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The objective of this paper is to suggest the advantages of using SAE J1699 tests and methods as a basis for characterization of physical layer devices. This paper will examine some of the commercially available physical layer IC's that could be used to drive Class B and C multiplex networks. Device characteristics such as propagation delays, current consumption, and common mode will be presented. These characteristics could be used to test device performance in Class B and Class C multiplex applications. Also presented will be an introduction to the new SAE J1699 Recommended Practice for multiplex device testing and how J1699 might be used for physical layer device testing.

Texas Instruments and General Electric have been involved with a program to establish a Merchant Market Multichip Foundry at TI based upon the GE developed high density interconnect (HDI) multichip module (MCM) technology. This technology has been successfully applied to more than 60 complex MCM designs for aerospace, computer and telecommunication applications. The HDI technology embeds bare chip within a thin film interconnect structure eliminating the need for wirebonds or TAB attach. This unique MCM technology has demonstrated higher performance, higher density and higher reliability than any other available technology. The embedded chip feature provides a robust structure that is able to withstand high thermal cycles, high shock and high vibration environments. This paper describes semiconductor evolution processes that have driven the recent developments in MCM technology and will describe the leading chips last MCM technologies and the basic HDI chips first technology.

When integrating Class B multiplexing into automotive systems, cost-effective solutions will require an optimal partitioning of the multiplex protocol between hardware and software. The system designer is confronted with making tradeoffs based upon application through-put requirements, device availability, and cost goals. This report discusses a model for determining the system software/hardware partitioning. The model is then applied to a sensor node application to provide further insight.