SMT007 Magazine


Issue link:

Contents of this Issue


Page 78 of 95

June 2017 • SMT Magazine 79 7. Zhen (Jane) Feng, Ph.D., Juan Carlos Gonza- lez, Sea Tang, Murad Kurwa, and Evstatin Krastev, Non-Destructive Techniques For Identifying De- fect In BGA Joints: TDR, 2DX, And Cross-Section/ SEM Comparison, SMTAI Conference, 2008. Editor's Note: This paper was originally pub- lished in the proceedings of SMTA International, 2016. Paul D. Scott, Ph.D., is innovation manager at IBEX Innovations. Evstatin Krastev, Ph.D., P.E., is director of Applications for Test and Inspection at Nordson Dage. 2D X-RAY INSPECTION WITH MATERIALS AND THICKNESS IDENTIFICATION References 1. Evstatin Krastev and John Tingay, Recent Advances in the X-ray Inspection Technology with Emphasis on Large Board Computer Tomog- raphy and Automation, PanPac Microelectronics Symposium, 2014. 2. Evstatin Krastev, D. Bernard, Dragos Gol- ubovic, 3D Board Level X-ray Inspection via Limited Angle Computer Tomography, SMTAI Conference, 2012. 3. S. Sethuraman et al., The Effect of Process Voiding on BGA Solder Joint Fatigue Life Measured in Accelerated Thermal Cycling, SMTAI Confer- ence, 2007. 4. D.Hillman et al., The Last Will and Testa- ment of the BGA Void, SMTAI Conference, 2011. 5. G. Qin et al., Assessing the Impact of Tem- perature Cycling Reliability of High Levels of Void- ing in BGA Solder Joints, SMTAI Conference, 2012. 6. Evstatin Krastev & D. Bernard, Modern 2D/3D X-ray Inspection—Emphasis on BGA, QFN, 3d Packages, and Counterfeit Components, Pan Pacific Symposium Conference Proceedings, 2010. The Intelligence Advanced Research Projects Activity (IARPA), which sits within the Office of the Director of National Intelligence (ODNI), has embarked on a long-term research effort involv- ing a multi-institutional collaboration including LCN academics, to develop special-purpose algo- rithms and hardware that harness quantum effects to surpass conventional computing. Practical ap- plications include more rapid training of machine learning algorithms, circuit fault diagnostics on larger circuits than possible today, and faster op- timal scheduling of multiple machines on multi- ple tasks. Through a competitive Broad Agency An- nouncement process, IARPA has awarded a research contract in support of the Quantum En- hanced Optimization (QEO) pro- gram to the international team led by the University of Southern California. The University College London, the California Institute of Technology, Harvard University, Massachusetts In- stitute of Technology, University of California at Berkley, Saarland University, University of Water- loo, Tokyo Institute of Technology, Lockheed Mar- tin and Northrup Grumman are also key collab- orators. Participants providing validation include NASA Ames Research Centre and Texas A&M, and those providing government-furnished hardware and test bed capabilities include MIT Lincoln Lab- oratory and MIT. "The goal of the QEO program is a design for quantum annealers that provides a 10,000-fold in- crease in speed on hard optimization problems, which improves at larger and larger problem sizes when compared to conventional computing methods," said Dr Karl Roenigk, QEO program manager at IARPA. If successful, technology developed under this program will provide a plausible path to perfor- mance beyond what is possible with today's computers. LCN Collaborates in IARPA-Funded QEO Program

Articles in this issue

Archives of this issue

view archives of SMT007 Magazine - SMT-Jun2017