New Models for Burn-In of Semiconductor Devices

Transcription

1 New Models for Burn-In of Semiconductor Devices Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, Jürgen Pilz - Alpen Adria University Klagenfurt, Austria Daejeon - South Korea

2 1 Burn-In today vs. new concepts 2 Countermeasure Model Publication List Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, New Jürgen Models Pilz -for Alpen Burn-In Adriaof University Semiconductor Klagenfurt, Devices Austria

3 1 Burn-In today vs. new concepts 2 Countermeasure Model Publication List Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, New Jürgen Models Pilz -for Alpen Burn-In Adriaof University Semiconductor Klagenfurt, Devices Austria

4 Bathtub curve Countermeasure Model Bathtub curve

5 Burn in - Elimination of Early life Early Fails Means to weed out early life fails: DD-screening Stress tests Outlier detection... Burn-In Burn-In is one method amongst many others to eliminate early life fails.

6 Burn-In today Countermeasure Model 2 Concepts Random sampling: 100 % Burn-In Optimization by Burn-In time reduction. Burn-In study Random samples are taken out of production and put into burn-in. In parallel 100 % Burn-In, as long as the Burn-In study is not passed. If the Burn-In study is pass, switch to BI-monitoring.

7 Burn-In today Countermeasure Model 90 % CL Random sampling: 0/ = % CL; 0/ = % CL; 1 90 % CL = 0/2.31 Mio. Beyond Sampling Pure random sampling gives limited results. The idea is to include further information to the random sample. On the following pages some of these ideas are introduced.

8 Burn In - new concepts Extended approach The classical approach looks only at the random sample. The extended approach takes further information into account: Countermeasure model: The efficiency of countermeasures as well as the overall performance of BI-studies is taken into account. Multiple reference products: In case of two or more reference products, an exact area scaling is now possible. Synergy model: Information about equal chip subsets, that have already passed Burn-In studies, are used. Area specific scaling: If different chip subsets show different ppm-values, referencing is done on these area-specific levels.

9 1 Burn-In today vs. new concepts 2 Countermeasure Model Publication List Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, New Jürgen Models Pilz -for Alpen Burn-In Adriaof University Semiconductor Klagenfurt, Devices Austria

10 Idea: Burn In Fails and Countermeasures - Estimation of p 1 Burn In Fail, Countermeasure α % effective 0.1 = α B(0; n, p) + (1 α) B(1; n, p) Effectiveness The effectiveness of a countermeasure reflects expert knowledge, available data,... It is a prior distribution. We propose to use the 10 % - quantile of this prior distribution.

11 Idea: Burn In Fails and Countermeasures - Estimation of p Example n = 100 k pcs., 1 Burn In fail, countermeasure 80 % effective. 0.1 = 0.8 B(0; n, p) B(1; n, p). Solution without countermeasure: p = 39 90% CL, with countermeasure: p = 27 90% CL.

12 Burn In Fails and Countermeasures - full picture Burn In Fail with Countermeasure - full picture Let s assume we put 100 k devices to burn in with 1 fail, introduce a countermeasure with 80 % effectiveness, and burn again 100 k pcs. with no fails. Taking all information into account, this results in 0.1 = 0.8 B(0; , p) B(1; , p), % CL.

13 1 Burn-In today vs. new concepts 2 Countermeasure Model Publication List Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, New Jürgen Models Pilz -for Alpen Burn-In Adriaof University Semiconductor Klagenfurt, Devices Austria

14 Countermeasure Model Let s assume two technologies which only differ in the metal block:

15 Countermeasure Model Let s say technology 1 had 250 k pcs. in Burn-In, technology 2 had 100 k pcs. in Burn-In. Products are assembled from all combinations of their subsets (combinatorial model):

16 Countermeasure Model Example - Comparison If we look only at technology 2: 1 / pcs % CL. If we look at technology 1 and 2: 1 / ( ) pcs. for the substrate 0 / pcs. for the metal block % CL.

17 1 Burn-In today vs. new concepts 2 Countermeasure Model Publication List Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, New Jürgen Models Pilz -for Alpen Burn-In Adriaof University Semiconductor Klagenfurt, Devices Austria

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19 Reference products 1 and 2 are built up with elements of size A gcd 1 fail at reference product 2 can be caused by 1 or several failed elements of size A gcd failed on the same chip (probabilities based on hypergeometric distribution). (all possibilities to built up reference products 1 and 2, p gcd ) = 0.1, numerical solution for p gcd

20 Example Reference Product 1: 5 mm 2, 0/ pcs, % CL; Reference Product 2: 12 mm 2, 1/ pcs, % CL. A gcd = 1 mm 2, p gcd = % CL, For a follower product with 7 mm 2 : p = % CL

21 1 Burn-In today vs. new concepts 2 Countermeasure Model Publication List Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, New Jürgen Models Pilz -for Alpen Burn-In Adriaof University Semiconductor Klagenfurt, Devices Austria

22 Area scaling Countermeasure Model Likelihood for a defect per device scales with the die size.

23 Burn-in study Countermeasure Model Figure: Reference and follower products per technology

24 Follower product - same CMOS, 3 x bigger DMOS

25 Separate area scaling - example Follower product - same CMOS, 3 x bigger DMOS Reference Product: 1/100k % CL Classical area scaling: % CL, Separate area scaling: % CL.

26 1 Burn-In today vs. new concepts 2 Countermeasure Model Publication List Horst Lewitschnig - Infineon Technologies Austria AG, Daniel Kurz, New Jürgen Models Pilz -for Alpen Burn-In Adriaof University Semiconductor Klagenfurt, Devices Austria

27 Publications Countermeasure Model Publications Countermeasure Model: Decision-Theoretical Model for Failures Which are Tackled by Countermeasures; Kurz, Lewitschnig, Pilz; IEEE Trans. Reliability, Vol. 63, No. 2, June R-package GenBinomApps, Lewitschnig and Lenzi, : Modeling of chip synergies for failure probability estimation in semiconductor manufacturing; Kurz, Lewitschnig, Pilz; applied to: Journal of Applied Statistics. : Failure probability estimation with differently sized reference products for semiconductor burn-in studies; Kurz, Lewitschnig, Pilz; Applied Stochastic Models in Business and Industry, online since Dec

28 Publications Countermeasure Model Publications : An advanced area scaling approach for semiconductor burn-in; Kurz, Lewitschnig, Pilz; Microeletronics Reliability, Vol. 55, Issue 1, January 2015 Acknowledgment: The work has been performed in the project EPT300, co-funded by grants from Austria, Germany, Italy, The Netherlands and the ENIAC Joint Undertaking. This project is co-funded within the programme Forschung, Innovation und Technologie für Informationstechnologie by the Austrian Ministry for Transport, Innovation and Technology.