Study Confirms 1.82-mm Coaxial-Interconnect Design Target for mmWave ATE

This article is a condensed version of an article published March 12, 2021, in Microwave Journal. Adapted with permission. Read the original article at https://www.microwavejournal.com/articles/35583-development-and-verification-of-a-185-mm-coaxial-interconnect-for-mmwave-ate.

By Jose Moreira, Senior Staff Engineer, SOC R&D, Advantest

The adoption of mmWave frequencies for applications such as 5G and WiGig creates new challenges for the ATE industry, including the need for a reliable blind-mate interconnection between the printed-circuit-board (PCB) test fixture and ATE measurement instrumentation. An ATE system requires multiple types of interconnects (Figure 1). Spring-pin interconnects predominate for power and digital. RF and mmWave signals require coaxial interconnects, due mainly to the isolation requirements, not just the frequency range. The ATE must also automatically mate to the PCB test fixture without any kind of manual interaction. 

Figure 1: This depiction of Advantest’s V93000 ATE system top-side shows the different interconnects for digital, power, RF, and mmWave.

A key requirement is interconnect reliability; for mmWave ATE applications, the interconnect must support 20,000 insertions while guaranteeing ATE system specifications. A reliability study demonstrates that a blind-mate 1.85-mm coaxial interconnect achieves this design target with a significant margin.

Figure 2 shows the bottom side of a mmWave ATE test fixture and the different mating interconnects. For the spring-pin-based interconnect, a plated via connects to the spring pin tip and to a PCB signal trace, which is then routed to the DUT. A coaxial mating connector handles RF and mmWave signals. A coaxial cable from the coaxial interconnect in the test fixture connects to another connector close to the DUT socket. Unlike a PCB signal trace, the coaxial cable provides layout flexibility and, more importantly, significantly lower loss, since even a thin coaxial cable is less lossy than the best PCB signal trace.¹ 

Figure 2: This view of the bottom-side of an Advantest V93000 ATE test fixture shows the mating connectors and signal routing.

1.85-mm interconnect design

Reference [2] describes the development of a 1.85-mm blind-mating interconnect design (Figure 3), which provides mode-free operation to 70 GHz with no interconnect failure for 20,000 docking cycles. The IEEE 287 standard-compliant³ 1.85-mm female interface on the nonmating side of the interconnect uses off-the-shelf 1.85-mm cable assemblies to connect the blind-mating interface to the ATE measurement instrumentation and to the connector in the PCB test fixture close to the DUT. 

Figure 3: The blind-mating spring-loaded 1.85-mm interconnect requires mode-free operation to 70 GHz with a guaranteed 20,000 docking cycles.

Figure 4 shows the 1.85-mm blind mating connector pairs implemented on the ATE system and DUT test fixture sides. The system supports a maximum of 64 mmWave interconnects. The connector interface is spring-loaded on the male, ATE interface side and designed to self-align as the interface is mated. The mating action is part of the test fixture docking process to the ATE system. The ATE interconnect interface (Figure 2) comprises several interconnects apart from the 1.85-mm blind-mate connectors, all of which require a large docking force and, in turn, require special care with the mechanical design of the entire docking interface. This blind-mating interconnect requires a constant specific pressure on the entire mating surface to achieve the required 70-GHz frequency bandwidth. If this pressure is not correct or homogenous, effects like in-band resonances will appear in the interconnect frequency response.

Figure 4. This illustration depicts 1.85-mm blind mating connector pairs implemented on the ATE system and DUT test-fixture sides.

Reliability measurement procedure

Unfortunately, no clear guidelines have been published for evaluating the reliability of a blind-mate interconnection. Using the IEEE 287 standard³ as a guide and considering available resources, we developed a reliability test plan using a set of 14 connectors. Ten connectors were used for a docking cycle test to the maximum number of 60,000 insertion cycles. We measured S-parameters after every 300 cycles and removed the connectors to perform optical and mechanical measurements after every 6,000 cycles. Due to measurement resource limitations, we tested only two interconnects in parallel.

To eliminate the possibility that individuals in a pair become adapted to each other across the test run, after every 6,000 cycles, we exchanged the female of the pair between the two connectors being tested in parallel. Otherwise, measured reliability results could be significantly better than what you would find in a real application, where different test fixtures connect to different ATE systems through the lifetime of the connector.

Two other connectors were stressed to 60,000 cycles; in this case, only contact resistance measurements were performed every 300 cycles. Similarly, the same physical measurements and female connector exchange were performed every 6,000 cycles, as previously described.

Finally, the remaining two connectors in the measurement set were subjected to an accelerated life test, where they were left in a climatic chamber for 72 hours at 85°C and 85% humidity followed by the 60,000-docking-cycle test, with S-parameters measured every 300 cycles.

Measurement results

Our reliability testing strategy generated an enormous amount of data, which is summarized below and discussed in detail in Reference [4]. 

The S-parameter measurement setup consisted of an Anritsu MS4647B VNA and a 4-port extension MN4697B as well as Megaphase RF Orange 1.85-mm measurement cables. The VNA was used without calibration, so the loss shown includes both the coaxial cables’ and the VNA’s intrinsic loss. We employed this approach because our objective is to measure variations of interconnect performance over an increasing number of docking cycles, not the intrinsic connector performance. 

Figure 5 shows the interior of one connector pair before the test, at 30,000 cycles, and at 60,000 cycles, showing degradation of the socket side in the female of the pair. 

Figure 5: These successive images depict the interior of the connector pairs at different numbers of cycles.

Figure 6 shows the measured S-parameters after 60,000 insertion cycles. Since S-parameter measurements were performed every 300 cycles, the graph contains 200 overlaid plots. After cycle 54,000, a resonance appeared in the measured insertion loss around 20 GHz, revealing a failure of the interconnect, even though it continued working at higher mmWave frequencies. The cause for the failures was a crack in one of the socket fingers. This is the same mechanism seen with all failed connector pairs—not surprising since finite-element mechanical simulation shows this point has the highest mechanical stress during connector mating.⁴

Figure 6. After cycle 54,000, a resonance appears in the measured insertion loss at around 20 GHz.

Figure 7 shows the measured |S₁₁| and |S₂₁| parameters for a connector with no resonance failures during the entire 60,000-cycle test. This measurement was done with a fully calibrated VNA before the start of the test and after the entire 60,000 cycles. The results show even after 60,000 cycles, measured insertion and return loss are still acceptable.

Figure 7. This diagram shows the measured |S₁₁| and |S₂₁| for a connector with no resonance failures during the entire 60,000-cycle test.

Additional considerations

Although from a test and measurement perspective, electrical performance is the critical metric, the IEEE 287 standard defines several mechanical metrics, including the connector socket’s withdrawal and insertion forces.³ Another important metric is concentricity, the difference between the center of the inner and outer diameters of the socket and pin. In addition, computed tomography (CT) provides additional information regarding connector reliability. Figure 8 compares the surface of the original connector at cycle 0 to the connector’s surface at cycles 12,000 to 60,000 by visualizing the deviation in microns of the connector surface compared to cycle 0. Resolution is in the range of single-digit microns. 

Figure 8: CT scans performed on one of the interconnect female connectors at different stages of the cycle testing show successive deviations.

And finally, it is worth noting that the 1.85-mm connector standard offers many advantages for the blind-mate interface. For example, the long length of mechanical engagement of the adapter housing protects the center conductor while acting as an electromagnetic interference shield. A recent Microwave Journal article,⁵ on which this article is based, provides more information on the connector, mechanical metrics, concentricity, and CT scanning as well as additional details on our connector reliability test plan and on the mechanical finite-element simulations we used to confirm the specific failure mechanism we detected.

Conclusion

Our reliability study of a blind mate 1.85 mm coaxial interconnect for ATE mmWave applications shows that the target of 20,000 insertions was achieved with a significant margin, since all the connectors in the study failed above 40,000 cycles, excluding the connectors that had the accelerated life procedure performed. 

Acknowledgments

We thank Kosuke Miyao, Andy Richter, Marc Moessinger, and Matthias Feyerabend from Advantest; the Advantest failure-analysis lab in Gunma, Japan; and Eric Gebhard from Signal Microwave. We also thank Professor Sven Simon and Peter Gaenz from the Department of Parallel Systems at the Stuttgart University for the CT scan measurements.

References

1. J. Moreira and H. Werkmann, Automated Testing of High-Speed Interfaces, Artech House, Second Edition, 2016.
2. B. Rosas, J. Moreira, and D. Lam, “Development of a 1.85 mm Coaxial Blind Mating Interconnect for ATE Applications,” IEEE International Microwave Symposium, 2017.
3. “IEEE Standard for Precision Coaxial Connectors (DC to 110 GHz),” IEEE 287-2007, September 2007.
4. A. J. Rodrigues Mendes, Reliability Evaluation of a 1.85 mm Blind Mating Coaxial Interconnect for mmWave ATE Applications, Master of Science Thesis, Instituto Superior Técnico, University of Lisbon, 2020. fenix.tecnico.ulisboa.pt/downloadFile/845043405507284/Final_Thesis_Antonio_81353.pdf.
5. Moreira, Jose, et al., “Development and Verification of a 1.85 mm Coaxial Interconnect for mmWave ATE,” Microwave Journal, March 12, 2021. https://www.microwavejournal.com/articles/35583-development-and-verification-of-a-185-mm-coaxial-interconnect-for-mmwave-ate

Captions

Figure 1: This depiction of Advantest’s V93000 ATE system top-side shows the different interconnects for digital, power, RF, and mmWave.

Figure 2: This view of the bottom-side of an Advantest V93000 ATE test fixture shows the mating connectors and signal routing.

Figure 3: The blind-mating spring-loaded 1.85-mm interconnect requires mode-free operation to 70 GHz with a guaranteed 20,000 docking cycles.

Figure 4. This illustration depicts 1.85-mm blind mating connector pairs implemented on the ATE system and DUT test-fixture sides.

Figure 5: These successive images depict the interior of the connector pairs at different numbers of cycles.

Figure 6. After cycle 54,000, a resonance appears in the measured insertion loss at around 20 GHz.

Figure 7. This diagram shows the measured |S11| and |S21| for a connector with no resonance failures during the entire 60,000-cycle test.

Figure 8: CT scans performed on one of the interconnect female connectors at different stages of the cycle testing show successive deviations.

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SLT Enables Test Content to Shift Right to Optimize Test Efficiency and Part Quality

By Dave Armstrong and Davette Berry, Directors of Business Development, and Craig Snyder, Business Development Manager

Increasing device complexity and the continuing drive for higher levels of quality are fostering a reconsideration of test strategies. To be effective, test engineers must choose how to optimally deploy test content, from wafer probing to system-level test (SLT). A March 2019 TestConX presentation¹ outlines how test content is typically allocated—for example, final test performs structural and functional tests, parametric measurements, and performance binning; burn-in screens for early-life failures; and SLT looks for mission-mode failures resulting from hardware and software interactions. For cost balancing, though, it might be preferable to transfer a test step that has traditionally been performed at final package test, for example, upstream toward wafer test or downstream to SLT. At Advantest, we call the upstream transfer “shift left” and the downstream transfer “shift right” (Figure 1).

Figure 1. The test flow from wafer probing to SLT offers opportunities to shift test content right or left to optimize test efficiency and part quality.

Shift left overview

A January-February article² in Chip Scale Review describes the shift left process, which is particularly applicable to the integration of heterogeneous known-good die (KGD). For KGD test, it is advantageous to shift test content left from final test toward wafer test or to a singulated-die test stage, where you can perform full-power active-thermal-control (ATC) testing at speed. For KGD, a shift left strategy of more testing sooner reduces the number of good die scrapped because of one bad part in a multi-die assembly, ultimately leading to lower costs and more profit.

SLT overview

Alternatively, other applications can benefit from a shift right strategy, in which some test steps are transferred from final test and burn-in toward SLT, especially as SLT becomes more pervasive in manufacturing test.

SLT mimics in a manufacturing test environment the real-world operating conditions of the device under test, as described in a September 2020 GO SEMI & BEYOND article. In SLT, the device under test interacts with its mission-mode software and communicates with peripheral devices including power-management ICs (PMICs), DRAMs, and high-speed interfaces including USB or PCIe gen 4. Originally focused primarily on the memory and storage market during early silicon bring-up, SLT has expanded to include test of high-end processors and systems on chips (SoCs) used in computing, mobile, and automotive markets as well.

In addition to expanding to more markets, SLT is increasingly being applied to 100% of manufactured parts—not just samples. 100% SLT opens the door for a shift right of many test functions from final test to an enhanced SLT stage. This shift may also result in a lower overall cost of test.

High-speed interface test

One opportunity for the shift right of test content from final test to enhanced SLT involves connectivity and the test of high-speed I/O, but high-speed I/O tests bring about key challenges. In mission mode, a device will likely be soldered to a printed-circuit board close to its peripheral circuitry or inserted into an OEM socket on a computer motherboard. Neither is possible in the manufacturing test environment of SLT.

In SLT, connectivity and signal degradation problems—not defective devices—cause significant first-pass yield problems, seriously compromising throughput due to retest.

What’s needed is a high-performance, high-durability test socket for use in SLT that provides an optimized, tuned interconnect between the chip under test and its peripheral circuitry. To that end, Advantest in January 2020 acquired Essai, a supplier of semiconductor final-test and SLT test sockets (Figure 2) and thermal-control units. Essai possesses the expertise to design and manufacture the sockets with ever smaller pitches and ever higher electrical and thermal performance to address the final-test and SLT needs for successive generations of chips. These sockets permit at-speed test of high-speed interfaces at SLT, thereby enabling full-speed system level testing.

 

Figure 2. A test socket suitable for SLT provides mechanical durability while supporting an optimized signal path from the device under test to its peripheral components.

In addition, the socketed SLT motherboard enables a more native environment configuration for the device under test and better represents real-world conditions than does a typical ATE final test insertion, where propagation delays related to the path from device through the socket and load board and finally to the instrument must be taken into account.

Thermal test

Almost all of Advantest’s SLT customers are testing device behaviors at different temperatures at some point in the test flow, and most, if not all, of these tests can be shifted right to the SLT environment. 

An example in the automotive industry is the cold-boot requirement to ensure that vehicle electronics will boot up on an Alaskan winter morning. 

SLT can exercise a device at high temperatures, too. Many devices have temperature sensors, which may trigger a processor at a certain temperature to communicate with a PMIC to initiate a low-power operating mode until the temperature returns to normal.

Testing across temperature ranges presents its own challenges. For example, when you subject the device to different temperatures you are also subjecting the interconnect to different temperatures, leading to potential failures due to expansion and contraction. One solution is to get the device to temperature while leaving the rest of the SLT environment at as neutral a temperature as possible. Further, with heterogeneous integration, a substrate which may be as large as 100 mm on a side may accommodate multiple die, each with its own thermal response and challenge. Such a package might require topside contact by a thermal interposer that maintains temperature setpoints within different zones, all within that same package.

Burn-in

Finally, burn-in is a common test insertion for both automotive and high-performance compute devices. SLT test times extend from less than a minute to tens of minutes, and burn-in times extend from tens of minutes to hours. Given that the burn-in and SLT test insertions require some common thermal stress infrastructure, Advantest can enable the automation of combining SLT and burn-in in a common test cell. With some customers exploring high-speed I/O test during burn-in, burn-in can offer another opportunity to shift test content right.

Conclusion

Ultimately, in addition to its role mimicking the device under test’s mission mode, SLT is an opportunity to shift test content right. What it is not is an opportunity to completely replace other test steps. There will always be a need for final test, covering at a minimum short/open test to find assembly defects and performing multi-die communications checks and/or parametric measurements. On the other hand, the SLT test often includes creative interconnect solutions to high-speed memory, which require a test environment that would be impossible on an ATE system.

Committing to SLT for 100% of devices is a big step for companies to take, but once they do so they find that they can simplify final test by reducing test redundancy while continuing to ensure, and potentially enhance, the level of quality. Advantest serves the entire semiconductor manufacturing test space, from wafer probe to SLT. Advantest engineers stand ready to work with customers to determine the optimum deployment of test resources for their specific applications.

References

1. Berry, Davette, et al., “Holistic approach to test coverage across Final Test, Burn In, and System Level Test,” TestConX, Mesa, AZ, March 3-6, 2019.
   https://www.testconx.org/premium/wp-content/uploads/2019/TestConX20193ap2_5612.pdf

3. Armstrong, Dave, “Heterogeneous integration prompts test content to ‘shift left,’” Chip Scale Review, January-February 2021, p. 7.
   https://chipscalereview.com/wp-content/uploads/2021/01/ChipScale_Jan-Feb_2021-digital.pdf
4. Pizza, Fabio, “System-Level Test Methodologies Take Center Stage,” GO SEMI & BEYOND, September 27, 2020.
   http://www.gosemiandbeyond.com/system-level-test-methodologies-take-center-stage/

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Driving Toward Predictive Analytics with Dynamic Parametric Test

By Alan Hart, Senior Director, Applied Research, Technology & Venture, Advantest America, Inc.

The foundation of parametric test within semiconductor manufacturing is its usefulness in determining that wafers have been fabricated properly. Foundries use parametric test results to help verify that wafers can be delivered to a customer. For IDMs, the test determines whether the wafers can be sent on for sorting. Usually inserted into the semiconductor manufacturing flow during wafer fabrication at both the pre- and post-metal phases (as shown in Figure 1), parametric test has traditionally been used to check both transistor fabrication and metal layer interconnection, providing inputs to statistical process control (SPC) tools.

Figure 1. In the manufacturing flow, parametric test is typically inserted pre- and post-metallization, as indicated in blue above.

Measured data generated from the parametric tests is assessed and entered into a database, generating a report for an engineer to review. If an anomaly is highlighted, the engineer then orders the lot to be called back for retesting. This process typically takes a day or two, adding to the length and cost of the manufacturing cycle.

Dynamic parametric test (DPT), on the other hand, removes this review/retest loop by triggering immediate action upon measurement of an anomalous data point, based on the user’s predetermined parameters. This action takes place instantaneously, while the wafer is still on the tester – no reprogramming is required. Essentially, DPT elaborates on SPC techniques to establish these triggers, automating a process that, previously, would have required human intervention.

DPT drivers

The primary driver for implementing DPT techniques is the increasingly tight limitations created by shrinking process nodes. Today, 7nm and 5nm devices are in development (and the first 2nm process was recently announced). This translates to fabrication of leading-edge chips that comprise billions of transistors, whose features are separated by just a handful of silicon molecules. Testing billions of transistors individually is impractical, making parametric test vital for capturing statistics that reveal how the process went and help predict how well the circuit will perform. As devices get smaller and smaller, it becomes increasingly challenging to capture enough statistics to yield meaningful results, thus a greater volume of parametric tests are being applied in the assessment of wafer process quality.

DPT accelerates time-to-problem-solving, and hence, time-to-market, by enabling the parametric test system to instantly initiate data exploration based on customer-defined programming. By affording a deeper understanding of parametric deviations, it allows the user to program detailed characterizations for key devices, and to execute custom test flows based on real-time statistics or other user-defined criteria. As noted earlier, it adds automation to the engineering function – in essence, creating virtual engineering staff that can immediately analyze and debug unexpected results, or optimize test flow for tester utilization.

Advantest’s approach to DPT

Traditional parametric test looks at historical data to see what happened (descriptive analytics). Today, the process is evolving to capture additional data, allowing us to understand why it happened (diagnostic analytics). Going forward, the data will be correlated with future test results, enabling us to predict what will happen (predictive analytics). Predictive analytics, a key objective of Industry 4.0, enables corrective actions earlier in the manufacturing flow, as well as faster extraction of potential root-causes of deviations. Thus, by beginning to connect all the manufacturing steps shown in Figure 1, we can help wafer fabs and foundries begin to reap downstream benefits.

The goal is to be able to understand not only how well the circuit will yield at functional test, but also to predict its reliability when in use in its final application. For example, having one’s mobile phone fail is frustrating, but if it fails when you’re in your car and you need the GPS, or an emergency situation arises and you can’t call for help, the result could be disastrous.

Advantest’s Dynamic Parametric Test (DPT) software is a data-analytics enhancement to the V93000 SMU8 parametric test system, built on PDF Exensio® software from PDF Solutions. Together, Advantest and PDF Solutions have built a focused solution for parametric test that programs human decisions and actions into the tester to add real-time intelligence into the parametric test cell. Users implement DPT to immediately apply modified testing, both test algorithms and die map topology, allowing them to gain greater insight into the causes of unexpected results and to improve the efficiency of the test cell.

Figure 2 illustrates how the two systems work together. The DPT solution includes modifications to both the V93000 SMU8 system software and the Exensio data analytics platform. The solution is integrated into the V93000 SMU8 and into the Exensio server that manages the rules engine. Using customer-created rules, the software evaluates the incoming data from the tester, determines any necessary modifications to the test flow and/or test algorithms, and communicates them back to the tester, which then executes the new recipe. All of this happens instantly, in real time.

Figure 2. The Advantest V93000 Dynamic Parametric Test (DPT) system powered by PDF Exensio® DPT. The V93000 measures data and, via the event data log (EDL) stream, sends it to the Exensio software, which evaluates the data and immediately transmits any adaptive actions back to the test system to run the revised recipe.

No pre-programmed instructions are included in the DPT solution. The customer defines rules and models based on their own historical data and manufacturing requirements, which the system uses to look for anomalies and automatically trigger appropriate actions as the tests are run. The system identifies three basic types of triggers:

• A value that deviates from historical results;
• A statistical computation based on historical results from wafers/lots/time; or
• Statistical trends based on historical results from wafers/lots/time.

The rules that define these triggers and their parameters are set up through a simple user interface, using test algorithms already available in the customer’s test library, and are applied either at the end of the die location test or the end of the wafer test (see Figure 3).

Figure 3. The DPT solution can apply the rules engine at the end of a die-location test or at the end of a wafer test. New data in the modified test flow is automatically collected, without requiring wafer reloading or engineering review.

Real-world example

The ways in which the system can be deployed are limited only by customer needs. As an example, Figure 4 shows a use case involving diode test, checking the forward voltage (V_d) necessary for a 100nA of current to flow through the diode. The spot measurements are distributed across the wafer, as a representative sample provides a good indication of how the entire wafer behaves. When a bad data point is discovered, the system might automatically switch from a spot measurement to a sweep measurement, adding more die locations, to determine whether the cause is a device point defect or a general fabrication problem.

In Figure 4a, the DPT run flagged an outlier device that returned an out-of-spec result. As Figure 4b illustrates, this then automatically triggered a deeper, five-point sweep measurement around the location of the faulty diode, which revealed further outliers in that region. Figure 4c condenses the sweep results, plotting the sweeps to determine what caused the two parallel lines to appear. In this case, the slope shows normal diode behavior, with no device leakage. The problem is thus determined to be a problem with the bad diodes’ saturation current (I_s).

The system’s further calculations reveal that Is is only modified by p-n junction area (via photolithography) or by dopant density in the anode or cathode. Knowing the potential contributors of the saturation current are physical area and impurity concentration leads to two different potential root-causes. The engineer can then look at the topological pattern, which, in this case, suggests that the problem was in either a photolithographic or etch step, likely from a single multi-die reticle exposure. Thus, in less than a second of automatic additional testing, DPT has provided the engineer with an augmented data set for quick problem resolution.

The system can detect virtually any type of problem created during the manufacturing process, including back-end probe testing. On most parametric test floors, continuity test failures due to failing probe contact are not uncommon. When a continuity test fails, DPT performs further tests to determine if the problem is actually a defective die location or a probe needle that needs to be cleaned or repaired.

Once DPT validates that previously good die are now failing, it automatically performs a wafer probe card clean/polish step. It then can explore a wider topological region, automatically adding die locations to determine where the continuity problem occurred. If the error was caused by a dirty probe needle, which is often the case, retesting the last failed die along with additional die nearby will confirm that the problem was fixed. Again, DPT saves time and money by cleaning probes at just the right time, prolonging their use, and preventing a pause in the fabrication process.

The future: intelligent DPT

As mentioned earlier, the ultimate goal of DPT is to utilize machine learning to make the process measurement results truly predictive, allowing parametric test to estimate wafers’ functional test yield as many days or weeks before they reach that step. With this type of forecast in hand, chipmakers could potentially alter the subsequent test plans and correct process deviations much sooner.

Looking again the manufacturing flow diagram, we see that, with the V93000-Exensio DPT solution, data becomes more valuable at each downstream step. As Figure 5 shows, the parametric test dataset can now be used to forecast functional test yield, days or weeks ahead of the wafers reaching functional probe test, accelerating reaction time to process anomalies.

Figure 5. Using DPT techniques feeds forward upstream manufacturing process data to optimize downstream testing.

The DPT solution is part of a broader manufacturing tool set that will provide greater value from data already being collecting or can automatically add to the dataset. In future versions, interconnecting data from wafer fab through package test will provide insights using other tools in the Advantest Cloud Solutions portfolio to accelerate manufacturing response time.

To learn more about the Advantest V93000/SMU8 + PDF Exensio Dynamic Parametric Test solution, plan to attend the 2021 International Virtual VOICE Developer Conference, June 21-23. For more information and to register, visit https://voice.advantest.com/

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