yieldWerx Semiconductor

As vehicles increasingly rely on electronic chips for critical functions, ensuring these chips are free from any risk of failure is becoming essential. To support this high standard of quality, yieldWerx offers a comprehensive suite of solutions for both suppliers and consumers of automotive parts. Key tools include: • Static/Dynamic Part Average Test (PAT) • Dynamic PAT for Blind Assembly  • Smart Defect Signature Analysis  • Zonal PAT  • Multi Variant PAT (MVPAT)  • Nearest Neighborhood Residual (NNR). These solutions are designed to help you achieve Zero Defects Per Million Die. Want to learn more? Click here: https://bit.ly/3UpFbQM

Welcome to the 17th Edition of yieldWerx Insights 👨💻 Here's what we cover in this issue: 👉 yieldWerx Semiconductor and SilTest Semiconductors partner-up 👉 Micron unveils 60TB SSD for AI workloads 👉 Dell launches PowerEdge XE9712 server racks 👉 Huawei's chip advances intensify global competition 👉 Foxconn and Nvidia ready to redefine manufacturing 👉 Finland's vision for Europe's semiconductor future 👉 STMicroelectronics partners with Hua Hong Stay ahead with yieldWerx Insights and elevate your yield management strategies with our powerful data analytics modules. #partnership #europe #semiconductors #yieldmanagement #automotive

yieldWerx has partnered with SilTest Semiconductors to redefine yield management and production efficiency for semiconductor manufacturers and fabless companies in Europe. This collaboration combines yieldWerx's analytical prowess and SilTest’s engineering expertise to address critical industry challenges with a data-driven approach. What’s the Impact? 🔄 Integrated Solutions: Bringing together engineering services and robust analytics to deliver actionable insights. 🚀 Efficiency Gains: Enabling quicker troubleshooting, optimized testing, and lower production costs. 🥼 Localized Expertise: Customized solutions and dedicated support for the European semiconductor market. 🤝 Together, SilTest and yieldWerx are committed to empowering Europe’s semiconductor companies with innovative tools and localized support. Here's the link to the complete press release: https://lnkd.in/gceqghsP

Metrology is the backbone of measuring process variables like thickness, alignment, and critical dimensions in semiconductor manufacturing. But here’s the dilemma: 📏 ➡️ Too few measurements? Risk losing in-line control & traceability. 💸 ➡️ Too many measurements? Increase costs, time, and complexity. The solution? Optimize the sampling rate — especially in high-volume manufacturing (HVM). Enter #VirtualMetrology (VM) 🔮 It uses upstream process data & sensors to predict post-process metrology outcomes. It’s like having measurements for every wafer without the need for extra hardware: ✅ All-wafer insights with just data & computing ✅ No extra cost for new metrology tools ✅ Breaks the traditional trade-offs in measurement capacity But wait, there’s more! When combined, VM + R2R control creates a dynamic feedback loop 🔄: 🔧 Adjusts tool parameters between runs 🎯 Ensures every wafer meets exact specs 📉 Reduces variability and boosts yield By leveraging these cutting-edge technologies, manufacturers can optimize processes, improve efficiency, and achieve wafer-level precision! 🌟 Want to learn more about the latest semiconductor yield management techniques? Visit https://lnkd.in/duNB2kv5 #AdvancedManufacturing #SemiconductorInnovation #DataAnalytics #ProcessControl #HVM

OSATs face increasing pressure to handle design complexity, reduce costs, and deliver high-quality products on time. That's where outsourced yield management software (YMS) can make a difference in the long run. By leveraging advanced data analytics, a powerful YMS helps OSATs streamline processes without the need for heavy in-house setups. The benefits? 🚀 🔹 Higher Yields & Lower Scrap: Early defect detection ensures only quality parts move forward, reducing costly callbacks. 🔹 Scalability: Seamlessly adapt to changes in production volumes and customer demands through cloud computing. 🔹 Faster Time-to-Market: Optimized test cycles enable quicker delivery to customers. 🔹 Data-Driven Optimization: Continuous improvement through predictive analytics and customized features—without needing a dedicated software team. 🔹 Lower Operational Costs: Turn capital expenses into flexible, scalable solutions. Outsourcing yield management isn't just a smart strategy—it’s the key to unlocking operational excellence. 💡 👉 Discover how yieldWerx can transform your OSAT operations! https://lnkd.in/dnDTqc5B #Semiconductors #OSAT #YieldManagement #DataDrivenDecisions #Manufacturing #Packaging #Testing

In the relentless pursuit of Moore’s Law, achieving good printed transistors isn't just about miniaturizing features—it’s a multifaceted equation involving patterning yield, resolution, accuracy, and productivity. The holistic lithography cost must also account for: 💰 Total System cost 🛠️ Operational lifetime and expenditures 🌍 Environmental impact By harmonizing both the technical and economic aspects, manufacturers can strike the perfect balance between precision and profitability.💡 Image Source: ASML #semiconductors #lithography #yieldmanagement #sustainability

Welcome to the Sixteenth Edition of yieldWerx Insights 👨💻 🔍 In this edition we discuss: 👉 Nvidia’s vision for “Hyper Moore’s Law” 👉 Highlights from the RISC-V Summit North America 2024 👉 SK hynix Unveils World’s First 16-Layer HBM3E 👉 CHIPs Act under fire from Republican leadership 👉 TSMC barred from producing its most advanced chips abroad 👉 IBM and Albany Partners unlock new yield benchmarks 👉 EU invests $142 mln in Dutch photonic chip plants Stay ahead with yieldWerx Insights and elevate your yield management strategies with our powerful data analytics modules. #TSMC #SKhynx #Nvidia #yieldmanagement #data #semiconductors

🔍 Data Overload: The Hidden Challenge for Semiconductor Yield Managers 📊 Semiconductor manufacturing data is both a goldmine and a bottleneck. As nodes shrink to 3nm and beyond, the volume of data generated is exploding—often in terabytes per wafer! But here's the catch: data is scattered across silos. From fab to final testing, teams rely on separate systems, making real-time insights nearly impossible. Yield managers find themselves tangled in a web of fragmented data, sometimes chasing issues long after they've impacted production. The solution? It's all about breaking down those silos with integrated analytics platforms that can centralize data, and streamline insights.💡 At yieldWerx Semiconductor, we’re turning data chaos into a strategic advantage. Ready to optimize your yield? Let’s talk! 📈 https://lnkd.in/dfySBdmJ

🎯 WAT: The Data Glue Between Fabs and Fabless Companies 🧷 Wafer Acceptance Testing (WAT), also known as Process Control Monitoring (PCM), generates data crucial to fabless companies at the end of the manufacturing line. With 30-100 tests per wafer and each test result mapped to specific wafer sites, WAT data offers a snapshot of process consistency and quality, aiding fabs in reducing defects. Why it matters? Efficient Quality Control: WAT provides a streamlined, manageable data set—much smaller than wafer sort or final test data—that supports fast analysis and critical parameter checks. Yield Optimization: By visualizing WAT trends and setting alerts, yield managers can spot issues before they impact reliability, reducing downstream risks. Cross-Stage Correlation: Connecting WAT data to wafer sort and final test data reveals deeper insights, often automating links that make root cause analysis faster and more accurate. This correlation also provides fabs with feedback, driving process improvements over time. Advanced YMS platforms, such as yieldWerx Semiconductor, automate these connections, offering fabless companies the power to detect potential failures early, set SPC limits, and ultimately drive higher yield quality. Want to see WAT analysis in action? Schedule a Demo Using the Link Below: https://lnkd.in/d3D59-Aw

🔬 Root Cause Isolation: A Key to Targeted Defect Management 🔍 Root cause isolation focuses on pinpointing defect sources, enabling process engineers to address issues precisely. This process has two phases: (1) prioritizing defect types using consistent detection and classification, often visualized through defect paretos. (2) isolating the defect source by analyzing data from equipment monitoring, sensor feedback, and historical defect records. Techniques like laser-based localization, time-domain reflectometry (TDR), and optical emission microscopy (OEM) aid in identifying exact fault locations within chips. Isolation often requires examining wafers across multiple steps to track defect emergence. This phase is time-intensive due to the need for systematic "forensic" analysis. Once the root cause is isolated, solutions such as design tweaks, component replacements, or process adjustments can be implemented quickly, with final checks ensuring reduced defect levels and enhanced performance. #yieldmanagement #semiconductors #faultdetection #PAT #chips Picture Source: Nano Science Instruments