From Data to Insights: How IT Operations Data Can Boost QualityCognizant
By leveraging highly-analyzed operational data - the voice of customers, machines and tests - quality assurance (QA) and IT groups can derive major gains in quality of apps and in user experience.
Surprising Discoveries and Key Takeaways on Warehouse EfficiencyIvanti
See what nearly 150 global warehouse technology leaders are saying about their mobile applications and OS migration plans. VDC Research and Ivanti are teaming up to break out the surprise findings from VDC’s new research report, along with the key trends you need to focus on in order to keep pace with warehouse demands. Join us for this 10 slide, 35 minute webinar featuring VDC Research’s Eric Klein and learn:
The top warehouse improvement initiatives for 2018, key factors driving new investment in mobile warehouse solutions, what warehouse decisiion makers are saying about app migration, and nine key takeaways to keep in mind for future growth.
In today’s globalized, competitive marketplace, being able to leverage technology to deliver faster turnaround times, meet lower pricing goals and provide customizable options can mean the difference between sustainability and irrelevancy. In this ebook, we’ll explore some of the leading solutions transforming the manufacturing industry:
- Automation for cost savings
- 3D printing for improved productivity
- Smart data for quality assurance
- Connectivity for safety and communication
- Security solutions to protect it all
Learn more: http://ms.spr.ly/6006Twegg
Enterprise Business Intelligence & Data Warehousing: The Data Quality ConundrumRTTS
RTTS recently performed a study of over 200 companies interested in improving the data quality of their Data Warehouse and Business Intelligence projects.
Our firm interviewed IT executives, data architects, ETL developers, data analysts and data warehouse testers to determine the state of the industry and current practices as they relate to data quality.
Highlights from the research:
- Oracle dominates the data warehouse industry with 42% of all installs.
- IBM is the leader in BI tools, with IBM Cognos owning 22% of the industry.
- Microsoft (22%) shockingly passed Informatica (19%) in the ETL tools section, but open source and home-grown tools (25%) are ahead of Microsoft.
- The majority of data warehouse installs (33%) are between 1 and 100 terabytes.
- 60% of companies surveyed test their data manually.
Read the results of the study, including details on the state of the industry and current practices as they relate to data quality.
The Value-driven Approach to Digitalizing Assets and their Supply ChainsYokogawa1
Facilities must pursue the agile optimization of feedstocks and other inputs with products and operations to reflect market demand and prices. This is how the demand-pull business model is achieved and a measurable change in profitability delivered. This presentation will showcase why a mindset shift to value chain optimization is needed, as well as the deliberate approach needed to digitally transform value chain optimization activities. The value chain digital twin combining traditional solutions and AI will be profiled, along with the first steps that need to be taken, now.
Mars Presentation at the Supply Chain Insights Global Summit 2018Lora Cecere
Mars Franklin committed in 2017 to build a program to improve customer service and become demand driven. In this presentation, John Wisniewski, program manager for digital transformation, share candid insights on the implementation.
From Data to Insights: How IT Operations Data Can Boost QualityCognizant
By leveraging highly-analyzed operational data - the voice of customers, machines and tests - quality assurance (QA) and IT groups can derive major gains in quality of apps and in user experience.
Surprising Discoveries and Key Takeaways on Warehouse EfficiencyIvanti
See what nearly 150 global warehouse technology leaders are saying about their mobile applications and OS migration plans. VDC Research and Ivanti are teaming up to break out the surprise findings from VDC’s new research report, along with the key trends you need to focus on in order to keep pace with warehouse demands. Join us for this 10 slide, 35 minute webinar featuring VDC Research’s Eric Klein and learn:
The top warehouse improvement initiatives for 2018, key factors driving new investment in mobile warehouse solutions, what warehouse decisiion makers are saying about app migration, and nine key takeaways to keep in mind for future growth.
In today’s globalized, competitive marketplace, being able to leverage technology to deliver faster turnaround times, meet lower pricing goals and provide customizable options can mean the difference between sustainability and irrelevancy. In this ebook, we’ll explore some of the leading solutions transforming the manufacturing industry:
- Automation for cost savings
- 3D printing for improved productivity
- Smart data for quality assurance
- Connectivity for safety and communication
- Security solutions to protect it all
Learn more: http://ms.spr.ly/6006Twegg
Enterprise Business Intelligence & Data Warehousing: The Data Quality ConundrumRTTS
RTTS recently performed a study of over 200 companies interested in improving the data quality of their Data Warehouse and Business Intelligence projects.
Our firm interviewed IT executives, data architects, ETL developers, data analysts and data warehouse testers to determine the state of the industry and current practices as they relate to data quality.
Highlights from the research:
- Oracle dominates the data warehouse industry with 42% of all installs.
- IBM is the leader in BI tools, with IBM Cognos owning 22% of the industry.
- Microsoft (22%) shockingly passed Informatica (19%) in the ETL tools section, but open source and home-grown tools (25%) are ahead of Microsoft.
- The majority of data warehouse installs (33%) are between 1 and 100 terabytes.
- 60% of companies surveyed test their data manually.
Read the results of the study, including details on the state of the industry and current practices as they relate to data quality.
The Value-driven Approach to Digitalizing Assets and their Supply ChainsYokogawa1
Facilities must pursue the agile optimization of feedstocks and other inputs with products and operations to reflect market demand and prices. This is how the demand-pull business model is achieved and a measurable change in profitability delivered. This presentation will showcase why a mindset shift to value chain optimization is needed, as well as the deliberate approach needed to digitally transform value chain optimization activities. The value chain digital twin combining traditional solutions and AI will be profiled, along with the first steps that need to be taken, now.
Mars Presentation at the Supply Chain Insights Global Summit 2018Lora Cecere
Mars Franklin committed in 2017 to build a program to improve customer service and become demand driven. In this presentation, John Wisniewski, program manager for digital transformation, share candid insights on the implementation.
PreScouter + GE Healthcare: How will the Internet of Things Impact your Indus...PreScouter
PreScouter and GE Healthcare partnered to analyze how they are researching Internet of Things technology. The presentation begins with a note from Dr. Ashish Basuray, Chief Scientist at PreScouter, Inc., an innovation consulting firm. Basuray addresses a fundamental question: why do we care to learn about new ideas, disruptive ideas like the Internet of Things? Following Basuray's introduction, Bill Shingleton, Ph.D., Technical Lead at GE Healthcare presented on the Industrial Internet of Things and how it impacts several industries. But, then he narrowed in on healthcare and GE's solution, Predix. This is the slide deck of the presentation for PreScouter's IoT Summit on October 6, 2016, from 5 -8 pm at the Schreiber Center in downtown Chicago.
For more information on disruptive technology, please visit: www.prescouter.com.
For Life Sciences, the Future of Master Data Management is in the CloudCognizant
Cloud-based MDM is cost-effective and easily implemented; it is scalable, robust and mature; and it has the flexibility required to enable and support the evolving transformation of life sciences commercial operations.
INTIENT Pharmacovigilance equips companies with a centralized platform to collect, manage and learn from the entire spectrum of patient safety data, embedding artificial intelligence, machine learning, robotic process automation and advanced analytics in each step. Visit https://accntu.re/2vTyhY5 to learn more.
Using the ISBSG data to improve your organization success - van Heeringen (Me...Harold van Heeringen
This presentation gives an introduction into the ISBSG organization and shows how the ISBSG products and data can help the software industry to become more mature. Three cases from personal experience are showed: a reality check of an expert estimate (that turned out to be optimistic), the analysis of the outgoing bids of a software supplier and the measurement of the performance of a single supplier, providing target productivity levels they should reach.
Applying Technologies Across the End-to-End Pharmacovigilance Process to Incr...MyMeds&Me
MyMeds&Me CEO Andrew Rut and Oracle Health Science's Director of Safety Analytics, Michael Braun-Boghos review the positive impacts of technology on current pharmacovigilance processes.
AstraZeneca: A Vision for a Collaborative Clinical EnvironmentVeeva Systems
Slides from AstraZeneca's 2019 Veeva R&D Summit presentation.
After receiving the 2018 Eagle Award for the best sponsor by the Society for Clinical Research Sites (SCRS), AstraZeneca is on an ongoing quest to remain a sponsor of choice for 2019 and beyond. Learn how they are leveraging technology, a unified clinical trial platform, and other strategies to simplify trial conduct at sites.
Electrical distributors have been collecting data on product sales and customer orders for years now. But, technology now allows for the collection, synthesis and analysis of information like never before. Under the guise of Big Data, many industries are planning and even projecting outcomes. Most distributors are only utilizing ERP data, but at what cost? This white paper walks through how members of the electrical distribution channel can plan and execute big data projects to maximize not only sales, but also stock, logistics and customer satisfaction.
Enabling Better Clinical Operations through a Clinical Operations StoreSaama
Srini Anandakumar, Senior Director of Clinical Analytics Innovation for Saama, presented at the Big Data and Analytics in Pharma in Philadelphia, November 1, 2017.
Formlabs Uses Supplier Development to Outpace CompetitorsLora Cecere
3D Printing technologies are quickly evolving? How did Formlabs outpace competitors? They used supplier development techniques to build and orchestrate a network to drive differentiation.
Jade Global with Oracle NetSuite Give Life Sciences Companies the Gift of Spe...Amber Wallace
By combining #cloudERP with industry-specific #lifesciences #digitaloperationsplatform, #lifesciences firms can accelerate now versus later @NetSuite #JadeGlobal. Download Whitepaper: https://jadeglobal.co/3Db0RVj
#erp #digitaltransformation #prerevenuelifesciences #pharmaceuticals #healthcare
Ms. Christine Summers - Antibiotics and Animals Building Consumer TrustJohn Blue
Antibiotics and Animals Building Consumer Trust - Ms. Christine Summers, Costco, from the 2015 NIAA Antibiotic Symposium - Stewardship: From Metrics to Management, November 3-5, 2015, Atlanta, Georgia, USA.
More presentations at http://swinecast.com/2015-niaa-symposium-antibiotics-stewardship-from-metrics-to-management
PreScouter + GE Healthcare: How will the Internet of Things Impact your Indus...PreScouter
PreScouter and GE Healthcare partnered to analyze how they are researching Internet of Things technology. The presentation begins with a note from Dr. Ashish Basuray, Chief Scientist at PreScouter, Inc., an innovation consulting firm. Basuray addresses a fundamental question: why do we care to learn about new ideas, disruptive ideas like the Internet of Things? Following Basuray's introduction, Bill Shingleton, Ph.D., Technical Lead at GE Healthcare presented on the Industrial Internet of Things and how it impacts several industries. But, then he narrowed in on healthcare and GE's solution, Predix. This is the slide deck of the presentation for PreScouter's IoT Summit on October 6, 2016, from 5 -8 pm at the Schreiber Center in downtown Chicago.
For more information on disruptive technology, please visit: www.prescouter.com.
For Life Sciences, the Future of Master Data Management is in the CloudCognizant
Cloud-based MDM is cost-effective and easily implemented; it is scalable, robust and mature; and it has the flexibility required to enable and support the evolving transformation of life sciences commercial operations.
INTIENT Pharmacovigilance equips companies with a centralized platform to collect, manage and learn from the entire spectrum of patient safety data, embedding artificial intelligence, machine learning, robotic process automation and advanced analytics in each step. Visit https://accntu.re/2vTyhY5 to learn more.
Using the ISBSG data to improve your organization success - van Heeringen (Me...Harold van Heeringen
This presentation gives an introduction into the ISBSG organization and shows how the ISBSG products and data can help the software industry to become more mature. Three cases from personal experience are showed: a reality check of an expert estimate (that turned out to be optimistic), the analysis of the outgoing bids of a software supplier and the measurement of the performance of a single supplier, providing target productivity levels they should reach.
Applying Technologies Across the End-to-End Pharmacovigilance Process to Incr...MyMeds&Me
MyMeds&Me CEO Andrew Rut and Oracle Health Science's Director of Safety Analytics, Michael Braun-Boghos review the positive impacts of technology on current pharmacovigilance processes.
AstraZeneca: A Vision for a Collaborative Clinical EnvironmentVeeva Systems
Slides from AstraZeneca's 2019 Veeva R&D Summit presentation.
After receiving the 2018 Eagle Award for the best sponsor by the Society for Clinical Research Sites (SCRS), AstraZeneca is on an ongoing quest to remain a sponsor of choice for 2019 and beyond. Learn how they are leveraging technology, a unified clinical trial platform, and other strategies to simplify trial conduct at sites.
Electrical distributors have been collecting data on product sales and customer orders for years now. But, technology now allows for the collection, synthesis and analysis of information like never before. Under the guise of Big Data, many industries are planning and even projecting outcomes. Most distributors are only utilizing ERP data, but at what cost? This white paper walks through how members of the electrical distribution channel can plan and execute big data projects to maximize not only sales, but also stock, logistics and customer satisfaction.
Enabling Better Clinical Operations through a Clinical Operations StoreSaama
Srini Anandakumar, Senior Director of Clinical Analytics Innovation for Saama, presented at the Big Data and Analytics in Pharma in Philadelphia, November 1, 2017.
Formlabs Uses Supplier Development to Outpace CompetitorsLora Cecere
3D Printing technologies are quickly evolving? How did Formlabs outpace competitors? They used supplier development techniques to build and orchestrate a network to drive differentiation.
Jade Global with Oracle NetSuite Give Life Sciences Companies the Gift of Spe...Amber Wallace
By combining #cloudERP with industry-specific #lifesciences #digitaloperationsplatform, #lifesciences firms can accelerate now versus later @NetSuite #JadeGlobal. Download Whitepaper: https://jadeglobal.co/3Db0RVj
#erp #digitaltransformation #prerevenuelifesciences #pharmaceuticals #healthcare
Ms. Christine Summers - Antibiotics and Animals Building Consumer TrustJohn Blue
Antibiotics and Animals Building Consumer Trust - Ms. Christine Summers, Costco, from the 2015 NIAA Antibiotic Symposium - Stewardship: From Metrics to Management, November 3-5, 2015, Atlanta, Georgia, USA.
More presentations at http://swinecast.com/2015-niaa-symposium-antibiotics-stewardship-from-metrics-to-management
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Semiconductor manufacturing is a complex, high-tech process that generates a large volume of data. Utilizing this data effectively is critical for improving production yield, maintaining product quality, and driving efficiency across operations. Enter big-data analytics. While the term “big data” often refers to vast data sets that are too large for traditional data-processing tools to handle, its importance in the semiconductor manufacturing industry can't be understated. Big-data and yield analytics not only provides ways to process, analyze, and draw insights from these large volumes of data but also facilitates more efficient decision-making, informed by detailed, real-time data insights.
Revolutionizing the Manufacturing Industry.pdfeinnosys
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We live in a data-rich world - almost everything we do is being captured and stored somewhere. There are algorithms crunching the data every millisecond and conveying unknown and untapped information. At an enterprise level, data analytics provides us a 360-degree view of our customers, products and the business landscape to make effective, smart decisions. This presentation delves into how the traditional business philosophy of ‘proximity to customer’ will lose its significance and how data will drive product decisions.
Advanced Manufacturing – Solutions That Are Transforming the IndustryMRPeasy
Advanced manufacturing is on its way to transform the industry. And there are solutions in place already that could help even small manufacturers keep up in the rapidly changing business environments.
1. NI Automated Test Outlook 2016
Smarter devices. Smarter test systems.
2. Table of Contents
05 Harvesting Production Test Data
Semiconductor organizations pioneer real-time data analytics
to reduce manufacturing test cost.
07 Life-Cycle Management Is All About Software
Obsolescence, OS churn, and compatibility challenge long-life-cycle
projects—an age-old problem warrants revisiting.
09 The Rise of Test Management Software
Off-the-shelf test executives are effective solutions for the influx
of new programming languages.
11 Standardizing Platforms From
Characterization to Production
RFIC companies employ IP reuse and hardware standardization across
the product design cycle to reduce cost and decrease time to market.
13 Making (mm)Waves in Test Strategy
Test managers are adopting modular solutions to economically
validate high-frequency components.A Technology and Business Partner
Since 1976, companies around the world including BMW, Lockheed Martin, and Sony have relied on NI products
and services to build sophisticated automated test and measurement systems.
Test delivers value to your organization by catching defects and collecting the data to improve a design or process.
Driving innovation within test through technology insertion and best-practice methodologies can generate large
efficiency gains and cost reductions. The goal of the Automated Test Outlook is to both broaden and deepen the
scope of these existing efforts and provide information you need to make key technical and business decisions.
3. Organizational
Test Integration
OptimizingTest
Organizations
Test Economics
Organizational
Proficiency
Testing the
Hybrid Approach
mmWaveTest
Strategies
Business
Strategy
Business
Strategy
ArchitectureArchitecture
ComputingComputing
SoftwareSoftware
I/OI/O
System
Software Stack
Measurements
and Simulation in
the Design Flow
Software-Centric
Ecosystems
ManagedTest Systems
Bridging the
Big Data Chasm
Rise ofTest
Management Software
Heterogeneous
Computing
PCI Express
External Interfaces
Big Analog Data
Cloud Computing
forTest
The Core of
the Matter
Harvesting
ProductionTest Data
IP to the Pin
Proliferation of
Mobile Devices
Test Software Quality
ScalableTest Software
Architecture
Driven by Necessity
Life-Cycle
Management
Portable Measurement
Algorithms
Moore’s Law
Meets RFTest
Redefining the
Notion of Sensors
From 1G to 5G
Characterization to
Production
2011 2012 2013 2014 2015 2016
AUTOMATED TEST OUTLOOK 2016
How We Arrived at the Trends
As a supplier of test technology to more than 35,000
companies each year, we receive a broad range of feedback
across industries and geographies.This broad base creates
a wealth of quantitative and qualitative data to draw on.
We stay up to date on technology trends through
our internal research and development activities.
As a technology-driven company, we invest more
than 16 percent of our annual revenue in RD. But
as a company that focuses on moving commercial
technology into the test and measurement industry,
our RD investment is leveraged many times over
in the commercial technologies we adopt. Thus, we
maintain close, strategic relationships with our suppliers.
We conduct biannual technology exchanges with key
suppliers that build PC technologies, data converters,
and software components to get their outlook on
upcoming technologies and the ways these suppliers
are investing their research dollars. Then we integrate
this with our own outlook. We also have an aggressive
academic program that includes sponsored research
across all engineering disciplines at universities around
the world. These projects offer further insight into
technology directions often far ahead of commercialization.
And, finally, we facilitate advisory councils each year
for which we bring together leaders from test engineering
departments to discuss trends and share best practices.
These councils include representatives from every major
industry and application area—from fighter jets to the
latest smartphone to implantable medical devices.
The first of these forums, the Automated Test Customer
Advisory Board, has a global focus and is
in its 16th year. We also conduct meetings,
called regional advisory councils, around the
world. Annually, these events include over
300 of the top thought leaders developing
automated test systems.
We’ve organized this outlook into five categories
(see above figure). In each of these categories,
we highlight a major trend that we believe will
significantly influence automated test in the
coming one to three years. We update the trends
in these categories each year to reflect changes
in technology or other market dynamics. We
will even switch categories if the changes are
significant enough to warrant it.
As with our face-to-face conversations on
these trends, we hope that the AutomatedTest
Outlook will be a two-way discussion. We’d
like to hear your thoughts on the industry’s
technology changes so we can continue to
integrate your feedback into this outlook as
it evolves each year. Email ato@ni.com or
visit ni.com/test-trends to discuss these
trends with your peers.
4. OPTIMAL+ BIG DATA INFRASTRUCTURE USING NI STS
Optimal+
Portal
MANUFACTURING FACILITIES
NI STS NI STS NI STS Proxy Server
Test Data
Commands and Control
The explosion of Internet of Things devices will
further challenge companies’ capabilities: products
are becoming more complex while quality expectations
soar, which causes test programs and the data they
generate to increase exponentially in size; data is
collected from geographically dispersed sources and
processes; and RMA prevention requires the retention
of data for months and even years. However, all is not
lost. Leading semiconductor companies are pioneering
a multifaceted big data analytics strategy to improve
product yields, prevent escapes, and streamline RMA
management. This groundwork is creating a blueprint
for how manufacturing test organizations in other
industries can realize the benefits of data analytics.
Collection and Detection
Providing a solid foundation for big data analytics
in manufacturing operations presents two primary
challenges. The first is collecting data from the
tester in a standardized format and quickly delivering
it, regardless of where that tester is located. Most
semiconductor vendors have supply chains composed
of separate companies in different countries conducting
manufacturing, assembly, and test. This often prevents
product teams from gaining rapid access to clean,
consistent test data. A standardized approach to collecting
data across a global supply chain is necessary for
companies to best leverage the knowledge contained
within that data.
The second challenge is storing data for long periods
of time and ensuring it is readily accessible for detailed
analysis. For companies involved in market segments
that demand high-quality electronic products, processes
that can help limit test escapes, rapidly resolve field
failures, and manage RMAs are critical. These processes
have generated a greater need for engineering operations
to work closely with IT to plan how global test data is
managed. Will the data be stored on-site, in the cloud,
or some combination of the two? Big data solutions
need to store and provide rapid access to enormous
quantities of information (tens to hundreds of terabytes)
and help teams accomplish tasks in the most efficient
way possible.
From Reactive to Proactive
Access to data in real time helps solve many problems
but only if a user can quickly mine that data. Data by
itself is meaningless until it is analyzed. And in the
case of semiconductor manufacturing data, much
of that value is time-sensitive. The faster a user can
analyze data, the more valuable the analysis results.
In many industries, data mining is a “reactive” process.
Something goes wrong (for example, too many field
failures), so a product team starts to analyze data to
determine the problem, correct it, and then put steps
in place to keep it from happening again. But in many
cases, the damage is done, either in terms of a product
recall or a negative impact on product revenue or even
the market valuation of a company. The challenge is
catching these problems early enough to mitigate them.
One of the major benefits of big data analytics is
being “proactive” in automatically analyzing, in minutes,
any amount of data 24 hours a day. In semiconductor
manufacturing, engineers can embed their knowledge
into automated rules engines that mine data 24/7, search
for manufacturing issues, and provide immediate alerts.
Acting on Data
Eliminating the “find a needle in a haystack” problem
is a paradigm shift for product and yield engineers. It
helps emphasize acting on issues instead of continually
looking for problems and finding them too late to effect
meaningful change.
A simple example is a probe card or load board that
is starting to fail. The immediate effect is usually a drop
in yield. But how long will it take for someone to notice
a problem? In some instances, the problem could go
unnoticed for hours or more. If yield drops 6 percent
during that time, any material tested during that
timeframe is irretrievably lost.
This is where big data analytics comes into play.
Yield engineers can set up a rule that checks for
any statistically relevant drop in yield at any test
site in the entire supply chain. As soon as the rule
is triggered, the rule engine alerts the appropriate
people to take action within minutes and, in this
case, preserve yield entitlement.
This also helps improve quality. One issue that
affects semiconductor device quality is the number
of“touchdowns” during wafer sort. Depending on
the retest policy, in the desire to “pass” a device, a
die may endure too many touchdowns, which puts its
long-term quality and reliability at risk. But if the device
tests as “good,” what can be done to prevent it from
being shipped into the supply chain? Using analytics,
every die from every lot can be evaluated between
wafer sort and final test to see how many touchdowns
it receives. If any given die records more touchdowns
than is deemed acceptable, that die can be rebinned
as “bad” before it goes to assembly or final test, which
removes a highly suspect die from the supply chain.
From Pain Comes Progress
Whatever a company’s pain points may be—yield,
quality, or productivity—big data solutions can help
improve operational metrics by automatically analyzing
manufacturing data based on rules that embody the
complete knowledge and expertise of its operations
teams. Today, many of the world’s largest semiconductor
companies, both IDM and fabless, are leveraging the
power of big data analytics to help them collect, detect,
and act on global manufacturing data and drive yield
and productivity while improving overall quality. This
ultimately increases profit margins and market share.
Harvesting Production Test Data
Every year, semiconductor companies accumulate tens of terabytes
of manufacturing test data whose inherent value and bottom line
impact are lost. And it’s only getting worse.
“Companies like Optimal+ are
delivering on the promise of big data
for semiconductor manufacturing by
providing near real-time ability to analyze
and act on the insights in the data,
lowering the cost of test and improving
the product quality. This trend will only
continue as other industries start to
embrace the benefits of big data.”
—Mike Santori, Business and Technology Fellow, NI
ni.com/ato 05
AUTOMATED TEST OUTLOOK 2016
Article contributed by:
David Park, Vice President of Worldwide Marketing, Optimal+
5. 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
0
400
800
1200
1600
2000
REVENUE(MILLIONSUSD)
PXI REVENUE VXI REVENUE AXIe REVENUE
INNOVATION AND STABILITY MAKE PXI THE STANDARD PLATFORM FOR AUTOMATED TEST
simply opening, saving, and revalidating a test program
set (TPS), or test sequence, can cost hundreds of
thousands of dollars. This has created an environment
where companies must rethink their software
strategies or risk hemorrhaging money to sustain
legacy testers.
Since minor software changes can greatly impact
TPS compatibility, instrument vendors should offer
TPS-compatible hardware migration options. This
includes preserving driver functionality, APIs, and
dependencies between driver versions to minimize the
impact on the hardware abstraction layer. For example,
NI is collaborating with Astronics Corporation to bring
remaining VXI instruments into the PXI platform, such
as the Astronics PXIe-2461 frequency time interval
counter, which preserves TPS compatibility with
legacy systems. Despite their best efforts, vendors
cannot always provide TPS-compatible alternatives.
In these situations, a common approach is emulating
legacy instrument functionality. Recently, engineers
have adopted software-designed instruments with user-
programmable FPGAs to augment standard instrument
capabilities with custom functionality to emulate legacy
behavior. For example, filters and triggers that were
common in instruments 20 years ago and obsolete
in today’s instruments can be reengineered.
Coming Full Circle
Whether you’re managing the B-52 bomber platform
or introducing a new line of infotainment systems
for the connected car, life-cycle management is
critical. It can be either an expensive afterthought
or a competitive advantage. In the face of market
dominance of mobile technologies, the accelerated
decay of legacy instrumentation, and the rising costs
of software validation, scalable test architectures and
strategies will distinguish best-in-class organizations.
One of the largest operational costs associated with
automated test systems, especially in the aerospace
and defense industry, is the support and maintenance
cost over the life of the system. Proactive life-cycle
management requires designing maintainable testers,
diligently monitoring automated test equipment (ATE),
and tracking instrument and component
end-of-life (EOL) notifications.
While life-cycle management might not be a novel
concept, the reality is that the evolution of mobile
technology, accelerated hardware obsolescence, and sheer
volume of test software are making this task increasingly
difficult. Best-in-class organizations are rearchitecting
test strategies to gain a competitive advantage amid the
growing challenge of life- cycle management.
Evolution of OS Life Cycles
Within a decade, OS providers have transitioned from
releasing a single OS and maintaining it for several
years, such as Microsoft Windows XP (which was
supported for 13 years), to today’s paradigm that
targets mobile users that expect constant upgrades.
This requires OS providers to frantically release new
versions and retroactively fix bugs in daily updates.
Global market intelligence firm IDC forecasts that
smartphones and tablets will control 88.4 percent of
the smart-connected device market by 2019, leaving
portable and desktop PCs with only 11.6 percent.
As mobile devices control vast majority of the market,
OS providers will continue to prioritize the mobile user.
This shift poses a monumental hurdle for test systems
that rely on a stable OS to eliminate the need for system
revalidation. As a result, some organizations are moving
to Linux-based systems to have more control over
the OS. Another approach is to minimize the number
of OSs to reduce the burden for test engineering and
IT organizations. Many legacy test systems contain
several OSs (one for each unique box instrument),
which introduces the risk of revalidation due to individual
OS updates. One major benefit of modular platforms,
such as VXI or PXI, is the single OS controlling all
instruments in the chassis or system.
Accelerated Decay of VXI
and Legacy Instruments
In the late 1980s and early 1990s, the aerospace
and defense community standardized on VXI as
the modular commercial off-the-shelf platform for
ATE systems. However, as VXI grows obsolete and
support diminishes for legacy instruments, programs
are under increased pressure to migrate to a stable
alternative. This is compounded by a looming RoHS
conversion deadline, which will increase the rate
of component and instrument EOLs.
Over the past decade, PXI has replaced VXI as the
de facto modular platform for ATE systems due to the
size, performance, cost, and level of innovation in the
platform. Global consulting firm Frost Sullivan expects
PXI to grow by 17.6 percent annually, which accounts
for most of the expected growth for the test and
measurement industry. With nearly 70 vendors offering
more than 1,500 PXI instruments and a steady stream
of innovation, PXI will continue to provide increased
value to long-life-cycle ATE systems.
TPS-Compatible Migration Paths
As teams migrate from VXI-based to PXI-based
test systems, the investment required to modernize
hardware will typically pale in comparison to that
of updating and revalidating software. Due to the
criticality of the system and the tight regulations
for requirements tracking and software validation,
Life-Cycle Management
Is All About Software
In 2015, the US Department of Defense announced that the
B-52 bomber, originally introduced in 1952, will be in operation
until 2044—a life cycle of nearly 100 years.
“The cost to rewrite a TPS due to the replacement of legacy/obsolete instrumentation
in a test system is approximately $150k/TPS. When multiplied across dozens of TPS
per test system and three to five generations of test equipment over the life of a test
system, the potential savings in TPS costs alone are very significant—any efforts
that vendors can make to smooth this transition will prove to be invaluable.”
—David R. Carey, PhD, Associate Professor of Electrical Engineering, Wilkes University
Source: Frost Sullivan
ni.com/ato 07
AUTOMATED TEST OUTLOOK 2016
6. HETEROGENEOUS TEST DEVELOPMENT APPROACHES
Python C LabVIEW .NET FORTRAN
C
VS.
Python LabVIEW .NET FORTRAN
TEST MANAGEMENT SOFTWARE
organizational whiplash. This can be a costly exercise
that often requires code migration, revalidation of the
codebase, and additional training in the new language.
The best test managers must look to a newer
approach to test-system development that builds
a heterogeneous system out of multiple languages.
This kind of approach allows a team to use multiple
languages, each for its own advantages, to build more
powerful test systems. For instance, Python could
be used for scripting validation and verification tests
based on code developed by RD engineers. In the
same system, C# could be used to develop an object-
oriented interface for custom hardware or to existing
.NET libraries while LabVIEW communicates with and
gathers data from hardware. Since all languages are
designed to tackle specific applications, using each
to its strengths would ultimately save time and money.
Though beneficial, this approach can present a new
challenge to test system development: different
languages now need to work and communicate together
to form a single system. To resolve this, all test engineers
need to understand not just the one environment they
specialize in but also the others to adequately interface
with them.
The Software Solution
Test departments are now turning to commercial
off-the-shelf test management software to act
as a Rosetta Stone of sorts between different
languages. This software not only offers users a
common environment in which they can work with
any type of test code but also completes executive
tasks, such as sequencing and calling each test,
handling data logging, and generating reports. Each
engineer can then focus on writing the best test for
each component of the DUT without needing to worry
about how to communicate with the other portions
of code. And since engineers can use the environments
they are most comfortable with, an organization can
focus on hiring engineers with skills unique to its
applications, even if they don’t have prior knowledge
of, or training in, the company’s required language.
Additionally, test managers can take advantage
of the full power of a heterogeneous design while
avoiding the new challenges that such a design
introduces. This includes the use of test management
software for a more modular development process,
which produces a system that’s easier to maintain
and upgrade because each component can be updated
individually without affecting the rest of the test system.
Ultimately, test executives typically include the
support of commercial vendors that continually
patch and upgrade the test software, which further
offsets the cost of maintenance and increases the
sustainability of these systems. These advantages,
combined with the benefits of a heterogeneous test
system design, are how the best test managers are
building the future of automated testing.
So how did we get here? The evolution is rooted deeply
in the history of programming languages and the thirst
for higher levels of abstraction, and it starts with the first
high-level programming language, FORTRAN. Developed
in 1953 by John Backus, FORTRAN addressed the need
for a greater level of abstraction for machine processes
built around the way that humans naturally communicate
their ideas—through language.
After the success of FORTRAN, more languages like
C, Pascal, ATLAS, and PAWS were developed, each
bringing new constructs and models of computation.
And with each new language came more powerful
levels of abstraction, such as object-oriented
programming, which is now one of the most widely
used programming constructs. In addition, these
newer models of computation often are developed
to solve common problems. Some of these newer
models of computation are developed for general-
purpose programming tasks, but some are developed
for a particular application. For example, LabVIEW
was developed for test, measurement, and control
applications, and Python was developed for quick
code-scripting tasks.
These increasing levels of abstraction result in languages
better suited to specific tasks. The best test managers
now design test systems that leverage the power of
multiple languages and save development time by
using test management software.
Traditional Test System Development
Considering that software is the backbone of
automation when building a test system, many
organizations prefer to standardize on a single,
fairly general language used for all aspects of test
system design from individual component tests to
test management across the board. The end result
is the development of a homogenous test software
approach. The main advantage is all members of a
team can work in a single, standardized environment,
which allows easier sharing of libraries and code
modules across the team. The training for this
approach is also greatly simplified since the team
learns and works in a single environment.
However, standardizing on one language does present
some disadvantages. Using a single language can limit
new hires to a certain skillset or force new employees
into learning new tools. This topic of building a skilled
workplace was explored in NI’s Automated Test Outlook
2014. As students graduate, they often have a preference
for and experience in one or more specific languages.
Also, as new managers take over, they commonly opt
to implement a language of their choice, which causes
The Rise of Test Management Software
Look around your test group. If you are like most organizations that
have conducted automated test for a while, you’re probably seeing
an increase in languages. Thanks to more specialized forms of
abstraction in today’s higher level programming languages, this
problem is not going away anytime soon. It is only intensifying.
“We approach unique test challenges
with the best language for each task at
hand. By using commercial off-the-shelf
test management software to act as a
grand unifier during the whole product
life cycle, we greatly increase our
engineering productivity and minimize
the time to market.”
— Simon Wiedemer, Head of Automated Testing Architecture,
Festo AG Co. KG
ni.com/ato 09
AUTOMATED TEST OUTLOOK 2016
7. ACCELERATED PRODUCT DEVELOPMENT THROUGH STANDARDIZATION
Time to Market
Correlate
Results
Test
DUT
Choose
Hardware
Write
Software
Characterization
Verification and Validation
Preproduction
High-Volume Manufacturing
Characterization
Verification and Validation
Preproduction
High-Volume Manufacturing
STANDARDIZEDTRADITIONAL
Two decades later, a quad-band “world phone” costs a few
hundred dollars. Even a basic mobile phone that supports
over 20 cellular bands, in addition to Bluetooth, Wireless
LAN, and GPS technology, retails for under $100 today.
While this dramatic drop in price has significantly
benefited consumers, it has created substantial
challenges for those supplying the RF components
inside. According to a recent Databeans analyst forecast,
the cost of radio frequency integrated circuits (RFICs) for
mobile devices has dropped by more than 40 percent
since 2007. This price decrease is coupled with the
challenge of rising device complexity. Ten years
ago, a single-function GSM power amplifier was
the norm. Today, many RFICs are significantly more
complex. They support multiple radio standards and
multiple bands with more advanced technologies
such as dynamic power supplies, MIPI digital
interfaces, and more.
To maintain margins while the average sales price shrinks,
companies must reduce the cost of semiconductor
design and test. Given that test cost is often nearly half
of the cost of goods sold, according to IC Insights, RFIC
suppliers have a renewed focus on decreasing the cost
of manufacturing test.
Over the past decade, this intense focus has produced
a significant shift from using turnkey ATE solutions to
building in-house and cost-optimized testers based on
off-the-shelf instrumentation. The ability to specify a
tester for a specific IC device—along with improvements
in instrumentation technology—can significantly reduce
test cost. This shift to a custom tester approach has been
a large factor in the success of modular instrumentation
platforms like PXI in manufacturing particularly because
modular instruments have shown excellent value
per performance.
Competition and Innovation
Increase Pressure on Cost
As intense market competition and an ever-accelerating
pace of wireless innovation complicate the desire for
lower costs, recognizing that these forces require shorter
product release cycles for companies to stay competitive
is important. With much of their manufacturing test costs
already reduced through the use of modular instruments,
organizations must find new ways to improve the
efficiency of product development.
Once considered the holy grail of product development,
one increasingly important practice is to shorten the
product design cycle with standardized design and test
tools. In the past, product development teams often used
different design and test practices and equipment in each
phase of product development. With this approach, the
engineer validating silicon and the engineer designing
the manufacturing test plan were often left to design
their own tester from the ground up.
To be profitable, companies must improve efficiency
between each phase of the product development cycle.
As a result, many companies are adopting integrated
Standardizing Platforms From
Characterization to Production
In 1983, the first commercial mobile phone retailed for $3995,
almost $10,000 in today’s economy. It supported a single band,
weighed almost a kilogram, and was about the size of a brick.
ni.com/ato 11
platform approaches to help reduce total test costs as
well as shorten time to market. As the 2015 McClean
Report says, organizations must place greater effort into
“decreasing IC design, development, and fabrication
expenditures in order for the industry to maintain its
continuous reduction in cost per function.”
Although the desire to use a common test platform
from design to test is not new, innovations in test
equipment are now making that possible. A decade
ago, the test equipment engineers might have used in
their characterization labs was simply not fast enough
for high-volume manufacturing test, and using different
tools throughout the product life cycle was a necessity.
Today, PXI instruments offer the measurement
accuracy required for RD and the speed required
for manufacturing test. As a result, organizations are
increasingly standardizing on modular instrument
platforms throughout the entire design cycle, which
directly reduces the cost associated with correlating
measurement results. In addition to the improved speed
and measurement quality of PXI, application-specific
systems, such as the NI Semiconductor Test System,
build on the PXI platform by adding a rugged enclosure,
fixturing, DUT control, and the turnkey software required
for the semiconductor manufacturing environment.
Mergers and Acquisitions Drive Standardization
Other factors driving the need to standardize on common
design and test platforms are mergers and acquisitions
within the semiconductor industry. Although the
consolidation of suppliers enables companies to address
a larger set of components in a particular mobile device,
it uniquely impacts the engineering teams responsible
for delivering products to market.
This impact is usually caused by merging geographically
distributed engineering teams that have their own
preferences in programming languages, test strategy,
and tool investments. Product development inefficiency
often emerges when distributed teams do not share
common best practices.
As a result, many organizations are in the midst of
standardization. One critical focus is using a single
codebase from automated measurements in RD
to automated measurements in manufacturing test.
By sharing a common codebase of test software,
along with using the same core measurement technology
throughout the design cycle, organizations have reduced
test software development cost and ultimately decreased
time to market.
Status Quo Leaves Money on the Table
Just as the digital age commoditized digital
IC, the information age is commoditizing analog IC.
Commoditization comes with lower cost, and it requires
a dramatically new approach to test. In an era where
test strategy is considered a competitive advantage,
organizations are using standardization on a common
platform as a method to reduce test costs. However,
if an organization is not considering a common platform
approach for test, it might be in trouble. Although the
old way is sometimes easier, the additional cost and
inefficiency leave company profits on the table.
AUTOMATED TEST OUTLOOK 2016
“…greater effort is being placed on
decreasing IC design, development,
and fabrication expenditures in order for
the industry to maintain its continuous
reduction in the cost per function.”
—The McClean Report 2015, IC Insights
8. In addition, the proposed study of frequencies ranging
from 24 GHz to 86 GHz from World Radiocommunication
Conference 2015 shows the importance of mmWave
frequencies for use in 5G wireless communications.
The benefits of extending communications networks to
mmWave are derived from the physical characteristics of
operating at such high frequencies. These include greater
spectrum efficiency from wider bandwidth signals,
shorter wavelengths that require smaller component
dimensions and allow more antennas to be packed
into the same space, and the ability to handle larger
network capacity and better isolation of simultaneous
users. Consumers reap material benefits but RFIC
manufacturers face new challenges when they cannot
directly transfer the methodologies used to test previous
standards. Leading RFIC manufacturers will have to adopt
modular hardware and scalable software to test mmWave
frequencies successfully both financially and technically.
The Impact on Business Strategy
The substantial benefits of mmWave technology
in consumer applications point to a complex and
economically challenging portfolio of RFIC designs
necessary to serve a variety of niche applications.
RFIC manufacturers are now thinking about economies
of scope as well as economies of scale. Semiconductor
manufacturers must either institutionalize the reuse of
common functional elements across multiple designs or
accept lower margins to remain competitive.
Economic considerations are further magnified when
designing for an emerging standard like 5G. Divergent
frequency band proposals from multiple parties generate
uncertainty as to which spectrum will ultimately be
included in the standard. Unless test systems are flexible,
investing before standards are finalized creates a high risk
of sunk costs.
To mitigate these high initial costs, manufacturers have
used test methods like “golden DUT” and built-in self-
test. But these low-cost options aren’t enough to fully
validate designs. True metrological rigor must be applied
to ensure that products can be certified and can conform
to specifications and regulations. This can be achieved
only through performance validation using traceable
test instrumentation.
Maintaining test flexibility is difficult because of the
costs of supporting new frequencies and bandwidths
as well as the costs of covering investments made for
frequencies that are ultimately orphaned. Similar to
the functional reuse underlying successful IC design
strategies, investing in the right test system means
investing in modularity. An economically efficient test
system provides a core platform by isolating functional
components for modulation, demodulation, data
movement, and processing. This platform can be paired
with the appropriate extension to reach the frequency
of choice. Such a design allows investing in components
that scale across frequencies. It also helps mitigate the
costs associated with serving various applications and
Making (mm)Waves in Test Strategy
Expectations are high for the integration of millimeter wave (mmWave)
technology into the connectivity and communications protocols defined
by the IEEE and 3GPP. WiGig (802.11ad) is already delivering extremely
high-throughput and low-latency connectivity for numerous applications.
“Millimeter wave research has presented
a myriad of technology proposals, which
continue to evolve, and since frequencies
of operation and bandwidths have not
been finalized, flexible systems for
characterization, VV, and production
testing will prove to be invaluable in
their ability to remain nimble during the
establishment of standards.”
—Amarpal (Paul) Khanna, PhD, IEEE Fellow,
General Chair for IMS 2016, and RD Manager at NI
MODULAR SYSTEMS EASILY SCALE FOR mmWAVE
Sub 6 GHz Sub 6 GHz and mmWave
ni.com/ato 13
Trend Watch 2016
accounting for the uncertainty in 5G development while
offering fully conformant test capability.
Test Challenges: The Lab Versus the Floor
Unlike sub 6 GHz frequencies, antenna dimensions at
mmWave frequencies are quite small. They are often
fabricated as patch arrays bonded to the IC itself, which
makes transmission technologies like beamforming
more economical but challenging to characterize. As
is common in design validation, devices are placed in
anechoic chambers with an array of test antennas in
locations that validate emissions patterns over the air
(OTA). Though OTA test systems are essential for the
complete validation of device performance, difficulty in
ensuring radiated isolation, the need for high-touch test
procedures (reduced throughput, increased cost), and
the physical cost and size may make them unsuitable
for the production floor.
The difficulty in transferring OTA-based test systems
from RD into production makes clear that effective
test solutions must take advantage of core functional
hardware and software platforms and provide flexible
connectivity to the device. Using common core
platforms with different connectivity, manufacturers
can run statistical correlations on the results collected
from high-sample-count OTA tests in the lab. These
results validate radiation patterns under different
beam configurations, with probed results produced by
individual antennas during the same beam configurations.
By using the common back end, manufacturers can
deploy the appropriate front-end solution for each test
scenario without having to invest in a new test system
configuration for each stage of the value chain.
Multifunction Designs Yield
New Test Considerations
Another disruption to old test methods is the integration
of mmWave technologies with other standards to form
a “multiband” wireless system that schedules users
and data more efficiently. Good examples are wireless
routers touting “triband” Wi-Fi, though today they
actually use one and two channels in the 2.4 GHz and
5 GHz unlicensed band, respectively. With the addition
of 802.11ad at 60 GHz, this system will truly be “triband.”
Testing such functionally integrated devices poses
new questions. Do these become single modules that
support all bands in one package? What test points will
be exposed for functional test? Will these modules be
tested at all bands on one station, or will they separate
sub 6 GHz test and 60 GHz test?
Modular platforms like PXI mitigate these scalability
challenges by simplifying new I/O insertion that can
augment existing functionality. In addition, traditional
single-standard systems, which commonly incorporate
LAN buses, do not scale to handle larger waveform sizes
limited by data movement and processing power. For
example, a typical 802.11ad signal requires up to 50X
the data movement capacity as a typical 802.11ac signal.
Unlike traditional systems that quickly grow in size and
cost, modular test platforms like PXI provide a well-
balanced combination of size, cost, and I/O to support
functionally integrated applications. PXI can handle nearly
16 GB/s of throughput today, and, as the underlying bus
and processing technologies continue to evolve, it seems
to be the logical test platform for future test technologies.
Test Strategy = Business Strategy
With the heavy investment in mmWave research for 5G
communications and the remaining uncertainty around the
frequencies that will emerge to support this rollout, it’s clear
that the challenges WiGig RFIC manufacturers face today
will only grow in scope. Savvy organizations will plan test
strategies early through close partnerships with vendors
that can offer flexible test platforms supporting long-term
product strategies. Modular platforms have led the research
of 5G and mmWave technologies and will continue to lead
the charge in test by providing cost-effective, technology-
flexible solutions for the growing complexity of applications
using high-frequency technologies.
AUTOMATED TEST OUTLOOK 2016