The statistical process control gives the opportunity to reduce the risk of batch faults and therefore potentially reduces the reconditioning costs or the loss of a whole batch.
Six Sigma is a measure for the statistical certainty, to which extend the process is, within the specification Limits. Usually the statistical process control is realized using a normal distribution. But what if a normal distribution does not describe the process data?
This contribution will give insight to applications of the SEMI C64 Ship to control algorithm, the use for non-normal distributed process data and the effects of the skewness of process data as well as the number of available measurements on the calculated control limits. It will also report experiences applying C64 algorithm to real-life-data. The authors will give insight to the Implementation in JSL as well as the Integration in JMP and give an estimate for the applicability for real processes.