Effective application of Q(R) charts in low-volume manufacturing

Q charts provide means for statistical process control in low-volume proces ses and start-up phases of production. Concerns on their performance have l ed to research into different types of enhancements and much discussion on the appropriateness of these. Driven by the aim to implement control charts in the low-volume production of advanced wafer steppers, we investigate th e performance of additional run rules and tightening control limits on the traditional Q chart compared with an exponentially weighted moving average (EWMA). Furthermore, we develop an alternative QR chart based on the mean m oving range as estimator of the process standard deviation and consider the economics of low-volume processes by means of a specific cost model. The c omparisons are based on the run length distributions after a permanent shif t and trend, both with an onset early in the process. Real life examples ar e given for various important variables in wafer stepper production. It is concluded that the EWMA based on QR statistics provides the best performanc e throughout. Competing alternatives with almost equal performance are the EWMA of Q statistics and the combination of four tests of special causes (1 -of-1, 2-of-3, 4-of-5 and 8-of-8) applied on either the Q or QR chart. Over all, the mean moving range performs better. Copyright (C) 1999 John Wiley & Sons, Ltd.