Equipment Data is Valuable Only When it is Accessible: How SEMI E196 Helps Empower Advanced Analytics
By KY Wang (Eunodata), Stephen Liu (Eunodata) Jack Huang (FIL Technology) and Albert Fuchigami (PEER Group)
The semiconductor manufacturing industry is turning to advanced analytics packages to help make informed decisions to improve operational efficiencies.
The foundation for this analysis is large volumes of data.
The majority of data in semiconductor manufacturing comes from the equipment, components, and systems provided by equipment suppliers. Poorly documented equipment data and unclear direction on how to access it can compromise analysis even before it begins.
Similarly, changing the data structure or meaning as a result of software upgrades without informing the equipment user impedes any type of useful analysis because the data cannot be collected.
In both cases, equipment suppliers must provide equipment users with all the necessary instructions on how to access equipment data to empower advanced analytics. Without this information, misunderstandings can trigger false alarms, cause unnecessary downtime, and negatively impact production capacity.
The Taiwan Equipment Edge Data Governance (EEDG) Task Force under the Taiwan Information & Control (I&C) Technical Committee has developed a new SEMI Guide Standard that outlines how equipment suppliers can provide equipment users with access to data through documentation and best practices. This standard, SEMI E196 – Guide for Equipment Edge Data Governance, describes different deployment scenarios and how equipment suppliers can help equipment users access the data correctly.
SEMI E196 utilizes the shareable and nonshareable data definitions defined in SEMI E190 – Specification for Equipment Data Publication (EDP) to help frame the types of information equipment suppliers should provide:
- Shareable Data – Accessible from the manufacturing equipment through software interfaces (streaming interfaces and local data sources).
- Nonshareable Data – Equipment data that is not shareable; equipment supplier does not make this data accessible to the equipment user. This data can include the supplier’s private information, intellectual property (IP) and information that is only accessible through graphical user interfaces (GUIs) and hardware instrument panels.
Equipment suppliers determine what equipment data is considered shareable and nonshareable through agreements with each equipment user. This blog article goes into more details about these definitions and the SEMI EDP Standards.
SEMI E196 provides guidance on how equipment users can access shareable data from equipment supplier-provided factory-facing computing devices. This could be from the manufacturing equipment itself, other computing devices on the ‘edge’, or in the factory’s server racks.
Best practices described by this guide include:
- Providing a good data inventory which describe the shareable equipment data and how the equipment user can access it. For example, through SECS/GEM, EDA/Interface A, or custom interfaces.
- Recommendations to secure the data through robust data protection mechanisms.
- If the equipment user accesses data through a database or local files, describe the schema and have a process to update the equipment user if the schema changes. It is critical that applications accessing the data continue to work properly after an equipment update.
This Guide Standard also describes examples on how to incorporate data latency principles into various deployment scenarios. This is an essential subject for analysis applications to understand so they can interpret the data accurately.
As Dutch programmer Wietse Venema said: "Lack of documentation is becoming a problem for acceptance." In an industry where production demands are driven by technological advancements, such as mobile devices, automotive, and more recently, artificial intelligence and major data center infrastructure projects, proper documentation on how to access valuable equipment data as outlined in SEMI E196 is imperative to unlocking powerful analytical insights. These insights will enable the semiconductor manufacturing industry to push forward in meeting the ever-increasing global appetite for more chips.
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Authors
KY Wang is Co-Founder and CEO of Eunodata. He is co-leader of Equipment Edge Data Governance (EEDG) Task Force. He has been in the semiconductor industry for over 25 years on IT/AMHS and operations leadership positions at Micron director, Inotera AVP, and Nanya Tech. He is passionate about driving manufacturing excellence with real-time edge AI solutions.
Stephen Liu is Customer Success & Service Director of Eunodata. He is member of Equipment Edge Data Governance (EEDG) Task Force. He has been in the semiconductor industry for over 25 years on IT, Smart Manufacturing and AI at Micron, Inotera, TSMC, and Matsushi. He enjoys demonstrating how leveraging edge data with AI functions to solve customer’s production problems.
Jack Huang is Co-Founder and CEO of FIL Technology. He is active in SEMI Smart Manufacturing and Information & Control (I&C) Technical Committees. Jack is passionate about adopting SEMI standards-leveraging tools like IRAM and Smart Data-AI frameworks to drive manufacturing excellence. He is good at developing field-proven applications using modeling, monitoring, control and optimization technologies.
Albert Fuchigami is a Senior Standards Specialist at PEER Group. He is active in the SEMI Standards Program, co-chairs the North America Information & Control (I&C) Technical Committee, and co-leads the Data Diagnostic Acquisition (DDA) Task Force. Fuchigami enjoys demonstrating how standards provide factory host systems with a way to optimize their operations through automation and cybersecurity resilience. He is a champion for integrating HTTP/2 with gRPC and Protocol Buffers technology into the Equipment Data Acquisition (EDA) / Interface A standards.
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SEMI
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December 8, 2025