Method of screening ASIC defects using independent component analysis of quiescent current measurements

A method comprising steps of:

• (a) receiving as input measurements of a parameter for each die in a sample lot of semiconductor die;
• (b) generating a test matrix from the parameter measurements for each die in the sample lot;
• (c) computing a de-mixing matrix from independent component analysis that models passing die in the sample, lot;
• (d) generating a matrix of sources as a product of the test matrix and the de-mixing matrix;
• (e) normalizing the matrix of sources to zero mean and unit variance;
• (f) selecting a statistical limit of the passing die in the sample lot to determine a maximum and a minimum parameter value limit for each of the sources;
• and
• (g) generating as output the maximum and the minimum parameter value limit for each of the sources.

A computer program product comprising a medium for embodying a computer program for input to a computer and a computer program embodied in the medium for causing the computer to perform steps of:

• (a) receiving as input measurements of quiescent current for each die in a sample lot of semiconductor die;
• (b) generating a test matrix from the quiescent current measurements for each die in the sample lot;
• (c) computing a de-mixing matrix from independent component analysis that models passing die in the sample lot;
• (d) generating a matrix of sources as a product of the test matrix and the de-mixing matrix;
• (e) normalizing the matrix of sources to zero mean and unit variance;
• (f) selecting a statistical limit of the passing die in the sample lot to determine a maximum and a minimum quiescent current limit for each of the sources;
• and
• (g) generating as output the maximum and the minimum quiescent current limit for each of the sources.

A computer program product comprising a medium for embodying a computer program for input to a computer and a computer program embodied in the medium for causing the computer to perform steps of:

• (a) receiving as input measurements of a parameter for each die in a sample lot of semiconductor die;
• (b) generating a test matrix from the parameter measurements for each die in the sample lot;
• (c) computing a de-mixing matrix from independent component analysis that models passing die in the sample lot;
• (d) generating a matrix of sources as a product of the test matrix and the de-mixing matrix;
• (e) normalizing the matrix of sources to zero mean and unit variance;
• (f) selecting a statistical limit of the passing die in the sample lot to determine a maximum and a minimum parameter value limit for each of the sources;
• and
• (g) generating as output the maximum and the minimum parameter value limit for each of the sources.