16 September 1994 Knowledge-based very large scale integration (VLSI) process diagnostic system
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One of the most critical issues facing the semiconductor industry is process testing and evaluation. Correcting marginal or faulty processes quickly is essential to maintaining yield and throughput. Simulation, statistical process control, and final circuit electrical tests are the most common methods of approaching the testing and evaluation problem. Statistical process control techniques are used to monitor critical parameters at periodic intervals in the manufacturing process. The variation of the parameters is analyzed to assure the process is within specifications. Although this approach is able to detect and prevent many faults, it is unable to detect other faults that can lead to bad devices. Currently, final electrical and functional tests provide the most comprehensive information in terms of establishing circuit functionality and implementing the necessary process adjustments. However, specific process flaws are generally only detectable by indirect trial and error procedures. These trial and error procedures often require a process engineer to go through a number of iterations between the process and final test data to find the problem.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael E. Parten, Michael E. Parten, M. Kittappa, M. Kittappa, F. R. Zapata, F. R. Zapata, } "Knowledge-based very large scale integration (VLSI) process diagnostic system", Proc. SPIE 2336, Manufacturing Process Control for Microelectronic Devices and Circuits, (16 September 1994); doi: 10.1117/12.186801; https://doi.org/10.1117/12.186801


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