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Slava Libman

Chief Executive Officer

Based in San Francisco, CA, USA

Event; Tokyo Electron; Qualcomm; Yield enhancement; Technology;

UPM Webinar Series – Facility 2.0: Webinar #1 - Enabling Yield in Next Generation of Semiconductor Manufacturing

An insight co-authored by some of the IRDS experts who gave their insights at the last UPM Community Event

Watch the event recording here. 

In collaboration with semiconductor industry experts, UPM has launched its new webinar series in preparation for the UPM 2022 Annual Conference in September. The purpose of the series is to reveal mission critical issues, so that solutions to these issues can be addressed at the conference. 
As indicated by IEEE-IRDS (International Roadmap for Devices and Systems), ‘the semiconductor industry faces the challenges and opportunities of increased product demand in the immediate future. The growth of artificial intelligence (AI) and the Internet of Things (IoT) and the ongoing demands from the smartphone sector and other high-tech industries place stress on the semiconductor supply chain. The challenge will be further complicated by ongoing international trade disputes, which may drive up the cost of semiconductor materials and interfere with global collaboration within the industry.’
The semiconductor industry is currently undergoing unprecedented transformational changes. The drivers for the changes are numerous, and each one of them is a mission critical: 
  • time-to-market and supply chain pressures
  • magnitude of construction and deficit of trained staff
  • step function higher complexity of the device and of the manufacturing process
  • sustainability commitments and more
The first webinar of this series focused on the semiconductor technology drivers. View the event recording here. The growing number and complexity of semiconductor applications – based on integration of edge and cloud base High Performance Computing (HPC), biometrics, sensors, etc. – drives exponentially growing advanced chip demand. Yield and reliability are becoming critical factors in technology enabling. High performance requires 3D complexity and heterogeneous integration to achieve larger number of transistors per device and lower energy consumption.  Automotive industry and cloud computing now require longer life of HPC, driving new requirement for reliability of the advanced devices.

Source: Qualcomm
Advanced devices have implications for yield in the following ways:
  • AI drives larger chip sizes, making it significantly harder to minimize the number of defects per chip
  • Tall and stacked transistors necessitate high aspect ratios, making it nearly impossible to remove contamination trapped in the trenches
  • Newer devices will require more process steps, thus increasing the risk of defect formation. New materials will bring new challenges
  • Time-to-market urgency drives faster facility ramp, thus applying even bigger pressure on the proactive yield management.
In addition to device-driven challenges, the facility technology capabilities present an additional layer of issues. Metrology has become constrained in its ability to detect defects both on the wafers and in the high purity materials/environments to which the wafer is exposed. As the result, the More Moore (MM), Factory Integration (FI) and Yield Enhancement (YE) forums of IRDS are collaborating on proactive and predictive approach to address this challenge.


Some of the defect control can be done via big data but it requires facilities to be organized differently.

Proactive technology/quality management implies definition of the gaps in order to help improve high purity materials and related technologies and address manufacturing needs by continuous and systemic improvements. This requires years of research and development. 
At the same time, predictive management implies new level of data analytics and machine learning capabilities which could leverage “big data” in real time to correlate yield excursions with changes happening in the systems supporting manufacturing. This requires higher digitization, effective data management, strong cyber security protection, effective data interpretation, improved connectivity, and alignment with the supply chain. 
Yield prediction will likely leverage many of the same prediction technologies used for Virtual Metrology (VM,) but will require coordination across the fab and improved data quality. Initially the focus will be on yield excursion detection (YEx) with root cause analysis via data mining (DM). This drives the following:
  • Latent yield solutions require data integration up and down the supply chain with improved security. Standards must be adopted to guarantee secure supply chain data transfer/ sharing
  • Distributed trust (e.g., via Blockchain) capabilities/mechanisms should be fully integrated into supply chain
  • Detecting security breaches in supply chain has increased importance
  • Field yield (e.g., latent yield) must be tied back to analytics, including data integration, root-cause-analysis, and yield optimization inside fab. 
Comprehensive analysis of the device drivers combined with facility gap analysis is the way IRDS drives yield enhancement and supports solutions for unprecedented industry challenges with definitions for the design and operation of the next generation of facilities. The details of the published roadmap can be found on IEEE IRDS website.


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