Process quality improvement usually can be achieved through reducing o
utput variability and process failure rate. Traditional economic decis
ions about the target of process quality improvement focus on the trad
eoff between investment costs and the direct benefit realized from the
improved process. Given characteristics of an improved process, a sch
eme for statistical process control may be redesigned to have appropri
ate values of inspection interval, sample size, and control limits. Th
is approach treats the determinations of the process improvement targe
t and the control chart parameters both independently and sequentially
. Through computational experiments, this research compares the cost e
ffectiveness of simultaneous decisions on the process improvement targ
et and on the control chart parameters to a sequential approach. The s
ystem examined is monitored with an (X) over bar control chart. Proces
s quality of two kinds - output variability and process failure rate -
are discussed. The cost of process improvement was assumed to be a lo
garithmic function. The results reveal that pursuit of a lofty process
improvement target can decrease total system costs.