Download presentation

Presentation is loading. Please wait.

Published byBreana Sauvage Modified over 3 years ago

1
Compensation for Measurement Errors Due to Mechanical Misalignments in PCB Testing Anura P. Jayasumana, Yashwant K. Malaiya, Xin He, Colorado State University Kenneth P. Parker and Stephen Hird Agilent Technologies

2
Objective 2 Identification of outlier boards using Capacitive Lead Frame Testing data Improve the accuracy of outlier detection by compensating for systematic errors such as mechanical misalignment and fixture-to-fixture variations BTW 2010

3
Outline PCA Based Outlier Detection Test Data for Mechanical Misalignments PCA Based Compensation Summary 3 BTW 2010

4
Capacitive Lead Frame Testing 4 Ref: Parker & Hird, ITC 2007 BTW 2010

5
Example: Capacitance vs. Pin Number (for a J245) 5 BTW 2010

6
6 1 st Principal Component contains largest variance from the data projection 2 nd Principal Component, orthogonal to the 1 st one, contains second largest projected variance Useful for analyzing multi- dimensional interrelated data Measurement 2 2 nd PC 1 st PC 0 Measurement 1 Principal Component Analysis (PCA) BTW 2010

7
PCA for PCB Outlier Detection 7 M McMcMcMc Let M be (mxn) matrix of Capacitive Lead Frame Testing measurements - m is the number of boards - n is number of tested pins per board Centering BTW 2010

8
PCA for PCB Outlier Detection M c = USV T Singular Value Decomposition M c = USV T where, U mxn A scaled version of PC scores S nxn Diagonal matrix with square roots of Eigen values in descending order V T nxn Eigen vectors (PCs). V Transformation Matrix Z = M c V Z = M c V Matrix with z-score values of boards Z-scores of a board are linear combination of all corresponding measurements for that board 8 BTW 2010

9
Test Statistic for Outlier Detection 9 z ik : Value of the k th PC for i th board E : a subset of PCs - most significant PCs are used here Sort the boards with respect to d 1 Plot cumulative distribution function (CDF) of d 1 Outliers clearly identifiable on right side of plot, typically separated from others by a clear margin BTW 2010

10
10 Board run numbers on CDF plot from left to right: 52,51,50,53,49,32,73,24,48,25,74,72,83,71,57,47,1,42,56,70,6,68,38,37,58,43,59,41,39, 55,40,2,23,78,33,35,44,69,79,54,75,36,64,80,76,31,77,65,60,29,81,63,61,62,3,67,66,82, 27,45,28,46,26,30,34,12,8,7,10,9,16,11,13,14,15,4,5,17,22,19,18,20,21 PCA Based Outlier Detection ITC 2009 Treats data holistically Outlier detection as opposed to threshold based detection

11
Capacitive Lead Frame Testing 11 Ref: Parker & Hird, ITC 2007 Capacitance < 100fF (<10fF with opens faults) Systematic variations, e.g., variations in connector height, co-planarity of ball connections, sense plate, … Relatively small mechanical variations can lead to larger measurement variability (Ex. 18fF variation across shift test cases vs. std deviation of <1fF) Test values and test limits set now may fail if mechanical variations appear later BTW 2010

12
Mechanical Misalignments 12 Setup Left or right End Tilt Height (mils) Setup Vertical Shift Height (mils) Tilt_00Shift_00 Tilt_18Shift _18 Tilt_216Shift_216 Tilt_324Shift_324 BTW 2010

13
Raw measurements for B1 with one normal and three left tilted sense plates Tilt_0 Tilt_1 Tilt_2 Tilt_3 BTW 2010

14
Raw measurements with normal and vertical shifted sense plate for board B5 connector J3 Shift_0 Shift_1 Shift_2 Shift_3 BTW 2010

15
Compensating for Tilt 15 BTW 2010

16
Raw measurements with normal and vertical shifted sense plate for board B5 connector J3 Shift_0 Shift_1 Shift_2 Shift_3 BTW 2010

17
Plot of PC values for Shift Data Note: PC-1 can be used to identify the amount of shift or tilt in sense plate Unlike visual inspection, PCA can identify complex but systematic patterns If the same board is tested in multiple fixtures, it may be possible to identify differences and compensate for them BTW 2010

18
Adjusted capacitances by setting all but 1st PC equal to 0 for data B1 PC-1 captures the tilt information as well as other common information BTW 2010

19
Data set including two synthetic traces, Def_1 and Def_2 simulating open faults on pins 121 and 165 BTW 2010

20
Adjusted capacitances by setting only 1st PCs to 0 BTW 2010

21
Data set including two synthetic traces, Def_1 and Def_2 simulating open faults on pins 75 and 165 BTW 2010

22
Adjusted capacitance by setting all but 1st PC to zero BTW 2010

23
Adjusted data based on setting only 1st PC to 0 BTW 2010

24
24 A PCA based technique presented for identification and compensation for measurement errors introduced due to sense-plate variations Method can be used to separate misalignment related information from defect related information in test data Approach is NOT sensitive to the order of the pins, and thus shows promise for complex but systematic errors introduced by sense plate misalignments Method applicable to other kinds of test data Summary BTW 2010

25
25 Overcome variations caused by measurement errors, mechanical and electrical tolerances Adaptive and learning techniques for detection and diagnosis Future Work BTW 2010

Similar presentations

OK

Probability of Error Feature vectors typically have dimensions greater than 50. Classification accuracy depends upon the dimensionality and the amount.

Probability of Error Feature vectors typically have dimensions greater than 50. Classification accuracy depends upon the dimensionality and the amount.

© 2018 SlidePlayer.com Inc.

All rights reserved.

To ensure the functioning of the site, we use **cookies**. We share information about your activities on the site with our partners and Google partners: social networks and companies engaged in advertising and web analytics. For more information, see the Privacy Policy and Google Privacy & Terms.
Your consent to our cookies if you continue to use this website.

Ads by Google

Ppt on standing order act materials Ppt on job evaluation sample Ppt on machine translation service Ppt on cse related topics such Ppt on electrical circuit breaker Ppt on marketing management for mba Download ppt on web browser Ppt on bakery business plan Ppt on dynamic resource allocation in cloud computing Download ppt on motion sensing technology