Getting The Biggest ROI On Your Digital Twin


In the semiconductor industry, digital twins are the focus of a lot of attention, with substantial investments from industry players and governments alike. This year the European Union and the United States have pledged hundreds of millions of dollars in grants and funding opportunities, including the new CHIPS Digital Twin Manufacturing USA Institute. Ultimately, many people see great value in... » read more

AI’s Power To Transform Semiconductor Design And Manufacturing


Artificial intelligence and machine learning (AI/ML) have immense power to transform semiconductor design and manufacturing for a variety of broad and far-ranging applications. Just consider the volume of data generated by design and manufacturing each year. With increasingly complex products, machines, processes and supply chains, the overall amount of data associated with semiconductor making... » read more

Increasing Roles For Robotics In Fabs


Different types of robots with greater precision and mobility are beginning to be deployed in semiconductor manufacturing, where they are proving both reliable and cost-efficient. Static robots have been used for years inside of fabs, but they now are being supplemented by collaborative robots (cobots), autonomous mobile robots (AMRs), and autonomous humanoid robots to meet growing and widen... » read more

Big Payback For Combining Different Types Of Fab Data


Collecting and combining diverse data types from different manufacturing processes can play a significant role in improving semiconductor yield, quality, and reliability, but making that happen requires integrating deep domain expertise from various different process steps and sifting through huge volumes of data scattered across a global supply chain. The semiconductor manufacturing IC data... » read more

Coping With Parallel Test Site-to-Site Variation


Testing multiple devices in parallel using the same ATE results in reduced test time and lower costs, but it requires engineering finesse to make it so. Minimizing test measurement variation for each device under test (DUT) is a multi-physics problem, and it's one that is becoming more essential to resolve at each new process node and in multi-chip packages. It requires synchronization of el... » read more

Managing Wafer Retest


Every wafer test touch-down requires a balance between a good electrical contact and preventing damage to the wafer and probe card. Done wrong, it can ruin a wafer and the customized probe card and result in poor yield, as well as failures in the field. Achieving this balance requires good wafer probing process procedures as well as monitoring of the resulting process parameters, much of it ... » 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

Transforming Vision Inspection With Machine Learning


How auto-manufacturers can apply ML & AI algorithms to enhance image analytics on their factory floor and to ensure higher product quality? Discover the next generation visual inspection in our new case study. In this case study , you will learn about: Current limitations of image inspection in the manufacturing industry. The O+ end-to-end solution, which brings machine learning and... » 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