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Quantifying Shmoo Results

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D
Dan Shu

This document discusses quantifying shmoo plot results by defining a metric called Shmoo Quality (SQ). SQ is defined as the area of the pass region in a shmoo plot. Quantifying SQ allows direct comparison of shmoo plots and trend analysis of SQ over time or process variations. An example is given where SQ is calculated for shmoo plots of three golden devices before and after changes, demonstrating up to 163% improved SQ. Quantifying shmoo results provides benefits for product and test engineering.

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2014/5/11 All Rights Reserved - ADVANTEST CORPORATION1 Quantifying Shmoo Results: Brain Storm Dan Shu April 28, 2014
All Rights Reserved - ADVANTEST CORPORATION2 Agenda • Purposes of Quantifying Shmoo Results • Definition of Shmoo Results: Shmoo Quality (SQ) • Test Methods for Shmoo Quality • Complex Cases of Shmoo plots • What Are We Going to Achieve? • Moving from an Analog Parameter Shmoo on an ATE Tester to a Digital Parameter Shmoo on an Internal Register value • Appendix: An Example of a Shmoo Quality Application • Credits
• These Left and Right Shmoo plot settings are identical. Can we easily tell which Device has a better (bigger) pass region? (Green is pass.) • Quantifying Shmoo Results will have great positive impacts on product and test engineering. All Rights Reserved - ADVANTEST CORPORATION3 Purposes of Quantifying Shmoo Results
• When comparing more than one Shmoo plots, we usually compare the X-Dimension and Y-Dimension opening (pass) region. This is the definition of Area: The amount of space inside the boundary of a flat (2-dimensional) surface. • Shmoo Quality (SQ) is defined as the Area of a Shmoo Plot Pass Region. • Unit of Shmoo Quality (SQ): X-Dimension unit times Y-Dimension unit. For example, if we Shmoo Voltage (X) vs. Frequency(Y), the SQ unit can be (V * MHz). • After this definition, we can quantify any Shmoo plot’s SQ. Furthermore, we can compare SQ values, datalog SQ, analysis SQ distribution, trends, etc. over process or temperature, etc. by data analysis tools such as Data Conductor. • In the Shmoo plot, the area of each pass/fail block equals Step_X * Step_Y. • SQ = total pass block * (Step_X * Step_Y) All Rights Reserved - ADVANTEST CORPORATION4 Definition of Shmoo Results: Shmoo Quality (SQ)
All Rights Reserved - ADVANTEST CORPORATION5 Test Methods for Shmoo Quality (SQ) Shmoo Quality ResultsShmoo Plot Settings
All Rights Reserved - ADVANTEST CORPORATION6 TestMethod: Shmoo Quality • The left-side picture is the V93K Test Suite inputs and the right- side picture is the V93K UI window and Datalog file format. • The example showed SQ = 11.15V * MHz on the right-side picture. • TestMethod will create or append a data file while the UI window shows the same contents. • STDF datalog will generate a PTR record with a test name as a suite name and the test result will be the SQ value. • This TestMethod can be used for almost any timing or level variable to Shmoo. The Results datalog file can be postprocessed by Perl to get a colorful picture. • This TestMethod Shmoo Quality approach is best for lots of parts that need to be SQ tested across many test phases. For example, a Split LOT may have 200 parts to go through SCAN CHAIN, SCAN BURST, and MBIST Shmoo with perhaps 2 – 3 different pattern files. An STDF datalog of SQ value can help get the data analysis work done in minutes.
All Rights Reserved - ADVANTEST CORPORATION7 STDF datalog PTR Record PTR Record TEST_NUM: 0 HEAD_NUM: 1 SITE_NUM: 1 TEST_FLG: 0x0 PARM_FLG: 0xC0 RESULT: 14.000000000 TEST_TXT: SCAN_CHAIN_5 MHz_NOM ALARM_ID: OPT_FLAG: 0xE LO_LIMIT: 0.000000010 HI_LIMIT: 9999999827968.000000000 UNITS: LO_SPEC: 0.0000 HI_SPEC: 0.0000 • We can see the QS results in the STDF file are logged as normal analog results. • TM controls the test name. In this case, “SCAN_CHAIN_5MHz_NOM” is the test name in the STDF data log. • We can define Units in TM as well.
All Rights Reserved - ADVANTEST CORPORATION8 Complex Cases of Quantifying Shmoo Qualify • The left Plot illustrates some fail points in the big pass region. • The right Plot illustrates some pass points within the failure region.
All Rights Reserved - ADVANTEST CORPORATION9 Algorithmic Definition of Shmoo Results • We have defined that Shmoo Quality (SQ) is the Area of a Shmoo Plot Pass Region. • We also observed in the previous slide that the simple Area definition of the pass region may not make sense in some of the real cases. • We may have to remove some good “pass” block neighborhoods with one isolated “fail” block, or to remove an isolated “pass” block from SQ calculation. • Engineers usually need to review those special Shmoo plot cases in order to better understand the real situation. • The sample TestMethod is a simple step to demonstrate the mindset of Quantifying. The TestMethod we are using here can be improved in many ways.
All Rights Reserved - ADVANTEST CORPORATION10 What Are We Going to Achieve? • We want to quantify everything that we can. Knowing how to analyze those detail differences will help us improve quality, cost, and speed. • This exercise of creating a test method to generate a Shmoo plot will help us to Shmoo the device internal register value. Under such circumstances, the tester’s timing or level settings usually have less influence over those internal register settings. • We can use this approach to let the ATE program do Shmoo and datalog automatically (avoiding the engineer having to do it manually) as characterization and R&D engineering work with a relatively large numbers of devices. For example, there tests can be done by prober auto sorting, handler auto indexing, or operators. • This Shmoo plot TM exercise also helps generate the BER Contour Plot by the Shmoo “TX/RX len” internal register setting, and reads back the internal error counter through JTAG or another serial port.
All Rights Reserved - ADVANTEST CORPORATION11 From Analog to Digital Parameter Shmoo 000000000000000000000++++00000000000 000000000000000+++++++++++0000000000 00000000000+++++++++++++++0000000000 00000000000+++++++++++++++0000000000 00000000000++++++++++++++++000000000 0000000000+++++++++++++++++000000000 000000000++++++++++++++++++000000000 000000000+++++++++++++++++0000000000 00000000++++++++++++++++++0000000000 00000000++++++++++++++++++0000000000 000000000++++++++++++++++++000000000 00000000+++++++++++++++++++000000000 00000000+++++++++++++++++++000000000 000000000++++++++++++++++++000000000 • In the left-side data array, each x- y point can store a Error Count value (from 0 – infinite). • Use Perl scripts to generate a BER contour plot. At each point, a color will represent the Error Bit Count. • Usually X-Dimension is the Chip Internal Phase Delay sampler position and Y-Dimension is the digital threshold value. • The Error-Free Area is the targeted value we want to get. Move from Analog Parameter Shmoo on the ATE Tester to Digital Parameter Shmoo on the Internal Register Value
All Rights Reserved - ADVANTEST CORPORATION12 2-D Shmoo Plot with Error Count • Left-side plot is the V93K PS9G receiver’s view in an 8G PCIe Gen3 signal. • Right-side plot is the IC internal PCIe receiver’s view of the signal. The ATE tester only can control the register setting through JTAG. This is the challenge. From Tester to IC Built-In Digital Register Value Shmoo
All Rights Reserved - ADVANTEST CORPORATION13 Appendix: An Example of Shmoo Quality (SQ) Application Golden Device 1, Nonquantified SQ • The Golden Device 1 old (left) and new (right) patterns show a difference in the Shmoo Plot, but the SQ is not quantified.
All Rights Reserved - ADVANTEST CORPORATION14 Golden Device 1, Quantified SQ • The Golden Device 1 old (left) and new (right) patterns show a difference on the Shmoo Plot, with a quantified SQ. • Improved Shmoo Quality = SQ (new) / SQ (old) = 20.6875 / 13.625 = 151.8%
All Rights Reserved - ADVANTEST CORPORATION15 Golden Device 2, Nonquantified SQ • Golden Device 2 old (left) and new (right) patterns show a difference on the Shmoo Plot, but SQ is not quantified.
All Rights Reserved - ADVANTEST CORPORATION16 Golden Device 2, Quantified SQ • Golden Device 2 old (left) and new (right) patterns show a difference on Shmoo Plot, with a quantified SQ. • Improved Shmoo Quality = SQ (new) / SQ (old) = 25.375 / 15.5625 = 163.1%
All Rights Reserved - ADVANTEST CORPORATION17 Golden Device 3, Nonquantified SQ • Golden Device 3 old (left) and new (right) patterns show a difference on the Shmoo Plot, but SQ is not quantified.
All Rights Reserved - ADVANTEST CORPORATION18 Golden Device 3, Quantified SQ • Golden Device 3 old (left) and new (right) patterns show a difference on the Shmoo Plot, with a quantified SQ. • Improved Shmoo Quality = SQ (new) / SQ (old) = 24.5 / 21.1875 = 115.6%
All Rights Reserved - ADVANTEST CORPORATION19 Three Devices’ Shmoo Results Summary • We can easily generate a statistic analysis report based on the quantified Shmoo results. Shmoo Quality (SQ) Summary Table: Unit (V*MHz) Device SN Old Pattern New Pattern Improvement (%) 1 13.625 20.6875 151.83% 2 15.5625 25.375 163.05% 3 21.1875 24.5 115.63%
All Rights Reserved - ADVANTEST CORPORATION20 Credits I want to express my thanks to managers and fellow colleague and many others.

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Quantifying Shmoo Results

  • 1. 2014/5/11 All Rights Reserved - ADVANTEST CORPORATION1 Quantifying Shmoo Results: Brain Storm Dan Shu April 28, 2014
  • 2. All Rights Reserved - ADVANTEST CORPORATION2 Agenda • Purposes of Quantifying Shmoo Results • Definition of Shmoo Results: Shmoo Quality (SQ) • Test Methods for Shmoo Quality • Complex Cases of Shmoo plots • What Are We Going to Achieve? • Moving from an Analog Parameter Shmoo on an ATE Tester to a Digital Parameter Shmoo on an Internal Register value • Appendix: An Example of a Shmoo Quality Application • Credits
  • 3. • These Left and Right Shmoo plot settings are identical. Can we easily tell which Device has a better (bigger) pass region? (Green is pass.) • Quantifying Shmoo Results will have great positive impacts on product and test engineering. All Rights Reserved - ADVANTEST CORPORATION3 Purposes of Quantifying Shmoo Results
  • 4. • When comparing more than one Shmoo plots, we usually compare the X-Dimension and Y-Dimension opening (pass) region. This is the definition of Area: The amount of space inside the boundary of a flat (2-dimensional) surface. • Shmoo Quality (SQ) is defined as the Area of a Shmoo Plot Pass Region. • Unit of Shmoo Quality (SQ): X-Dimension unit times Y-Dimension unit. For example, if we Shmoo Voltage (X) vs. Frequency(Y), the SQ unit can be (V * MHz). • After this definition, we can quantify any Shmoo plot’s SQ. Furthermore, we can compare SQ values, datalog SQ, analysis SQ distribution, trends, etc. over process or temperature, etc. by data analysis tools such as Data Conductor. • In the Shmoo plot, the area of each pass/fail block equals Step_X * Step_Y. • SQ = total pass block * (Step_X * Step_Y) All Rights Reserved - ADVANTEST CORPORATION4 Definition of Shmoo Results: Shmoo Quality (SQ)
  • 5. All Rights Reserved - ADVANTEST CORPORATION5 Test Methods for Shmoo Quality (SQ) Shmoo Quality ResultsShmoo Plot Settings
  • 6. All Rights Reserved - ADVANTEST CORPORATION6 TestMethod: Shmoo Quality • The left-side picture is the V93K Test Suite inputs and the right- side picture is the V93K UI window and Datalog file format. • The example showed SQ = 11.15V * MHz on the right-side picture. • TestMethod will create or append a data file while the UI window shows the same contents. • STDF datalog will generate a PTR record with a test name as a suite name and the test result will be the SQ value. • This TestMethod can be used for almost any timing or level variable to Shmoo. The Results datalog file can be postprocessed by Perl to get a colorful picture. • This TestMethod Shmoo Quality approach is best for lots of parts that need to be SQ tested across many test phases. For example, a Split LOT may have 200 parts to go through SCAN CHAIN, SCAN BURST, and MBIST Shmoo with perhaps 2 – 3 different pattern files. An STDF datalog of SQ value can help get the data analysis work done in minutes.
  • 7. All Rights Reserved - ADVANTEST CORPORATION7 STDF datalog PTR Record PTR Record TEST_NUM: 0 HEAD_NUM: 1 SITE_NUM: 1 TEST_FLG: 0x0 PARM_FLG: 0xC0 RESULT: 14.000000000 TEST_TXT: SCAN_CHAIN_5 MHz_NOM ALARM_ID: OPT_FLAG: 0xE LO_LIMIT: 0.000000010 HI_LIMIT: 9999999827968.000000000 UNITS: LO_SPEC: 0.0000 HI_SPEC: 0.0000 • We can see the QS results in the STDF file are logged as normal analog results. • TM controls the test name. In this case, “SCAN_CHAIN_5MHz_NOM” is the test name in the STDF data log. • We can define Units in TM as well.
  • 8. All Rights Reserved - ADVANTEST CORPORATION8 Complex Cases of Quantifying Shmoo Qualify • The left Plot illustrates some fail points in the big pass region. • The right Plot illustrates some pass points within the failure region.
  • 9. All Rights Reserved - ADVANTEST CORPORATION9 Algorithmic Definition of Shmoo Results • We have defined that Shmoo Quality (SQ) is the Area of a Shmoo Plot Pass Region. • We also observed in the previous slide that the simple Area definition of the pass region may not make sense in some of the real cases. • We may have to remove some good “pass” block neighborhoods with one isolated “fail” block, or to remove an isolated “pass” block from SQ calculation. • Engineers usually need to review those special Shmoo plot cases in order to better understand the real situation. • The sample TestMethod is a simple step to demonstrate the mindset of Quantifying. The TestMethod we are using here can be improved in many ways.
  • 10. All Rights Reserved - ADVANTEST CORPORATION10 What Are We Going to Achieve? • We want to quantify everything that we can. Knowing how to analyze those detail differences will help us improve quality, cost, and speed. • This exercise of creating a test method to generate a Shmoo plot will help us to Shmoo the device internal register value. Under such circumstances, the tester’s timing or level settings usually have less influence over those internal register settings. • We can use this approach to let the ATE program do Shmoo and datalog automatically (avoiding the engineer having to do it manually) as characterization and R&D engineering work with a relatively large numbers of devices. For example, there tests can be done by prober auto sorting, handler auto indexing, or operators. • This Shmoo plot TM exercise also helps generate the BER Contour Plot by the Shmoo “TX/RX len” internal register setting, and reads back the internal error counter through JTAG or another serial port.
  • 11. All Rights Reserved - ADVANTEST CORPORATION11 From Analog to Digital Parameter Shmoo 000000000000000000000++++00000000000 000000000000000+++++++++++0000000000 00000000000+++++++++++++++0000000000 00000000000+++++++++++++++0000000000 00000000000++++++++++++++++000000000 0000000000+++++++++++++++++000000000 000000000++++++++++++++++++000000000 000000000+++++++++++++++++0000000000 00000000++++++++++++++++++0000000000 00000000++++++++++++++++++0000000000 000000000++++++++++++++++++000000000 00000000+++++++++++++++++++000000000 00000000+++++++++++++++++++000000000 000000000++++++++++++++++++000000000 • In the left-side data array, each x- y point can store a Error Count value (from 0 – infinite). • Use Perl scripts to generate a BER contour plot. At each point, a color will represent the Error Bit Count. • Usually X-Dimension is the Chip Internal Phase Delay sampler position and Y-Dimension is the digital threshold value. • The Error-Free Area is the targeted value we want to get. Move from Analog Parameter Shmoo on the ATE Tester to Digital Parameter Shmoo on the Internal Register Value
  • 12. All Rights Reserved - ADVANTEST CORPORATION12 2-D Shmoo Plot with Error Count • Left-side plot is the V93K PS9G receiver’s view in an 8G PCIe Gen3 signal. • Right-side plot is the IC internal PCIe receiver’s view of the signal. The ATE tester only can control the register setting through JTAG. This is the challenge. From Tester to IC Built-In Digital Register Value Shmoo
  • 13. All Rights Reserved - ADVANTEST CORPORATION13 Appendix: An Example of Shmoo Quality (SQ) Application Golden Device 1, Nonquantified SQ • The Golden Device 1 old (left) and new (right) patterns show a difference in the Shmoo Plot, but the SQ is not quantified.
  • 14. All Rights Reserved - ADVANTEST CORPORATION14 Golden Device 1, Quantified SQ • The Golden Device 1 old (left) and new (right) patterns show a difference on the Shmoo Plot, with a quantified SQ. • Improved Shmoo Quality = SQ (new) / SQ (old) = 20.6875 / 13.625 = 151.8%
  • 15. All Rights Reserved - ADVANTEST CORPORATION15 Golden Device 2, Nonquantified SQ • Golden Device 2 old (left) and new (right) patterns show a difference on the Shmoo Plot, but SQ is not quantified.
  • 16. All Rights Reserved - ADVANTEST CORPORATION16 Golden Device 2, Quantified SQ • Golden Device 2 old (left) and new (right) patterns show a difference on Shmoo Plot, with a quantified SQ. • Improved Shmoo Quality = SQ (new) / SQ (old) = 25.375 / 15.5625 = 163.1%
  • 17. All Rights Reserved - ADVANTEST CORPORATION17 Golden Device 3, Nonquantified SQ • Golden Device 3 old (left) and new (right) patterns show a difference on the Shmoo Plot, but SQ is not quantified.
  • 18. All Rights Reserved - ADVANTEST CORPORATION18 Golden Device 3, Quantified SQ • Golden Device 3 old (left) and new (right) patterns show a difference on the Shmoo Plot, with a quantified SQ. • Improved Shmoo Quality = SQ (new) / SQ (old) = 24.5 / 21.1875 = 115.6%
  • 19. All Rights Reserved - ADVANTEST CORPORATION19 Three Devices’ Shmoo Results Summary • We can easily generate a statistic analysis report based on the quantified Shmoo results. Shmoo Quality (SQ) Summary Table: Unit (V*MHz) Device SN Old Pattern New Pattern Improvement (%) 1 13.625 20.6875 151.83% 2 15.5625 25.375 163.05% 3 21.1875 24.5 115.63%
  • 20. All Rights Reserved - ADVANTEST CORPORATION20 Credits I want to express my thanks to managers and fellow colleague and many others.