During the semiconductor fabrication process each wafer goes through a product specific
sequence of operations (hundreds) in batches - lots. Every lot goes through each operation in the sequence. At each operation a lot could go through only one of many tools performing the same function. Maximum number of tools could up to 25, and the number
of tools could be different from operation to operation. At the end of the manufacturing line many performance metrics are measured to monitor deviations from the desired target specifications. Often observed variation of a performance metric is caused by a subset of
tools with effects of the problematic tools potentially changing in time.
The simulated dataset closely reproduces the nature and complexity of the tool level fault isolation problem engineers face in the semiconductor manufacturing. It records every tool and time stamp at every operation every lot went through (predictors), and the corresponding numeric performance measure (target).
The goal is to recover a subset of influential/
probelmatic operations/tools and the corresponding contributions in time to the variation of the numeric performance metric. Graphical representation like on the figures 1, 2 would be the best (that includes constant offset-shifts), pure interactions could be shown
as nested boxplots.