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Too Much Fab And Test Data, Low Utilization


Can there be such a thing as too much data in the semiconductor and electronics manufacturing process? The answer is, it depends. An estimated 80% or more of the data collected across the semiconductor supply chain is never looked at, from design to manufacturing and out into the field. While this may be surprising, there are some good reasons: Engineers only look at data necessary to s... » read more

Using Analytics To Reduce Burn-in


Silicon providers are using adaptive test flows to reduce burn-in costs, one of the many approaches aimed at stemming cost increases at advanced nodes and in advanced packages. No one likes it when their cell phone fails within the first month of ownership. But the problems are much more pressing when the key components in data warehouse servers or automobiles fail. Reliability expectations ... » read more

Testing More To Boost Profits


Not all chips measure up to spec, but as more data becomes available and the cost of these devices continues to rise, there is increasing momentum to salvage and re-purpose chips for other applications and markets. Performance-based binning is as old as color-banded resistors, but the practice is spreading — even for the most advanced nodes and packages. Over the last three decades, engine... » read more

Infrastructure Impacts Data Analytics


Semiconductor data analytics relies upon timely, error-free data from the manufacturing processes, but the IT infrastructure investment and engineering effort needed to deliver that data is, expensive, enormous, and still growing. The volume of data has ballooned at all points of data generation as equipment makers add more sensors into their tools, and as monitors are embedded into the chip... » read more

Adaptive Test Gains Ground


Not all devices get tested the same way anymore, and that’s a good thing. Quality, test costs, and yield have motivated product engineers to adopt test processes that fall under the umbrella of adaptive test, which uses test data to modify a subsequent test process. But to execute such techniques requires logistics that support analysis of data, as well as enabling changes to a test based ... » read more

Demand Grows For Reducing PCB Defects


Board manufacturers are boosting their investment in inspection, test and analytics to meet the increasingly stringent demands for reliability in safety-critical sectors like automotive. This represents a significant shift from the past, where concerns about reliability primarily targeted the devices connected to printed circuit boards. But as SoCs become disaggregated into advanced packages... » read more

New Data Format Boosts Test Analytics


Demand for more and better data for test is driving a major standards effort, paving the way for one of most significant changes in data formats in years. There is good reason for this shift. Data from device testing is becoming a critical element in test program decisions regarding limits and flows. This is true for everything from automotive and medical components to complex, heterogeneous... » read more

Better Analytics Needed For Assembly


Package equipment sensors, newer inspection techniques, and analytics enable quality and yield improvement, but all of those will require a bigger investment on the part of assembly houses. That's easier said than done. Assembly operations long have operated on thin profit margins because their tasks were considered easy to manage. Much has changed over the past several years, however. The r... » read more

Monitoring IC Abnormalities Before Failures


The rising complexities of semiconductor processes and design are driving an increasing use of on-chip monitors to support data analytics from an IC’s birth through its end of life — no matter how long that projected lifespan. Engineers have long used on-chip circuitry to assist with manufacturing test, silicon debug and failure analysis. Providing visibility and controllability of inter... » read more

Using Fab Sensors To Reduce Auto Defects


The semiconductor manufacturing ecosystem has begun collaborating on ways to effectively use wafer data to meet the stringent quality and reliability requirements for automotive ICs. Silicon manufacturing companies are now leveraging equipment and inspection monitors to proactively identify impactful defects prior to electrical test. Using machine learning techniques, they combine the monitor ... » read more

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