Design, Diagnosis, and Digitization for efficient system test and analytics to accelerate time to quality across the End to End Value Chain
The Networking Systems trend continues to push the boundaries on heterogeneous integrations of multiple dies in a package, silicon and photonics convergence, and higher density component integration on the system board. The need to detect known good die under any conditions at the earliest possible test step is key. A die will go through many test steps from its initial wafer test to use in its final application, presenting many opportunities for the known good die to become a known bad die, as electrical, thermal, power, signal integrity and test conditions change from one step to the next.
The use of advanced Si technology nodes brings in lower supply voltages and higher sensitivity to noise, and the use of advanced packaging increases design thermal sensitivity. These trends result in increases in:
- cost to “build in” reliability, voltage and thermal margins;
- higher functional complexity;
- noise/thermal driven
interdependence of components on the board,
- more complex failure mechanisms that are harder to partition unless component level DFT and testing is carefully thought out in advance and designed in.
The key to address the challenges above, is to extend high coverage test, characterization and fault isolation methodology that serves the component eco-system to system community and enables tighter component to system co-optimization. The ability of any known bad die to dump out pertinent, actionable, digitized information at any point of fail end to end, that is traceable by a unique identifier, enables a proliferation of data analytics to be done, that can help to drive test coverage earlier in the supply chain, and lead to real-time root cause, quicker corrective action and cost reduction.
In the presentation we will cover differences between component level test and system level test and various paths to cover the gap. We will also show how test data is integrated to partition the failure and to feed into process control of direct suppliers and deeper into supply chain.