Data Sharing And Digital Threads


Electronics and the components that power them are more complex and advanced than ever. With these products an integral part of our daily lives, their reliability has become nothing less than mission-critical. As the demand for components accelerates, it is important that quality is not compromised under the pressure to meet quantity requirements. Otherwise we’re going to be seeing a lot of r... » read more

New Approaches To Security


Different approaches are emerging to identify suspicious behavior and shut down potential breaches before they have a chance to do serious damage. This is becoming particularly important in markets where safety is an issue, and in AI and edge devices where the rapid movement of data is essential. These methods are a significant departure from the traditional way of securing devices through l... » read more

The 3 Main Obstacles To Zero DPPM And How To Overcome Them


As we all well know, there are multiple mission critical applications in today’s “Age of Smart” that are calling for zero DPPM (defective parts per million) in semiconductors and electronic systems. In industries such as automotive, medical, aerospace, and more, where lives are at stake, defective parts are not an option. The quality imperative However, with the ever-growing complexi... » read more

Next Wave Of Security For IIoT


A rush of new products and services promise to make the famously un-secured Industrial IoT (IIoT) substantially more secure in the near future. Although the semiconductor industry has been churning out a variety of security-related products and concepts, ranging from root of trust approaches to crypto processors and physically unclonable functions, most IIoT operations have been slow to adop... » read more

Using Sensor Data To Improve Yield And Uptime


Semiconductor equipment vendors are starting to add more sensors into their tools in an effort to improve fab uptime and wafer yield, and to reduce cost of ownership and chip failures. Massive amounts of data gleaned from those tools is expected to provide far more detail than in the past about multiple types and sources of variation, including when and where that variation occurred and how,... » read more

Using Data Analytics More Effectively


The semiconductor industry is under a lot of pressure from their customers nowadays. They’re expected to keep up with consumer expectations for shorter electronic product life cycles, without compromising on the reliability and quality of the components and products coming off the line. A recent article from McKinsey & Company, however, describes how quality procedures have become a bottl... » read more

Reliability Becomes The Top Concern In Automotive


Reliability is emerging as the top priority across the hottest growth markets for semiconductors, including automotive, industrial and cloud-based computing. But instead of replacing chips every two to four years, some of those devices are expected to survive for up to 20 years, even with higher usage in sometimes extreme environmental conditions. This shift in priorities has broad ramificat... » read more

When AI Goes Awry


The race is on to develop intelligent systems that can drive cars, diagnose and treat complex medical conditions, and even train other machines. The problem is that no one is quite sure how to diagnose latent or less-obvious flaws in these systems—or better yet, to prevent them from occurring in the first place. While machines can do some things very well, it's still up to humans to devise... » read more

Finding Faulty Auto Chips


The next wave of automotive chips for assisted and autonomous driving is fueling the development of new approaches in a critical field called outlier detection. KLA-Tencor, Optimal+, as well as Mentor, a Siemens Business, and others are entering or expanding their efforts in the outlier detection market or related fields. Used in various industries for several years, outlier detection is one... » read more

Deep Learning Spreads


Deep learning is gaining traction across a broad swath of applications, providing more nuanced and complex behavior than machine learning offers today. Those attributes are particularly important for safety-critical devices, such as assisted or autonomous vehicles, as well as for natural language processing where a machine can recognize the intent of words based upon the context of a convers... » read more

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