Process quality improvement usually can be achieved through reducing output variability and process failure rate. Traditional economic decisions about the target of process quality improvement focus on the tradeoff between investment costs and the direct benefit realized from the improved process. Given characteristics of an improved process, a scheme for statistical process control may be redesigned to have appropriate values of inspection interval, sample size, and control limits. This approach treats the determinations of the process improvement target and the control chart parameters both independently and sequentially.Through computational experiments, this research compares the cost effectiveness of simultaneous decisions on the process improvement target and on the control chart parameters to a sequential approach. The system examined is monitored with anX̄control chart. Process quality of two kinds - output variability and process failure rate - are discussed. The cost of process improvement was assumed to be a logarithmic function. The results reveal that pursuit of a lofty process improvement target can decrease total system costs.