U N L O C K I N G VA L U E :The Power of AI in Semiconductor Test
ACS White Paper

White Paper

Unlocking Value: The Power of AI in Semiconductor Test

INTRODUCTION
AI (Artificial Intelligence) and data analytics empower
semiconductor manufacturers to extract valuable
insights from the massive amounts of data generated
throughout the silicon lifecycle. By leveraging AI
algorithms, semiconductor manufacturers canoptimize silicon design, assembly, and testingprocesses. Through the analysis of vast datasets,
AI can identify patterns, predict failures, and optimize
quality, leading to improved yield rates, reduced
production costs, and accelerated time-to-market.
Semiconductor manufacturers are actively developing
data analytics applications to establish a fully
integrated workflow across the semiconductor test
ecosystem. A state-of-the-art data analytics solution
encompasses vital features like streaming datacollection and control, data feed forward, low latency,
intelligent decision-making powered by ML-driven
algorithms, and robust data security and integrity
capabilities. This enables the end-to-end utilization

possible, enabling prompt corrective actions.
This leads to improved quality, yield, and fastertime-to-market for customers.

THE STATE OF THE SEMICONDUCTOR INDUSTRY
IN 2023
The semiconductor industry is fundamentally athrilling, high-stakes game of cat and mouse.
It is a world of cutting-edge technology, where theseparation between science and science fiction isoften blurred. It is also an industry where the biggest
players hold almost all the cards, but where new
players are constantly emerging to shake things up.
In the world of semiconductors, the line between
success and failure is razor-thin and the futureis always uncertain, but constant innovation andprogress are inevitable, with new technologies suchas 5G, the Internet of Things (IoT), and AI driving
demand for more advanced semiconductor devices
and solutions.

of analytics throughout manufacturing and test

Integrated circuits reflect a relatively recent Newoperations.

World Order where the trade tensions between

This white paper addresses the significant
semiconductor test challenges of the digital age andhighlights the benefits of intelligent manufacturingsolutions that drive efficiency and optimize production
processes for semiconductor customers. The
solutions include ACS Real-Time Data Infrastructure

countries and supply-chain disruptions are constantthreats and where the impact of the pandemic
continues to affect the industry as well. But despite
these challenges, the industry continues to pushforward, driven by the relentless pursuit of innovationand progress.

(RTDI) and machine learning-driven analytics

The industry is constantly pushing the boundaries

solutions from Advantest and its ecosystem partners,

between what is possible and what seems impossible.

establishing a digital highway for the seamless

It is a world of innovation and limitless possibilities,

integration of all test data. By leveraging low-latency

where the brightest minds and the most daringedge computing and analytics solutions, real-timeentrepreneurs can change the course of history.

monitoring of semiconductor test operations becomes

The risks are high, but so are the rewards, where© 2023 Advantest CorporationMay 2023

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Unlocking Value: The Power of AI in Semiconductor Test

the future is always up for grabs, and where the only

more chips per wafer but also to more transistors

thing that’s certain is that nothing is certain. Ultimately,per chip, increased design complexity, and more

only the strongest and the smartest will survive.

process corners as well as new processes, tests,

PREDICTIONS FOR THE INDUSTRY: 2023 AND BEYOND
The impact of the rapidly evolving digital

diagnostics, and more complex assembly.²•The data explosion originates in part from theever-growing number of test vectors necessary tosuperhighway is already being felt with big data

test the increasing number of transistors per chipand advanced technologies driving change.

(Figure 2).³

One projection puts the semiconductor market atapproximately $1.1 trillion in 2030, with a CAGR of
9.03% from 2020 to 2030 compared to 3.96% from2010 to 2020 (Figure 1).

Figure 2. The growing number of transistors and the vectors needed to test
them is driving the test-data explosion.

•The industry is seeing a greater focus ondata analytics. The increasing amount of data
generated during test will place a greater emphasison data analytics to extract insights and improve
decision-making.

Figure 1. One projection puts semiconductor market at approximately$1 trillion in 2030.

•The increasing complexity of semiconductor

The increase in the software content of electronics

devices will drive the increased adoption of AI andproducts will also have a positive impact on theML in semiconductor testing. AI and ML can enablegrowth of the semiconductor market.¹

more advanced testing methods and equipment tohelp improve efficiency, accuracy, and scalability.

This rapid market growth will significantly impact testwith respect to the exploding test-data volume and•ways to handle that volume:•backward will become more prevalent, helping
to improve the accuracy and efficiency ofOne report says that “…roughly 2 TB of data weresemiconductor testing.

generated per day in 2019…” and adds, “Thevolume of test data jumped in the move from 10nm

The use of data feed forward and data feed•

Data and Edge computing will augment

to 7nm, and it will increase again at each new

semiconductor testing, allowing for more flexiblenode.” The report attributes this increase in part toand scalable testing methods.

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Unlocking Value: The Power of AI in Semiconductor Test

Market growth will also increase pressure on test

and advancements in automation and robotics willwith regard to application areas, packaging strategies,

continue to be adopted more widely in semiconductor

environmental concerns related to edge applications,

testing, helping to improve efficiency and reduceand cybersecurity:

human error.

•MAJOR CHALLENGES FACING THE INDUSTRY

The growing demand for autonomous vehicles,
IoT, and 5G devices will drive the need for moreadvanced semiconductor testing methods andequipment.

Increasingly widespread use of heterogeneous
integration⁴—the integration of multiple technologies
and materials in a semiconductor product—will leadto an increased need for testing methods that canhandle it.
•

Test equipment must be flexible and able to handle
a wide range of environmental conditions, and test

and service-based business models, the increasing
complexity of semiconductor devices will require
faster test times and higher throughput to keep pacewith the rapidly increasing demand for semiconductor
devices; more accurate and precise testing as
semiconductor devices become denser and more
complex with increasingly tighter tolerances; andflexible and open solutions to test a wide range ofdevices using technologies from differing sources.

rather than being restricted to a centralized

Furthermore, test systems must have the ability toDevices under test will include increasing numberof sensors, and the data produced by them willneed to be leveraged to improve product quality,reliability, and efficacy. Also, test equipment will
have more embedded sensors which will exploited•integration, 2.5D and 3D packaging, test data volume,data should be available in the distributed network
database.
•In addition to the challenges related to heterogeneous

test multiple technologies, such as digital and analog,
be on the same platform; be able to handle a larger
number of device types and package sizes; can test
at different temperatures and voltages; and to test
new materials and structures, such as those used in
2.5D and 3D packaging. Finally, strategies must beto monitor and control test operations in real-time.

developed to handle the challenges of data privacy,

As semiconductor devices become more complex

data computing.

and further connected, there will be a greaterneed to focus on cybersecurity to protect against
potential cyber threats and ensure the integrity of
IP during the testing process.
And finally, the semiconductor test industry will likely
see the emergence of new business models, suchas pay-per-use and subscription-based services,© 2023 Advantest Corporation

security, and compliance in the era of big data and

The challenges of big data are daunting. One
estimate states that 80% or more of the data collectedacross the semiconductor supply chain is neverlooked at, from design to manufacturing and out into
the field. Contractual obligations, particularly in theautomotive and aerospace industries, may requirearchiving data for 10 or 15 years, but engineers tend

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Unlocking Value: The Power of AI in Semiconductor Test

to only look at the data needed to solve a specific

The approach applies neural networks to parametricproblem. In addition, some stored data lacks theprediction, taking into account dependencies on

traceability and context that would make it useful.²

temperature, power, and other conditions, enablingThat is not to say there is no value in the data.
But the tools and infrastructure to effectively analyze
the data and extract maximum value from it are
currently inadequate. Everyone desperately wants tomine their data, but practically speaking they simply
physically cannot make it happen.

significant test-time reductions with zero impact
on quality.⁵

ADVANTEST ACS: THE SOLUTION TO SEMICONDUCTORTEST CHALLENGES
With advanced analytics, including ML capabilities
and future-proof, real-time, automated production

Yet another problem is that currently, testing iscontrol, the ecosystem addresses test challenges

typically accomplished via a file-based approach,by integrating all data sources across the entire

whereby the data is not available until end of wafer

IC manufacturing supply chain. This ecosystem

or end of lot, and only then can the data be analyzed

enables customers to achieve intelligent data-driven

offline, often at a different location. Even though theworkflows and helps customers realize better yields,

clock is ticking, hours or days are often needed tofaster time-to-market, accelerated time-to-volume,

perform analysis and corrective action.

and improved quality and reliability. As a part ofThis approach is no longer viable given the rapid
pace at which the test industry is evolving. As stated,chips are becoming increasingly complex and, inmany cases (including medical and automotive device

Advantest’s Grand Design strategy, ACS is enhancing
edge and data infrastructure services, data analytics,
and AI/ML solutions as a means of helping customers
accomplish data-driven workflows.

test), zero defects is the goal. In other cases, even

Advantest’s data-based products and services areminor defects that used to be acceptable now render

based on a single scalable real-time data platform

more sensitive and complex chips useless. Testing(Figure 3), which empowers customers to develop orthese more advanced chips has therefore become theprocure market-leading solutions from Advantest andchallenge, along with meeting more aggressive time-

its partners. ACS uses real-time ML analytics so thatto-volume goals and time-to-volume goals that ensure

customers can quickly turn insights into production-

IC producers can remain competitive.

worthy actions. These rules and procedures are

One company has reported success using an online
infrastructure approach, which reduces latency fromeasy-to-use and accessible across the entire
semiconductor value chain.

hours or days to milliseconds or microseconds. Theapproach enables on-the-fly ML scoring an decisionmaking while maintaining secure communication.

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Figure 3. A real-time test-data platform can eliminate the hours or days
otherwise necessary to perform corrective actions.

Figure 4. ACS, AI and data analytics add value to the evolving
semiconductor value chain.

THE BENEFITS OF ADVANTEST ACSACS RTDI acts as a communication backplane for

Given that the current testing approach is costly,

information exchange. It supports online edge

cumbersome, and time-consuming, the industry
needs a new paradigm. To address this need,
Advantest has created the industry’s first RealTime Data Infrastructure (RTDI)―an innovative,revolutionary approach to providing analysis andcorrective analysis and action in the evolving testing
environment (Figure 4). Compared to file-based

the test floor to facilitate rapid, secure, and accuratecomputing/analytics to enable real-time adaptive
decision-making within and between touchdowns.
Real-time data monitoring with intelligent data
extraction and control enables the initiation ofcorrective actions within milliseconds.
ACS RTDI includes several specific key features

analysis, online edge-computing analytics are

and technologies:

performed in a secure, True Zero Trust™ environment•that detects issues and applies corrective actions

technology to enable automated softwarein just milliseconds. In this way, ACS RTDI provides

distribution for containerized apps. This productreal-time, adaptive decision-making with solutions

ensures easy, secure, and reliable deployment ofthat are also easy to integrate into any test program,the apps to the test fleet while ensuring seamlessand it enables customers to maximize the Advantest
value chain to deliver improved yield, quality, time-tomarket, and time-to-volume.

The ACS Container Hub™ employs container

integration into the ACS ecosystem.
•ACS Edge™ Server, a high-performance and highly
secure edge-compute and analytics solution, offers
millisecond latencies to facilitate real-time adaptive
decision-making during test execution.

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Unlocking Value: The Power of AI in Semiconductor TestACS Nexus™ provides a standard interface for real-market, more rapid time-to-volume, improved quality

time test-cell data streaming and inline equipment

and reliability. It offers a wide range of capabilities,

control between equipment and external clients

including AI/ML use cases and big-data businessacross all Advantest platforms, enabling inline

cases to optimize the entire semiconductor test life

analytics capabilities, real-time control, and acrosscycle that can be tailored to meet the specific needs

different test stages. It enables applications toof different customers and applications.

maximize yield, optimize throughput, and ensure
test quality without increasing breakdown risk inthe production line.
•ACS Unified Server supports scalable andredundant compute and storage resources toenhance workload management and minimize therisk of downtime while providing True Zero Trust™
security for the test floor and it supports data feed
forward/feedback and also provides transactionlevel security, cross-platform support, multi-party
sharing, and data governance while enabling
packet inspection and transaction logging.

Collectively, these solutions are helping customers
transform data into real-time production control,

Figure 5. A solutions store is a part of the ACS ecosystem.

The solution store provides access to a variety ofadvanced technologies and use cases for AI and ML:•efficiency compared with traditional methods.

delivering excellent results and improved ROI for
their products. Advantest is setting a new standard

Defect detection, with improved accuracy and•

Test optimization, with test conditions such as

in the semiconductor test equipment and test data

voltage and temperature controlled to improveanalytics industries.

testing efficiency and accuracy.

ONLINE SOLUTIONS STORE
To further support ACS’s ground-breaking strategy,
ACS also has an online solutions store (Figure 5)•resources and improved production planning.
•Test data analysis, to extract insights from andidentify patterns in large amounts of data towhere customers can find a comprehensive collection

improve the testing process.

of software designed for the digital age that address
major challenges facing the semiconductor industry.

Yield prediction, allowing for more efficient use of•Parametric testing, to determine the parametric

The store offers a wide variety of ready-madeperformance of semiconductor devices with regard

analytics solutions from multiple providers, enabling

to power consumption, frequency response, andcustomers to achieve higher yields, faster time-to-temperature variation.

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Unlocking Value: The Power of AI in Semiconductor Test

Statistical process control, through monitoring
the production process and identifying patterns
that indicate a potential issue, allowing for early
detection and correction of problems.

•CONCLUSION
Armed with these advanced analytics, including
ML capabilities and future-proof, real-time, automatedproduction control, the ACS Data Solutions ecosystem

Test time reduction, by selecting the most relevant

integrates all data sources across the entire IC

test vectors or by optimizing the test sequence.

manufacturing supply chain, a revolutionary first inACS RTDI USE CASESACS RTDI can serve several use cases. A fabless orIDM user, for example, could use it to make smarter
real-time decisions at various insertion points: wafer
sort, final test, and system-level test. As anotherexample, an OSAT could use RTDI and its True Zero
Trust™ Security to share data with fabless customers

the industry.
By pushing the limits of what is possible, Advantest is
driving test performance to new heights by elevating
its edge and data infrastructure services. Advantest
is augmenting data analytics and empowering AI andmachine learning solutions so customers accomplish
data-driven workflows.

while avoiding storing data in a publicly accessible
network.
Some specific functions that ACS RTDI can provide
include real-time checks of trim value shifts that canindicate equipment issues and smart chiplet pairing
to match the specifications of multiple chiplets in one
package. ACS RTDI can also enable adaptive test
time reduction to optimize cost of test without risking
test escapes, and it can facilitate adaptive test flow.

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REFERENCES
1. First In-Depth Analysis Report 2023, International Business Strategies, Inc. (IBS),
https://www.ibs-inc.net/reports.
2. A. Meixner, “Too Much Fab and Test Data, Low Utilization,” Semiconductor Engineering,January 2021.
3. D. Armstrong, “Device validation: the ultimate test frontier,” Chip Scale Review,November/December 2022, p. 26.
4. R. Swaminathan, “Advanced Packaging: Enabling Moore’s Law’s next frontier throughheterogeneous integration,” AMD, January 6, 2022.
5. S. Mier, “ML in Semiconductor Test,” MEPTEC, November 2021.
https://www.youtube.com/watch?v=nIZ4tTlWIAc“This paper may contain technical information about Advantest test systems that originate in the United States and is controlled
for export by the U.S. Government under the U.S. Export Administration Regulations (at 15 C.F.R. Parts 730-774). Accordingly,
any export, reexport, or transfer (in-country) of this paper or any part thereof may be subject to those regulations and prohibitedwithout first obtaining approval from the U.S. Government or as otherwise authorized by U.S. law and regulations.”

ADVANTEST CORPORATION
United States Headquarters, Advantest America, Inc.
3061 Zanker Road, San Jose, CA 95134
www.advantest.com© 2023 Advantest CorporationMay 2023

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