Statistical control charts have been widely and successfully used for monitoring the performance of industrial processes. Several modifications on the classic Shewhart charts have been proposed in the literature; they aim at providing better tools for monitoring processes with special characteristics. One such modification is the recently developed adaptive control charts. Although providing advantages over Shewhart charts, in particular by signaling out-of-control situations faster, there is no prolific literature on practical implementation of adaptive charts. In this article we propose an economic model for the design of adaptive control charts. We apply the model in a case study from the automotive parts industry, detailing the meaning and determination of model parameters. Adaptive and Shewhart control schemes are compared based on their control costs.
adaptive control charts; control chart economic model; automobile industry; statistical process control
