Abstract
Relational databases to store design and electrical test data coupled with software tools for statistical analysis and graphics have provided a high degree of automation to post-processing of data for rapid feedback and debug. However, domain expertize is a valuable asset and in many cases an essential ingredient for finding the root cause. A brief overview of statistical methods including probability, distributions, correlation, and regression analysis is given. The use of prior knowledge obtained from circuit simulations and from test results on other product chips are emphasized. Examples of visualizing and summarizing techniques take advantage of building expectations from models and circuit simulations, and exploit visual pattern recognition capabilities in humans.
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References
Box GEP, Hunter WG, Hunter JS (1978) Statistics for experimenters: an introduction to design, data analysis and model building. Wiley, New York
Montgomery DC (2001) Design and analysis of experiments, 5th edn. Wiley, New York
Koronacki J, Thomson JR (2001) Statistical process control: the Deming paradigm and beyond, 2nd edn. Chapman and Hall, Boca Raton
Burr JT (2005) Elementary statistical quality control, 2nd edn. Marcel Dekker, New York
Montgomery DC (2009) Introduction to statistical quality control. Wiley, New York
Joglekar A (2001) Statistical methods for six sigma in R and D and manufacturing. Wiley Interscience, Hoboken
Pande PS, Neuman RP, Cavanagh RR (2000) The six sigma way. McGraw-Hill, New York
Tufte E (1983) The visual display of quantitative information. Graphics, Cheshire
Tufte E (1997) Visual explanations. Graphics, Cheshire
Tufte E (1990) Envisioning information. Graphics, Cheshire
Bhushan M, Ketchen MB (2011) Microelectronic test structures for CMOS technology. Springer, New York
NIST/SEMATECH e-Handbook of Statistical Methods. http://www.itl.nist.gov/div898/handbook/. Accessed 10 May 2014
Zhang W, Li X (2010) Bayesian virtual probe: minimizing variation characterization cost for nanoscale IC technologies via Bayesian inference. Design automation conference DAC’10, pp 262–167
Online matrix calculator. http://comnuan.com. Accessed 21 Jan 2014
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Bhushan, M., Ketchen, M.B. (2015). Basic Statistics and Data Visualization. In: CMOS Test and Evaluation. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1349-7_9
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DOI: https://doi.org/10.1007/978-1-4939-1349-7_9
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