HMM Round Robin Study: What to Expect When Testing Components to the IEC 61000-4-2 Waveform Kathleen Muhonen(1), Robert Ashton(2), Theo Smedes(3), Mirko Scholz(4), Rudolf Velghe(3), Jon Barth(5), Nathaniel Peachey (1), Wolfgang Stadler(6), Evan Grund(7) (1) RF Micro Devices, 7628 Thorndike Road, Greensboro, NC 27410 USA tel.: 336-202-5912, fax: 336-678-7369, e-mail:
[email protected] (2) ON-Semiconductor, 5500 McDowell Road, Phoenix, AZ 85008 USA (3) NXP Semiconductors, Gerstweg 2, 6534 AE Nijmegen, The Netherlands (4) IMEC, Kapeldreef 75, 3001 Heverlee, Belgium (5) Barth Electronics, 1589 Foothill Dr., Boulder City, NV 89005 USA (6) Intel Mobile Communications, ETC-DSI-ESQ-TQM, D-81726, Munich, Germany (7) Grund Technical Solutions, 5923 Amapola Drive, San Jose, CA 95129 USA
50 Words Abstract - ESDA Work Group 5.6, HMM (Human Metal Model), has conducted a round robin study using the HMM Standard Practice to determine reapeatability and reproducibility. Eight labs, using various ESD guns, 50 ohm and two-pin HMM pulsers show a range of results that highlights the variability allowed in the required waveform.
I. Introduction The Human Metal Model (HMM) Standard Practice was published by the ESD Association in 2010. A Standard Practice is defined as a procedure for performing one or more operations or functions that may or may not yield a test result; and if a result is obtained it may or may not be reproducible. Note that this Standard Practice is not intended to be used for qualification of products. Its intent is to define a test method for evaluating integrated circuits using the IEC-61000-4-2 waveform. The IEC standard is designed for testing systems, however, original equipment manufacturers (OEMs) are requesting their integrated device manufacturers (IDMs) to test individual components to this standard [1]. The interpretation and implementation of extending this system level test to device testing will inevitably vary from company to company. In order for an OEM and its IDM to be able to compare data at different sites, some sort of standard procedure should be followed that is repeatable and reproducible [1, 2]. Therefore the main purpose of the SP is to define a common way of applying the IEC waveform to integrated circuits, (ICs). Workgroup 5.6 of the ESD Association has completed a round robin study to see if the HMM Standard
Practice prepared by that working group is repeatable and reproducible across multiple test sites. This paper reports the results of the round robin study and establishes the degree of variability that can be expected when using this Standard Practice.
II. HMM Standard Practice A. Scope and Purpose The scope of the HMM Standard Practice states that this is a procedure for testing and characterizing the (ESD) sensitivity of component pins that will be directly connected to external connectors or ports on a system. The HMM pulse is the same waveform in the IEC 61000-4-2 document. The intent, or purpose, of this Standard Practice is to establish a test method for stressing pins of electrical components that will be directly connected to external ports of a system. It is not, however, intended to prove that a component will survive a particular stress in a completed system [3].
B. Waveform Specs The waveform used in the HMM Standard Practice is the same waveform as defined in IEC 61000-4-2 [3, 4]. Figure 1 shows this waveform. The documents
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specify the peak current, Ipeak, and the current at 30 and 60 ns. Ipeak is allowed to vary by 15% and the currents at 30 and 60 nsec are allowed to vary by 30%. The delivery of the pulse that is shown in Figure 1 can be done by using any qualified ESD gun or HMM pulser. Currently the HMM pulsers are either 50 ohm coaxial pulsers or two-pin pulsers with a manufacturer specified impedance. ESD guns all have a 330 ohm equivalent source impedance. All three types of delivery systems were used in the round robin study.
Figure 2: HMM Test Setup A
Discharge Point
A
Ground clamp Test or circuit board
ESD Pulse Source
Discharge Point A Ground Plane
A = 0.5 meters minimum
Figure 3: HMM Test Set-Up B
Figure 4 shows setup C which is used for a 50 ohm pulse source. This setup specifies the mounting of the DUT on a circuit board with 50 Ω traces, connectors for applying the stress pulse and measurement equipment. Setup C does not require the use of a 0.5 m metallic ground plane [3].
Figure 1: HMM and IEC Waveform
C. Test Set-Up The HMM document describes three test setups. Setups A and B are for use with an IEC 61000-4-2 compliant ESD gun and setup C is for use with a 50 Ω pulse source. In setup A, as shown in Figure 2, the device under test (DUT) is mounted on a circuit board which is placed at the center of a 0.5 m square, horizontal metal ground plane. The ground plane of the circuit board is continuous with the metallic ground plane and the ground strap of the ESD gun is connected to the edge of the metallic ground plane. The circuit board is designed to such that the stress can be applied in a way that resembles the way it reaches the IC in its real application. Test setup B, shown in Figure 3, is similar to setup A, except that the metal ground plane and circuit board are mounted vertically and the ESD stress is applied from the back side of the DUT board so the ground shields the DUT from the gun EM fields [3]. Ground clamps insuring that test board is securely grounded to Ground Plane
ESD Pulse Source
Discharge Points
A Ground Cable
Test or circuit board
A A = 0.5 meters minimum
Ground Plane
Figure 4: HMM Test Set-Up C
III. Round Robin Study This round robin study consisted of 8 test sites located at various companies and several countries. All of the test sites were given identical parts. Each site was instructed to use the HMM document to conduct the test but could choose whatever delivery system to use as long as their system had a compliant waveform. The first stress voltage and the stress step have been defined to guarantee comparability of the results. As for the 8 test sites, there were seven ESD guns used from six manufacturers and two pulsers from separate manufacturers. Six out of the seven sites that used guns used the horizontal ground plane and one site (site 5) used the vertical ground plane and the stress was applied as shown in Figure 3. Of the pulsers, one site had a 50 ohm pulser (site 8) with coax cable delivery and the other site had a 330 ohm two pin pulser (site 9). Note in the results site 2 and 3 were omitted due to an incomplete data set.
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In this study each site tested 4 different parts: (2) transient voltage suppressors (TVS) each from a different manufacturer, (1) Thyristor Surge Protection Device (TSPD) and (1) RF switch. Each site was given 5 replicates of each product to test and record the failure point. Failure criteria for each device was defined by device manufacturer and thoroughly explained to the test sites. The test procedure, however, was to use the HMM document to execute all tests. Data has been collected and is summarized here.
IV. Results A. Data Collection The TSPD part variability analysis is shown in Figure 5. A cursory glance will reveal that the data varies from about 5 kV to 12 kV for failure level. The overall standard deviation is 1630 V and the standard deviation of the means for each site is 1670 V (not shown the figure). Due to the coarse nature of the measurement (steps of 1 kV at times), several sites had zero standard deviation within their own lab.
Figure 6: Variability and Standard Deviation of TVS #1
Figure 7 shows TVS, part 2, that fails from 8 kV to 21 kV with an average of 12 kV. Here the variability within each lab is quite high. Sites 1 through 8 had a minimum variation of 0 kV and a maximum variation of 9 kV. The overall standard deviation was 3500 V and the standard deviation of the means was 3250 V. Finally, Figure 8 shows the RF switch failed anywhere from 3.5 kV to 13 kV with an average of 6 kV. The variability within each lab was less than 3 kV (most had 1 kV) except for site 6 which had 7 kV of variability. It is possible that site 6 had difficulty in some aspect of the measurement because part to part variability should have shown up across all sites which it did not. The standard deviation of this data was 1800 V and the standard deviation of the means was 1200 V. In addition, testing of this part started at 6 kV and many of the failure points happened after the first stress. If the start voltage was lower, the spread in the data would have been larger.
Figure 5: Variability and Standard Deviation of TSPD
Figure 6 shows that TVS, part 1, had failure levels from 10 kV to 14 kV with an average of about 11 kV. The standard deviation of the data is 1200 V and the standard deviation of the means is about 1250 V.
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deviations of over 1500 V. Even without further statistical analysis it is clear that this method is not sufficient for determining a part’s failure voltage with any degree of certainty. Statistical analysis was also done using the methods within the ASTM E691-92, “Standard Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method” [5]. This is the standard that the ESDA uses for analyzing inter-laboratory data. The statistics from this standard, which is intended to address repeatability between labs, indicated that the data between laboratories was in fact reproducible. This is clearly not consistent with even a casual evaluation of the raw data. The reason for this discrepancy will be discussed in the next section.
B. Statistical Analysis of the Data 1. ASTM 691 Figure 7: Variability and Standard Deviation for TVS #2
Figure 8: Variability and Standard Deviation for Switch
Figure 9 shows the distributions of all the data. The important number is the standard deviation for each part. None of the standard deviations are below 1500 V. The way that industry uses this method today is to assume there is the ability to determine that a part can pass 8 kV stress. These results show that there can be over 6000 V of variability in the data with standard
In the evaluation of any measurement technique there are two fundamental questions: what is the accuracy of the measurement and what is the precision of the measurement? Accuracy relates to the ability to trace the measurements back to accepted reference standards. Precision is defined as the closeness of agreement between independent test results obtained under stipulated conditions. Precision is affected by repeatability and reproducibility. Repeatability is the variation in results when a measurement is repeated using a specified procedure with the same equipment and a single operator. Reproducibility is the variation in results when a measurement is repeated using a specified procedure, but using different equipment and different operators. One way to determine the precision of a measurement technique is by conducting an interlaboratory study. Interlaboratory studies are often referred to as round robin studies because it is often done by passing a single set of samples to be measured from laboratory to laboratory to insure that the samples being measured are the same. The ESDA requires that Standard Practice test methods such as HMM be subjected to an interlaboratory study via ASTM E691 before the Standard Practice can be raised to the level of a Standard Test Method. This has been done for other standards the ESDA has published [6].
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Figure 9: Analysis of Data Distributions Including Mean and Standard Deviation
ASTM E691 restricts itself to a measurement which results in a single number. ASTM E691’s guidance on conducting an interlaboratory study includes recommendations on the number of laboratories, number of samples and the procedure to follow. ASTM E691 also defines a statistical method to compute a 95% confidence reproducibility limit, R, which is expressed as
R = 2.8sR ;
eq. (1)
where sR is the reproducibility standard deviation.
sR is the larger of the two terms sr and (sR )* . sr is *
the repeatability standard deviation and (s R ) is the provisional reproducibility standard deviation. sr is calculated by
s2 ∑1 p ; p
sr =
eq. (2)
where s is the standard deviation of results from a single laboratory and p is the number of laboratories. (sR )* is calculated by
(sR )* = (sx )2 + (sr )2 n − 1 ; n
eq. (3)
where s x is the standard deviation of the averages of results from each laboratory and n is the number of measurement results from each laboratory. The above equations assume that all of the measurements are from the same population. ASTM E691 recognizes that there may be issues with some measurements which make them not part of the same population. Measurement issues can come in two
forms: measurements within a laboratory which are outliers and laboratories whose results are outliers with respect to the other laboratories. ASTM E691 provides two statistics to look for anomalous measurements: the h statistic for reproducibility and the k statistic for repeatability. The h statistic is described as
h=
x−x ; sx
eq. (4)
where x is the average of results within a laboratory and x is the average of the averages from each laboratory. The k statistic is described as
k=
s . sr
eq. (5)
The values of h and k are referenced to as critical values. The critical value for h is based on the Student t-test and depends on the number of laboratories, while the critical value for k is based on the F-ratio and depends on both the number of laboratories and the number of repeated measurements at each laboratory. Values of h which exceed the critical value for h suggest a particular laboratory has results that are not consistent with the other laboratories. Values of k which exceed the critical value for k suggest that a laboratory has poor repeatability when compared to the other laboratories. The intent of the h and k statistics is to flag inconsistent results which should be investigated for errors and potentially eliminated from the interlaboratory study. The use of h and k to identify and potentially remove bad data allows a
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more accurate determination of the measurement technique’s precision [4]. The association of h with reproducibility and k with repeatability has led to the incorrect conclusion that ASTM E691 and the h and k metrics are intended to give a pass/fail determination if a measurement technique is repeatable and reproducible. This incorrect understanding of the h and k metrics can be illustrated by looking at the h values in Figure 10 for the HMM data presented here. This shows that all of the data meets the critical requirement for the h metric to indicate a reproducible measurement. This can easily happen if the standard deviation of the data is so large that the individual h values from equation 4 turn out to be small and will always be within the critical h value. Similarly, this too can happen for k values as shown in Figure 11. ASTM E691-92 Interlaboratory Data Analysis
HMM RR data 2.50 2.00
Critical h Value
1.50 1.00
Site 1 Site 4
0.50
Site 5
0.00
Site 6
TSPD 1
TVS 1
TVS 2
Switch
-0.50
Site 7 Site 8
-1.00
Site 9
-1.50
Upper h Lower h
-2.00 -2.50
Material & Lab
Figure 10: h Statistic for HMM Round Robin
part of the same population and that none should be eliminated to reduce the large variation in the data. This analysis indicates that the large calculated precision of the HMM data, as shown in Table 1, is correct. This level of precision is clearly not adequate to characterize failures using the HMM method. Table 1: R Values for HMM Round Robin Part
R Value
TSPD
3620 V
TVS 1
6443 V
TVS 2
11896 V
Switch
5280 V
2. Gauge R&R Gauge R&R stands for Gauge repeatability and reproducibility and is also used for interlaboratory studies. Data, such as in this round robin, is collected across sites, operators and equipment. The Gauge R&R looks at variability in the measurement equipment or process. If the uncertainty is too large, the measurement technique may be unusable [7]. Variability of the data was already shown in Figures 5 through 9. In addition to this calculations were done to determine the percentage of variability that comes from within each lab versus between the labs. This data was generated through statistical analysis software that has Gauge R&R evaluation tools. Figure 12 shows these percentages for each part in the round robin.
ASTM E691-92 Interlaboratory Data Analysis HMM RR data
3.00
Critical k Value
2.50
Site 1 Site 4
2.00
Site 5 1.50
Site 6 Site 7
1.00
Site 8 0.50 Site 9 Upper k
0.00
TSPD 1
TVS 1
TVS 2
Switch
-0.50
Material & Lab
Figure 11: k Statistic for HMM Round Robin
A casual look at the raw data in Figures 5 through 9 and basic engineering judgment says that these measurements do not meet the needed reproducibility for HMM measurements. The correct interpretation of h metric for this interlaboratory study is that the measurements from all of the laboratories appear to be
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TSPD
TVS #1
TVS #2
Switch Figure 11: Source of Variability
Note that for the TSPD and TVS #1, almost all of the variability is due to the lab to lab discrepancies. The TVS #2 and the switch had a more equal distribution of variability within each lab and across all labs. This is one indication that the uncertainty of this measurement method is too great and therefore unusable, especially with the tolerances that are being applied by labs today. Additionally, Gauge performance curves display the consequences of having measurement variability. These curves show the probability of accepting data as being in specification. These curves are shown in Figure 12.
Figure 12: Gauge Performance Curves
The vertical lines in each of these figures are the lower specification limit (LSL) on the left and upper specification limit (USL) on the right. These limits were determined by taking the mean of the data and bounding it by +\- 1000 V. Thus in the first data set for the TSPD device, the mean of the data was approximately 8500 V. Therefore the LSL is 7500 V and the USL is 9500 V. It was agreed that if the measurement method was accurate to +\- 1000 V it could possibly be used for determining a failure voltage. Realize that this is actually quite a large range for this purpose and the results are not encouraging. The Gauge standard deviation, LSL and USL as defined above were then used to generate the
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graphs in Figure 12. These were then generated with a graphing program from MathOptions [8]. The Gauge performance curves here are showing that none of the data even approaches 50% probability of being acceptable. An acceptable method would approach 100% inside the upper and lower spec limits. This analysis is another indicator that the measurement method is not useful in determining a failure level.
V. Summary and Conclusions The HMM test method has been developed to standardize testing components with the IEC 61000-42 waveform. It was hoped that the HMM test method would add uniformity to the way the IEC 61000-4-2 standard is interpreted and implemented. This study has revealed that a measurement method can have a large enough standard deviation that interpretations of the h statistic are misleading. This round robin clearly has variation that is too large for it to be useful even and the correct interpretation of the h and k statistics reveal that the precision of this method is quite large. So large that even with a standard deviation of over 5000 V, all the data appears to be from the same population. Further analysis of the data has also shown that this type of measurement method can be relatively repeatable within a lab but not reproducible across different labs. This is mainly attributed to the variation in the equipment that is available for this test. Gauge performance curves further support the conclusion that the method is not useable in determining a failure level with the IEC 41000-4-2 waveform. These results will redirect the effort of Workgroup 5.6 to find a better way to evaluate components for a system level environment. Tightening the waveform specification and looking into overall energy in the waveform are just two topics Workgroup 5.6 is
investigating. The goal is to develop a method that is not only repeatable within one lab but also reproducible across labs. Although these new investigations are not ready for this paper, the workgroup feels that the results of this round robin study are important enough that the information needs to be circulated now. It is imperative that companies requesting IEC 61000-4-2 stress be applied to a device with the variety of equipment understand the degree of variability associated with this method. That degree of variability is quite large and determining failure levels within +\- 1000 V of accuracy is not possible.
References [1] D. Robinson-Hahn, “Is System-Level ESD Testing Valid for ICs?”, Power Electronics Technology, September 2008, pp 26 - 29. [2] ANSI/ESD SP 5.6-2009. “Electrostatic Discharge Sensitivity Testing - Human Metal Model(HMM)” 2009. [3] IEC 61000-4-2 Ed. 2.0 b:2008. “Electromagnetic compatibility (EMC) – Part 4.2: Testing and measurement techniques – Electrostatic discharge immunity test.” [4] ASTM E691-92 Standard Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method. [5] K. Muhonen, N. Peachey, A. Testin, “Human Metal Model (HMM) Testing, Challenges to Using ESD Guns,” EOS/ESD Symposium, Anaheim, CA, 2009. [6] K. Muhonen et. al., “VF-TLP Round Robin Study, Analysis and Results,” EOS/ESD Symposium Proceedings, Tucson, AZ, 2008. [7] W. Kappele and J. Raffaldi, “Quality 101: An Introduction to Gauge R&R,” Quality Magazine, December 1, 2005. [8] MathOptions Inc., William Kappele – president, Bellingham, WA. www.ObjectiveDOE.com
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