Abstract
Statistical process control (SPC) is a set of methodologies for signaling the presence of undesired sources of variation in manufacturing processes. SPC methods for continuous processes may be developed by using stochastic models which do not assume that successive observations are independent. A method for applying SPC to continuous processes is presented. This method incorporates a computationally efficient procedure for the on-line identification and estimation of autoregressive with exogenous inputs (ARX) models. Two examples illustrating the method for SPC monitoring are presented.
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