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An Efficient Methodology for Multiple Fault Diagnosis Including Crosstalk Defects Using Multi-Objective Particle Swarm Optimizer

Authors(3):

Aiswarya A., Shiji A.S., Dr. Sreeja Mole S. S.
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Fault diagnosis plays an important role in improving yield of the VLSI IC manufacturing process. In this paper, we propose a multiple-fault-diagnosis methodology based on the analysis of failing primary outputs and the structure of the circuit under diagnosis. This work analyzes multiple faults simultaneously based on multiple fault simulation in a particle swarm optimization environment. Here, particle swarm optimization is proposed as a multi-objective optimization algorithm by considering crosstalk effect also. Experimental results show that our technique is highly efficient and effective in terms of diagnosability and diagnostic resolution. This approach does not put any restriction on the number of simultaneous faults and has approximately linear time complexity for multiple faults.

Aiswarya A., Shiji A.S., Dr. Sreeja Mole S. S.

Effect-Cause analysis, Fault Diagnosis, Fault Model, Multiple Fault Simulation, Particle Swarm Optimization (PSO), VLSI.

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Publication Details

Published in : Volume 1 | Issue 1 | January-Febuary - 2015
Date of Publication Print ISSN Online ISSN
2015-02-25 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
324-329 IJSRSET151171   Technoscience Academy

Cite This Article

Aiswarya A., Shiji A.S., Dr. Sreeja Mole S. S., "An Efficient Methodology for Multiple Fault Diagnosis Including Crosstalk Defects Using Multi-Objective Particle Swarm Optimizer", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.324-329, January-Febuary-2015.
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