Printed Circuit Design & Fab - February 2009 - (Page 32)

MATERIAL rEGiStration FiGurE 2. A schematic highlighting the interface to the optimizer and the flow of data to the predictive system. FiGurE 3. Scale factor prediction. of material and process variations in the prior processes can be determined. It should be noted that some advanced laser drill systems are able to provide compatible data for the model, but the primary machine interface for most users remains the optimizer. A schematic of the system is shown in FiGurE 2 highlighting the interface to the optimizer and the flow of data to the predictive system. Many modern optimizer systems are capable of quickly analyzing the individual scale factors in both panel axes (grainand-fill or warp-and-weft directions) simultaneously on every layer making for rapid and accurate analysis. Advanced systems are additionally able to analyze non-linear distortion by measuring targets around the periphery of the panel providing an even greater level of understanding of material distortion. Of course, optimizer capacity is finite, and it will be reduced when measuring each and every layer; however, it is not necessary to measure every panel in this manner. It is perfectly adequate to measure the majority of panels in the lot with standard overlapped targets and use “every layer” measurement for a smaller sample – often 5% to 10%. When product technology increases or factory-loading levels are reduced, and manning allows, it is beneficial to increase the sample size to enhance the collection of information. The self-learning model then combines the following elements of information: ■ Detailed knowledge of the stackup and materials used • Directly from CAM/PreCAM ■ Applied scale factors on each of the inner layers (artworks / LDI) • Directly from CAM ■ Measured scale error on each internal copper layer post lamination • Direct machine link Using this information, it is possible to use advanced mathematical methods to “parameterize the stackup” to break the stackup down into discrete material and interaction elements that influence the scale factor. The parameters are then determined by analysis of the layer-by-layer scale error occurring after lamination. By continuously feeding the model with stackup and 32 FiGurE 4. A graphic user interface. associated machine data, the model attains increasing prediction accuracy. Another benefit of such a system is that scale factor prediction (shown in FiGurE 3) is always up to date and current – using the most recently captured data for scale factor prediction to identify and take into account the effect of variation in material supply. In addition to feeding the self-learning model, the ability to analyze scale errors after lamination but before drilling allows for small compensations to be made to the drill program. We refer to this as reactive scale factor improvement. A GUI (graphic user interface) seen in FiGurE 4 allows operators, engineers and line managers to independently log in to view and to analyze data from any product lot – either in real time for drill compensation or for later analysis such as publishing a nondestructively generated “registration Certificate of Conformance” for supply to the end customer. In contrast to a standard microsection-based registration report, where the sectioned panel is sure to be a scrap circuit, this method can be guaranteed to be based on one or more of the circuits (panels) shipped to the customer. The reactive improvement system automatically compares the scale error on the measured panels against the available annular ring and drills to copper design rules. Where product is found to be out of tolerance or registration can be further improved, compensation algorithms automatically calculate a best-fit scaling that FEBRUARY 2009 printEd CirCuit dESign & fAB

Table of Contents Feed for the Digital Edition of Printed Circuit Design & Fab - February 2009

Printed Circuit Design & Fab - February 2009 Contents Our Line Market Watch Around the World Happenings ROI Tip Jar BGA Bulletin Interconnect Strategies Final Finsh Forum Defects Database Embedded Active Components In Multilayer LCP Packages Simulation: The Need for Speed Advanced Registration Systems The DC Design Squeeze Ad Index Do You Really Want a Better Autorouter? Designing With Conductive Materials, Part 1 Off th eShelf Marketplace On the Forefront

Printed Circuit Design & Fab - February 2009

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