March, 2018


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Enhanced Manufacturing Services 4.0 Part 3: Finding Gold in Production and Test Data


Continued from previous page


toward defects that occur frequently. A lack of coverage on defects that never occur has no relevance to final product quality. It is necessary to go beyond solving surface issues and to qualify the product test strategies against the real DPMO.


QuadDPMO ASTER has expanded its digital


suite of products with a new software tool, QuadDPMO. This tool aggre- gates traceability and repair data; enriches manufacturing and test in- formation with CAD data and the test coverage database; groups defect labels and root causes by defect class; investigates common areas of occur- rence for each defect class; and com- putes long-term, mid-term and short- term DPMO metrics.


Test coverage with standard DPM.


then better test coverage is required on certain components to prevent a higher escape rate. This, in turn, con- tributes to the NFF phenomenon.


Theoretical vs. Real DPM AOI and AXI inspection strate-


gies target the defects that occur most often, which results in an in-


crease in the weighted test coverage. An in-circuit test (ICT) strategy tar- gets defects with a lower level of oc- currence, resulting in a reduced weighted test coverage. Defect distribution highlights


that the “presence,” “alignment,” “quality,” and “open” defects are tar- geted more by inspection techniques, such as AOI and AXI, while ICT mainly targets “live” defects. It is a common misconception


that inspection alone is an acceptable test strategy. Some defects are ad-


Continued on page 40


Page 37


While a useful tool, test coverage analysis cannot root out all probable defects.


QuadDPMO produces reports


where test data can be analyzed by site, period of time, test station, batch ID, and product ID. It provides access to detailed reports, organized by defect family, code or label. This data can be sorted by many attrib- utes, such as pin count, pitch, mount- ing technology, mounting side, JEDEC shape, manufacturer, compo- nent function, board complexity, board type, etc. The resulting pie chart or bar


graph’s color codes can be trans- ferred automatically to the layout or schematic views to verify that the de- fect occurrence is linked to a physical or logical location (functional block). Since the QuadDPMO database


includes CAD data, test coverage met- rics and test and repair information, real DPM per component population information can be extracted. There are two major strategic benefits. First, if the theoretical defect


rate is higher than the real DPM, then test coverage has been devel- oped to detect defects that only rarely or do not occur. This provides the opportunity to optimize the test strategy by focusing on the most probable defects. This optimization can be static,


done one time for overall PCB produc- tion, or dynamic and adjusted in real time by disabling some tests when the DPM is decreasing. If the test be- comes a bottleneck on the production line, dynamic mode can facilitate in- creased throughput. Also, specific test lines could be selected based on their capability to detect certain defects, tuning the test line to the product. This capability could be expanded to allow OEMs to select an EMS provider based on its process capabili- ty, as reflected by its DPM figures. Second, if the real DPM is high- er than the theoretical defect rate,


Qaiyult Truh u hogpt Idsry Bs rcn nut et Pi ig Sle. Smlfid odr i pie. www.nathantrotter.com


Rla iiy eiblt Promne ef r ac


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