High-Speed I/O Testing with the Power of Two

By Dave Armstrong, Director of Business Development, Advantest America, Inc.

As the internet backbone speed continues to spiral upwards, the interface speeds to the devices making up the cloud also continue to scale up. As many of these interface, server and artificial intelligence (AI) devices move both to 112Gbps data rates and multi-chip heterogeneous integrations, the industry is facing an increased need for at-speed testing in order to confirm truly known-good devices (KGDs).  Until now, an elegant, efficient ATE-based solution for conducting these tests hasn’t been available.

In 2018, Advantest and MultiLane, Inc., a leading supplier of high-speed I/O (HSIO) test instruments, began to explore partnering together to provide a single-platform solution leveraging the best capabilities and qualities of both companies. A fast-growing company founded in 2007, MultiLane is based in Lebanon, where CEO and industry veteran Fadi Daou is committed to expanding the tech industry. With more 200 products and over 500 customers, MultiLane’s product and technology portfolio, as well its corporate culture, are highly complementary to Advantest’s.

The concept of the joint solution is straightforward: existing MultiLane instruments are ported to a form factor compatible with Advantest’s V93000 test head extension frame, as illustrated in Figure 1. As the figure shows, the combined solution consists of an Advantest V93000 tester and twinning test head extension from Advantest, to which MultiLane adds power, cooling and a backplane to create the HSIO card cage. MultiLane then takes existing off-the-shelf instruments and re-lays them out for inclusion in the card cage, which sits on top of the V93000 test head. The use of existing instruments is a key aspect because it contributes to lower cost of test while delivering an already proven capability – just in an ATE environment.

Figure 1. The basic components of the Advantest-MultiLane solution combine to create a unique test offering.

Delving down further into the specifics, Figure 2 illustrates the build-up of the solution. On the bottom is a family board – one of two DUT boards in the build-up – which the customer can typically purchase once and reuse for a variety of testing needs. This bottom board routes the V93000 signals being used to the pogo-block segments located in the HSIO card cage just above, which are then routed to the twinning DUT board at the top of the stack. Multiple MultiLane backplane cassettes sit just underneath the DUT board and device socket, enabling the shortest possible interconnect lead length via high-performance coaxial cabling. The number of cassettes is expandable to include as many as 32 digital storage oscilloscope (DSOs) or 32 bit-error-rate tester (BERT) channels.

Figure 2. The photo at left shows the view from the top of the HSIO card cage with the twinning DUT board and MultiLane instruments removed. 

The setup is designed to be highly configurable. High-speed signals are routed from blind-mate wide-bandwidth connectors to the twinning DUT board mounted connectors adjacent to the DUT. These connectors may be either on the top or on the bottom of the twinning DUT board to provide an optimal signal-integrity solution. Putting the connections on the top of the DUT board allows for direct connection to device signals without the need for routing through vias. For probing, the probe is typically installed on top of the DUT board, with the wide-band connections made on the bottom.  Moving the connectors to the bottom allows the probe to be the only thing extending from the top of the DUT board, as required in a wafer-probe environment.

Another configurable aspect of this solution-set is how bias-tees and splitters are utilized. While very wideband components, these circuits always cause some signal attenuation and distortion. Some users prefer to maximize the signal swing and integrity by not including these circuits in the path. Other users have plenty of amplitude and want the added testability afforded by these components to perform DC tests and/or feed low-frequency scan signal through their HSIO. The flexibility of this approach supports both solutions and allows users to change between them on a part-by-part basis.

Multiple instruments broaden capabilities

MultiLane presently has three pluggable instruments available to coordinate with the V93000 and HSIO card cage. The first can accommodate 58Gbps four-level pulse amplitude modulation (PAM4), while the second is twice the frequency at 112Gbps – the “new normal” data rate. The third is a full, four-channel 50GHz bandwidth sampling oscilloscope, integrated into the solution at a cost far lower than that of a standalone scope, with the same capabilities.  

Figure 3. MultiLane instruments are packaged in cassettes for insertion into the HSIO card cage.   

To ensure the platform solution meets customers’ needs and complementary roadmaps, the MultiLane software and tools are tightly integrated with the V93000. MultiLane eye diagrams and scope plots can be brought up in standard V93000 SmarTest tools (see samples in Figure 4). The scope can also analyze results in the frequency domain to provide a distortion analysis, as is typically done on a vector network analyzer (VNA).   

Figure 4a. MultiLane BERT output waveforms shown on the V93000.

Figure 4b. MultiLane DSO measurements shown on the V93000.

Conserving tester resources

A noteworthy capability of the solution is that the entire HSIO card cage and MultiLane instrument assembly can be used on the bench together with the V93000 DUT boards – i.e., they can run independent of the tester. In some cases, it may be possible to add a simple bench power supply and a PC interface to allow some long-running measurements to be made without the V93000. 

Returning the HSIO card cage on the tester, a local PC can also be used to talk to the MultiLane instruments via the internet. For example, the tester’s SmarTest program can be sequenced to an area of interest and pause, at which point a PC can interact with the MultiLane hardware to interactively explore and analyze the results – much like a scope would be used in the old days, only without the need for probing the fine-geometry wide-bandwidth interfaces. This unique capability both improves the utilization of the HSIO Instruments and allows the user’s offline experience, with the device and instruments to be leveraged into the ATE environment thereby improving efficiencies in both locations.   

Bringing it all together

Developing leading-edge test solutions in the 112Gbps area requires close collaboration and involvement with experienced high-speed I/O experts. Working together with our mutual customers, Advantest and MultiLane can leverage the strengths of both companies to help ensure success and provide the full benefits of this truly unique ATE-meets-HSIO test-platform solution.

Did you enjoy this article? Subscribe to GOSEMI AND BEYOND

Semiconductor Test – Toward a Data-Driven Future

By Keith Schaub, Vice President, Marketing and Business Development, Applied Research and Technology Group, Advantest America

Integrating new and emerging technologies into Advantest’s offerings is vital to ensuring we are on top of future requirements so that we are continually expanding the value we provide to our customers. Industry 4.0 is changing the way we live and work, as well as how we interact with each other and our environment.

This article will look at some key trends driving this new Industry 4.0 era – how they evolved and where they’re headed. Then, we’ll highlight some use cases that could become part of semiconductor test as it drives towards a data-driven future. 

The past

To understand where we’re headed, we need to understand where we’ve been. In the past, we tested to collect data (and we still do today). We’ve accomplished tremendous things – optimized test-cell automation, gathered and analyzed yield learnings, process drift and statistical information, to name a few. But we ran into limitations.

For instance, we lacked tools necessary to make full use of the data. Data is often siloed, or disconnected. Moreover, it’s not in a useful format, so you can’t take data from one insertion and use it in another insertion. Not having a way to utilize data for multiple insertions reduces its value. Sometimes, we were simply missing high-value data, or collecting and testing the wrong type of data.

The future

Moving forward, we think what we are going to see is, the data that we collect will drive the way that we test. Siloed data systems will start to be connected, so that we can move data quickly and seamlessly from one insertion to another – feeding the data both forward and backward – as we move further forward into Industry 4.0. This will allow us to tie all of the different datasets from the test-chain together, from wafer, from package, from system-level test. All of this data will be very large (terabytes and petabytes), and when we apply artificial intelligence (AI) techniques to the data, we’ll gain new insights and new intelligence that will help guide us as to what and where we should be testing.

We’ll ask new questions we hadn’t thought to ask before, as well as explore long-standing questions. For example, one dilemma we’ve faced for years is how best to optimize the entire test flow, from inception to the end of the test cycle. Should the test be performed earlier? Later? Is the test valuable, or should it come out? Do we need more tests? How much testing do we need to do to achieve the quality metric that we’re shooting for? In the Industry 4.0 era, we’ll start seeing the answers to these questions that resonate throughout the test world.

Data…and more data

Today, thanks to the convergence of data lakes and streams, we have more data available to us than ever before. In the last two years alone, we’ve generated more data than in all human history, and this trend will only increase. According to some estimates, in the next few years, we will be generating 44 exabytes per day. In other words, this would be about 5 billion DVDs worth of data per day. Stacked up, those DVDs would be higher than 36,700 Washington Monuments, and the data they contain would circle the globe in about a week (see Figure 1).

Figure 1. The volume of data we generate will soon reach 44 exabytes, or 5 billion DVDs, per day. Since this amount of data could circle the earth in about seven days, an “earth byte” could equate to a week’s worth of data.

These kinds of numbers are so massive that the term “Big Data” doesn’t really suffice. We need a global image to help visualize just how much data we will be generating on a daily basis. Based on these numbers, we could begin using the term “earth byte” to describe how much data is generated per week. Regardless of what we call it, it’s an unprecedented amount of data, and it is the fuel behind Industry 4.0.

Industry 4.0 pillars

Five key pillars are driving and sustaining the Industry 4.0 era (Figure 2):

• Big Data – as noted above, we are generating an unprecedented and near-infinite amount of data, half comes from our cell phones and much of the rest from the IoT
• IoT – sensor-rich and fully connected, the IoT is generating a wealth of data related to monitoring our environment – temperature, humidity, location, etc.
• 5G – the 5G global wireless infrastructure will enable near-zero-latency access to all of the data being generated
• Cloud computing – allows us to easily and efficiently store and access all our earth bytes of data
• AI – we need AI techniques (machine learning, data learning) to analyze in real time these large datasets being sent to the cloud in order to produce high-value, actionable insights

Figure 2. The five key pillars of Industry 4.0 are all interconnected and interdependent.

Because they are all reinforcing and accelerating each other, these Industry 4.0 trends are driving entire industries and new business models, creating an environment and level of activity that’s unprecedented.

Hypothetical use cases

Now that we’ve looked at where the test industry has been and what is driving where we’re headed, let’s examine some theoretical use cases (grounded in reality) that provide a visionary snapshot of ways we may be able to leverage the Industry 4.0 era to heighten and improve the test function and customers’ results. Figure 3 provides a snapshot of these five use cases.

Figure 3. Industry 4.0 will enable advancements in many areas of the test business.

1) Understanding customers better – across the supply chain

This use case encompasses various customer-related aspects that Industry 4.0 will enable us to understand and tie together to create new solutions. These include:

• • Customers’ march toward and beyond 5nm and how wafer, package, and system-level testing will work together for them
  • The entire supply chain’s cost challenges, which will help us optimize products and services across the value chain
  • How automotive quality requirements are driving into other business segments – as autonomous vehicles will be connected to everything across 5G, the quality of the connected network and its components will be forced to improve
  • 5G’s advanced technologies, including phased arrays, over-the-air, and millimeter-wave, all of which are already mature in the aerospace and military sectors – we will need to be able to leverage those technologies, cost them down appropriately, and support them for high-volume testing 

2) Decision making – yield prediction
The ability to predict yields will change everything. If you know, based on historical process data, that you’ll experience a yield drop within the next one to two months, you can start additional wafers to offset the drop. This easy fix would enable very little disruption to the supply chain.

If you can solve this problem, however, the next obvious question is, what’s causing it? Why don’t I just fix it before it happens? This involves prescriptive analytics, which will follow predictive analytics. Say you have developed a new generation of a product. You’ve collected yield data at all test insertions for previous generations of the product, which share DNA with the new incarnation. Combining past data with present data creates a model that enables highly accurate predictions about how the wafer will perform as it moves through the supply chain.

3) Creating new customer value – predictive maintenance
This use case is the most likely to come to fruition in the near term. Maintenance contracts require carrying inventory, spare parts and myriad logistics – they represent a huge cost. Soon, by combining tester fleet data with customer data and implementing machine learning, we’ll be able to dramatically improve tester availability, reduce planned maintenance, and decrease losses due to service interruptions. This will allow us to replace modules before they fail.

Predictive maintenance is a proven parameter that’s already being used in other industries such as oil and gas manufacturing. IoT sensor arrays are applied to the huge pipes and pumps controlling flow of chemicals, measuring stress, flow rates, and other parameters. The data from these sensors predict when a pump is going to wear out or a pipe needs to be replaced before it fails. We can leverage, redefine and redeploy this implementation for our use case. Soon, a field service engineer could show up with a replacement module before you even know that you need it.

4) Monetization – using data in new ways to drive our business
Data is an asset, and we’ll start to derive new business on sharing access, or leasing use of our data assets. One example might be a tester digital twin that resides in the cloud. Imagine that customers’ chip model data could be fed into this digital twin as a kind of virtual insertion, and the outputs would be parameters such as performance and yield. Customer benefits would include optimized programs, recommended tests, and predicted test coverage at each virtual insertion. This would enable them to optimize the entire flow depending on the product life cycle – perhaps test order could be changed, or a test added in order to improve quality. Because Advantest owns all the data that comes from our testers, we could lease or sell chipmakers access to the data, creating a significant business opportunity.

5) Automating and improving business operations – driving efficiencies
The test engineering community struggles with finding ways to improve process efficiencies. One way to do this is with the use of intelligent assistants. Still in their infancy, this category of AI can best be described as a trained assistant that could guide you in a helpful way when trying to perform a task.

For example, say we are validating a new 5G RF product on our Wave Scale RF card on the V93000 tester. All the pieces are being brought together – load board, tester, socket, chip, test program – and if there are any problems, the whole thing won’t work, or you’ll get partial functionality. An intelligent assistant or ‘bot’ trained in the necessary skillset can dynamically monitor the inputs and outputs and engineers’ interactions and provide real-time suggestions or recommendations on how to resolve the issues. At first it won’t be smart, but will learn quickly from the volume of data and will improve its recommendations over time.

As you can see, AI’s potential is vast. It will touch all aspects of our lives, but at its core, AI is really just another tool. Just as the computer age revolutionized our lives in the ’80s and ’90s, AI and Big Data will disrupt every industry we can think of – and some we haven’t yet imagined. Those slow to adopt AI as a tool risk being left behind, while those that embrace AI and learn to fully utilize it for their industries will be the future leaders and visionaries of Industry 5.0, whatever that may be.

Did you enjoy this article? Subscribe to GOSEMI AND BEYOND