Machine Learning For ADAS Camera Manufacturing


Virtually every vehicle manufacturer in the world is either developing, purchasing, or investing in ADAS systems in order to bring autonomous vehicles into the market. With this demand on the rise, the need for high quality automotive camera modules is rising. ADAS systems are built using computer vision technology and act as the “eyes” of autonomous vehicles. Numerous cameras are embedd... » read more

The Critical But Less Obvious Risks In AI


AI has been the subject of intense debate since it was first introduced back in the mid-1950s, but the real threat is a lot more mundane and potentially even more serious than the fear-inducing picture painted by its critics. Replacing jobs with technology has been a controversial subject for more than a century. AI is a relative newcomer in that debate. While the term "artificial intelligen... » read more

Looking To Unlicensed Spectrum For 5G


When the International Telecom Union (ITU) outlined the key objectives for 5G, the 3GPP faced the difficult task of expanding the capabilities of the current wireless network under the constraint of limited spectrum. Spectrum equates to bandwidth, and the industry needs more spectrum to increase data rates and address specific use cases beyond 4G. Unfortunately, there isn’t much unoccupied sp... » read more

The Hidden Potential Of Test Engineers


Design engineers are seen as the cornerstone of new projects in many semiconductor companies, working away with the team to design the next product and making sure it meets all specifications. We pay little thought to the test engineer, who works in the shadows designing algorithms, hardware and software that could pass or fail each die. The test engineer is the last line of defense between... » read more

Highly Efficient Scan Diagnosis With Dynamic Partitioning


Charged with the task of improving yield, product engineers need to find the location of defects in manufactured ICs quickly and efficiently. Typically, they use volume scan diagnosis to generate large amounts of data from failing test cycles, which is then analyzed to reveal the location of defects. Scan failure data provides the basis for many decisions in the failure analysis and yield impro... » read more

The Great Test Blur


As chip design and manufacturing shift left and right, concerns over reliability are suddenly front and center. But figuring out what exactly what causes a chip to malfunction, or at least not meet specs for performance and power, is getting much more difficult. There are several converging trends here, each of which plays an integral role in improving reliability. But how significant a role... » read more

5 Steps To Data-Driven Manufacturing


There is a lot of hype surrounding “Industry 4.0,” “Smart Manufacturing,” “the Industrial Internet of Things (IIoT),” and other associated terms, but it all boils down to one question: How do I become a data-driven manufacturer? Companies strive to be data driven, realizing that decisions will be more objective and more likely to achieve the desired results. In fact, many compani... » read more

Degradation Monitoring – From Vision to Reality


Reliability physics has historically focused on models for time-to-failure, but that approach is reaching its limit. Those models generally were developed using data gathered from very simple test structures that could be stressed to failure. Today, with electronics playing a such a critical role in our everyday life, failures are no longer an option. The underlying ICs being implemented call f... » read more

Hierarchical DFT On A Flat Layout Design


The use of hierarchical DFT methods is growing as design size and complexity stresses memory requirements and design schedules.  Hierarchical DFT divides the design into smaller pieces, creates test structures and patterns at the core level, then retargets the core patterns to the chip level. But, if you need to perform the physical place and route on the full flat design, can you still take a... » read more

Who Is Responsible For Part Average Testing?


With ever-increasing demands in the automotive industry, more and more semiconductor companies are interested in monitoring and improving quality and reliability. Outlier detection and more specifically Part Average Testing (PAT) is the industry standard for the automotive industry. But, who is responsible for quality? Historically, OSATs are responsible for this. In the past, once they... » read more

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