Added Dimensions of Difficulty: Image Analysis and 3D Visualization in JMP
There is one constant in modern life. No, death and taxes don’t count. That constant is society’s desire for better performing and lower priced electronic widgets. It’s a first world problem to be sure, but most of us seem to have it. One of the results of this market demand is that semiconductor and MEMS manufacturing processes are now manipulating matter at a near atomic scale. This is a non-trivial exercise. Complicating matters further, devices have recently started moving from 2D, planar configurations to 3D, stacked circuit configurations. This shift has allowed for performance improvements without additional dimensional reduction, at the expense of additional manufacturing complexity.
The shift to 3D manufacturing has impacted many aspects of measurement science and defect analysis. Defect analysis in particular has moved from being a surface issue where buried defects are generally regarded as being unimportant to an issue where defects must be considered in all spatial dimensions. This means that your average defect map isn’t going to cut it much longer. We need something better. This work will examine the use of spatial clustering and multidimensional visualization techniques in JMP using data sets produced by two modern measurement systems with 2 and 3 dimensional imaging capability. These measurement systems are Scanning Acoustic Microscopy and X-ray Diffraction Imaging.