A distinguishing feature of Japanese quality improvement techniques is an emphasis on the designing of quality into the product and into the process that makes the product. In particular, experimental design is used to discover conditions that minimize variance and appropriately control the mean level. The direct estimation of variance by replication at each of the design points, however, can be excessively expensive in experimental runs. In this article we show how it is sometimes possible to use unreplicated fractional designs to identify factors that affect variance in addition to those that affect the mean.