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On Boosting the Accuracy of Non-RF to RF Correlation-Based Specification Test Compaction

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Abstract

Several existing methodologies have leveraged the correlation between the non-RF and the RF performances of a circuit in order to predict the latter from the former and, thus, reduce test cost. While this form of specification test compaction eliminates the need for expensive RF measurements, it also comes at the cost of reduced test accuracy, since the retained non-RF measurements and pertinent correlation models do not always suffice for adequately predicting the omitted RF measurements. To alleviate this problem, we explore several methodologies that estimate the confidence in the obtained test outcome. Subsequently, devices for which this confidence is insufficient are retested through the complete specification test suite. As we demonstrate on production test data from a zero-IF down-converter fabricated at IBM, the proposed methodologies overcome the inability of standard specification test compaction methods to reach industrially acceptable test quality levels, and enable efficient exploration of the tradeoff between test accuracy and test cost.

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References

  1. Akbay SS, Chatterjee A (2007) Fault-based alternate test of RF components In: Proc. international conference on computer design, pp 517–525

  2. Biswas S, Li P, (Shawn) Blanton RD, Pileggi L (2005) Specification test compaction for analog circuits and MEMS. In: Design, automation and test in Europe, pp 164–169

  3. Brockman JB, Director SW (1989) Predictive subset testing: optimizing IC parametric performance testing for quality, cost, and yield. IEEE Trans Semicond Manuf 2(3):104–113

    Article  Google Scholar 

  4. Cristianini N, Shawe-Taylor J (2000) Support vector machines and other kernel-based learning methods. Cambridge

  5. Deb K, Pratap A, Agarwal A, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  6. Friedman JH (1991) Multivariate adaptive regression splines. Ann Stat 19(1):1–67

    Article  MATH  Google Scholar 

  7. Milor L, Sangiovanni-Vincentelli AL (1994) Minimizing production test time to detect faults in analog circuits. IEEE Trans Comput-Aided Des Integr Circuits Syst 13(6):796–813

    Article  Google Scholar 

  8. Seber GAF, Lee AJ (2003) Linear regression analysis. Wiley, New York

    MATH  Google Scholar 

  9. Stenbakken GN, Souders TM (1987) Test-point selection and testability measures via QR factorzation of linear models. IEEE Trans Instrum Meas IM-36(2):406–410

    Google Scholar 

  10. Stratigopoulos H-GD, Makris Y (2005) Non-linear decision boundaries for testing analog circuits. IEEE Trans Comput-Aided Des Integr Circuits Syst 24(11):1760–1773

    Article  Google Scholar 

  11. Stratigopoulos H-GD, Makris Y (2008) Error moderation in low-cost machine learning-based analog/RF testing. IEEE Trans Comput-Aided Des Integr Circuits Syst 27(2):339–351

    Article  Google Scholar 

  12. Stratigopoulos H-GD, Drineas P, Slamani M, Makris Y (2007) Non-RF to RF test correlation using learning machines: a case study. In: VLSI test symposium, pp 9–14

  13. Variyam PN, Chatterjee A (2000) Specification-driven test generation for analog circuits. IEEE Trans Comput-Aided Des Integr Circuits Syst 19(10):1189–1201

    Article  Google Scholar 

  14. Variyam PN, Cherubal S, Chatterjee A (2002) Prediction of analog performance parameters using fast transient testing. IEEE Trans Comput-Aided Des Integr Circuits Syst 21(3):349–361

    Article  Google Scholar 

  15. Voorakaranam R, Chatterjee A, Cherubal S, Majernik D (2005) Method for using an alternate performance test to reduce test time and improve manufacturing yield. Patent Application Publication #11/303,406

  16. Wrixon A, Kennedy MP (1999) A rigorous exposition of the LEMMA method for analog and mixed-signal testing. IEEE Trans Instrum Meas 48(5):978–985

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank IBM for providing the production test data employed in this study, as well as Dr. Haralampos Stratigopoulos from TIMA Laboratory in Grenoble, France, for the useful discussions on the methodologies described herein and developing the cost metric described in Section 3.4.

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Authors and Affiliations

  1. Department of Electrical Engineering, Yale University, 10 Hillhouse Avenue, New Haven, CT, 06520, USA

    Nathan Kupp & Yiorgos Makris

  2. Department of Computer Science, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, 12180, USA

    Petros Drineas

  3. IBM, Wireless Test Development Group, 1000 River Street 863G, Essex Junction, VT, 05452, USA

    Mustapha Slamani

Authors
  1. Nathan Kupp
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  2. Petros Drineas
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  3. Mustapha Slamani
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  4. Yiorgos Makris
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Correspondence to Yiorgos Makris.

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Responsible Editor: C. Metra

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Kupp, N., Drineas, P., Slamani, M. et al. On Boosting the Accuracy of Non-RF to RF Correlation-Based Specification Test Compaction. J Electron Test 25, 309–321 (2009). https://doi.org/10.1007/s10836-009-5113-7

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  • DOI: https://doi.org/10.1007/s10836-009-5113-7

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