Page 33 - Chip Scale Review_May June_2022-digital
P. 33

Better performance/improved
        architecture: best yield
          The goal of the signal deliver y
        improvements described above is
        opt i m i zat ion of the overall cost
        function. Traditionally, semiconductor
        test has been viewed as an added “cost
        of quality.” Many hours are devoted
        to highly optimizing the test process
        to reduce the cost of test, either by
        increasing throughput or lowering overall
        capital costs for the test cell and fixtures.
        The key is focusing test on optimizing
        yield through a balanced strategy of
        data analytics and yield learning, higher
        performing test solutions with improved
        accuracy and wider guard bands, or using
        test for trim and repair.
          As seen in Figure 5, a breakout of a
        typical device, even on a relatively high-
        yielding device, a minor improvement in
        yield (in this case 1%), produces almost
        10x the impact of the typical test cost
        optimizations, like reducing the hourly
        test cell cost, improving the overall test
        throughput by shortening the test time, or
        increasing parallel test efficiency.
          As the semiconductor indust r y
        ma rches for wa rd on t he pat h of
        technological advances, the economics
        of the manufacturing process must adapt
        to the higher costs of the silicon used
        to implement it. The path to achieve
        the best possible yields is enabled by
        the best possible ATE architectures
        integrated with the best possible
        interface performance.

        Reference
          1.  K .  R u p p ,  “ 4 0  Y e a r s o f
            Microprocessor Trend  Data,”
            Retrieved at: Our World in Data;
            https://ourworldindata.org/grapher/
            transistors-per-microprocessor








                       Biographies
                         Tucker Davis is the Product Manager for UltraFLEX plus , at Teradyne, North Reading, MA. He is focused
                       on complex digital devices, such as mobile application processors. Prior to joining Teradyne, he was an
                       Applications Engineer and Product Manager for National Instruments. Tucker holds a Master’s degree in
                       Electrical Engineering from the University of Oklahoma, where he graduated summa cum laude. Email: tucker.
                       davis@teradyne.com
                         Brian Brecht is an Engineering Manager at Teradyne, Agoura Hills, CA. With more than 25 years of
                       experience in the design of automated test equipment instruments and platforms. He holds a number of patents
          and has led design teams around the world in the delivery of high-performance device interface boards. In his current role, he is
          focused on advanced interface structures for testing next-generation devices.


                                                                                                             31
                                                               Chip Scale Review   May  •  June  •  2022   [ChipScaleReview.com]  31
   28   29   30   31   32   33   34   35   36   37   38