The reasons for the need of an iterative approach to experimentation are explained. The consequent implications in the use of screening designs (fractional factorials and other orthogonal arrays), response surface designs ...

When a process is such that there is appreciable delay in control action taking effect, minimal variance feedback control can require excessive adjustment. In this report it is supposed that the cost of making the adjustments ...

The problem of choosing a control scheme that minimizes the combined costs of monitoring, adjustment and being off-target is discussed. In addition to the various costs, the choice depends on the nature of the disturbance ...

In this paper we apply the strategy developed in Report 56 to a general second-order model with additional third-order terms. For this model we derive the robustness measure and give a series of tables of designs that are ...

The approach of Box and Jenkins was used to design a control algorithm for a feedback loop controlling the addition of dried gluten to breadmaking flour in a flour mill. The variations to be controlled were modeled by an ...

Experimental design is a powerful tool for quality improvement. In some situations, however, the design variables are subject to multiple linear constraints. In this report, we propose a class called projection designs ...

In this report, we discuss the analysis of projection designs proposed in Report #53. We show that analyzing projection designs is essentially the same as analyzing some traditional unconstrained designs such as factorial ...

In response to disturbing challenges ahead, leaders at the University of Wisconsin-Madison are committed to transform the institution to a Total Quality University. As a pilot project in the transformation, this paper ...

Quality control based on inspection and segregation is uneconomical and inefficient. To be effective, quality needs to be considered and planned at the product design stage. In this article we put what seems like detailed ...

In this report we show how to design CUSUM charts to monitor process variability. An eight step outline for the implementation of these charts is included.