June 12, 2005
June 12, 2005
June 15, 2005
10.1236.1 - 10.1236.8
Teaching the Significance of Data Correlation in Semiconductor Testing Rainer J. Fink Department of Engineering Technology and Industrial Distribution Texas A&M University College Station, TX 77843-3367 email@example.com
Texas A&M University offers a two course sequence in mixed-signal semiconductor testing. Although most educational institutions offer courses in the utilization of electronic devices, very few have the state- of-the-art facilities to investigate the real life device performance. The Semiconductor Test Initiative was created as a natural interconnect between our digital and analog course sequences. Significant support from Texas Instruments, Teradyne, as well as National Instruments allowed the creation of a state-of-the- art semiconductor testing facility to support research and academics. In a real-life scenario, data acquired from a single testing source is suspect until verified using a second trustworthy testing resource. This concept is investigated using two device families: Digital-to-Analog Converters as well as Analog-to- Digital Converters in a course entitled Advanced Mixed-Signal Test and Measurement. Using resources in the Texas Instruments Mixed-Signal Test Laboratory at Texas A&M University, results obtained using National Instruments LabVIEW and DAQ hardware are compared to data obtained using a state-of-the-art Teradyne A567 automated semiconductor tester. Deviations in results obtained using each test resource are investigated. “Damaged” devices are interspersed within a 100 chip set to assure coverage in the student generated test solution as well as demonstrate statistical concepts.
Definition: Correlation – ability to get the same answer using different pieces of hardware or software.
Students at Texas A&M University are uniquely suited to explore the affects of high tech semiconductor testing methodologies and correlation issues between state-of-the-art bench-top test equipment and industrial automated test platforms. Currently the Electronics Engineering Technology Program at Texas A&M University offers two courses in Mixed-Signal semiconductor testing as well as one course in Digital Circuit testing. This paper explores the academic implementation of semiconductor testing as performed in our Advanced Mixed-Signal Testing course on Digital-to-Analog Converters (DACs).
In a real-life scenario, data acquired from a single testing source is suspect until verified using a second trustworthy testing resource, a concept known as correlation. The use of both LabVIEW powered bench top instruments with DAQ hardware and a Teradyne A567 automated test instrument allows the test engineering student to collect data and correlate between test platforms. By utilizing a DAC0808 as a test chip, it was possible to correlate the data between a Teradyne A567 tester and a National Instruments test system with LabVIEW 7.1 and a PCI-6025E Data Acquisition Card. Several test related issues were explored: limitation of equipment capability, speed of equipment, loading issues, and circuit board designs that resulted in correlation failures. In testing the DAC0808, statistical variations in results of absolute error, gain error, offset error, Differential Nonlinearity (DNL), and Integral Nonlinearity (INL) were determined using all codes testing as well as major carrier testing. Deviations in results obtained using each test resource were investigated. “Damaged” devices were interspersed within a 100 chip set to assure coverage in the student generated test solution as well as to demonstrate chip failure concepts.
Proceedings of the 2005 American Society for Engineering Education Annual Conference & Exposition Copyright 2005, American Society for Engineering Education
Fink, R. (2005, June), Teaching The Significance Of Data Correlation In Semiconductor Testing Paper presented at 2005 Annual Conference, Portland, Oregon. https://peer.asee.org/14717
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2005 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015