of Reliability Predictions 29
E. Harold Vannoy
Product Assurance
AC Spark Plug Div.
General Motors Corp.
Tony Lin
Industrial Systems Engineering
GMI Engineering & Management Institute
870054 Confidence Allocation in System Reliability Estimation 37
E. Harold Vannoy and Hal Stephenson
Product Assurance
AC Spark Plug Div.
General Motors Corp.
870055 Prediction of Wiring Harness Reliability 45
J. H. Derr
Research Staff
Ford Motor Co.
C. M. Straub and S. Ahmed
Body and Chassis Engineering
Ford Motor Co.
870056 Automotive Module Burn-in-A Means to Reliability
Verif lcation 55
L Lee Kent
Bendix Electronics
Allied Automotive
870057 Calculating Semiconductor Cost of Ownership 61
Donald L. Denton
Texas Instruments
Dallas, TX
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Philip Koopman: koopman@cmu.edu