Targeted design for test, better fault models, and in-system testing must keep pace with advanced-node components.

Pseudo-random testing patterns are inadequate for meeting the stringent requirements of automotive electronics.

Identify early indicators of risk by analyzing timing margin data from within the chip.

“The truthfulness or reliability of the data, which refers to the data quality and the data value. Big data must not only be ...

In today’s semiconductor industry, machine learning (ML) is no longer a buzzword — it’s an operational necessity. From ...

White light scanning interferometer (WLSI) systems are also used in RDL process monitoring. These methods rely on ...

Shift right, then left is becoming more common for test and inspection in mission- and safety-critical applications.

The collaboration focuses on leveraging data and machine learning to bridge the gap between design and manufacturing. PDF ...

Change Memory for In-Memory Computing” was published by researchers at IBM Research-Europe. “We review the current state of ...

A new technical paper titled “Metrics and Methodology for Hardware Security Constructs” was published by NIST. Abstract ...

Qualcomm to buy AlphaWave; reworking chip grants; global semi, equipment sales up; GF's $16B expansion; Arm's AI-defined ...

Chips in automobiles, trucks, and buses are subject to extremes of temperature, humidity, vibration, and radiation. The challenges of designing for these environmental conditions have grown more ...