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6

Keats & Montgomery

The fourth paper by Enriąue Del Castillo presents a new algorithm and a graphical method for selecting economically optimal Shewhart x-bar charts for the short production run environment. This paper could have been included in the section on process economics and control charts, but we elected to place it here because we felt that the most important aspect of the paper is the short production run setting. This is an area that has been the subject of much research in recent years, and the paper by Del Castillo is a significant contribution. The main result of the paper can be captured in two simple graphs that allow selection of the optimal sample size, control limit width, and number of samples to take during a finite production run. A PASCAL codę is also presented as an altemative to the graphical optimization procedurę.

"A Graphical Aid for Analyzing Autocorrelated Dynamical Systems" by E. L. Russell III is the flfth paper in this section. The technique is an interactive data-exp!oratory technique that can aid statisticians and engineers in determining the form of a time series model, detecting shifts in model form, and checking for time series outliers. An example of using the technique to assist in fitting a time series model is presented.

The sixth paper is entitled "Process Capability: Engineering and Statistical Issues," and is co-authored by J. J. Pignatiello, Jr. and J. S. Ramberg. This is an excellent paper that clearly and effectively summarizes the use of process capability indices and the many problems associated with the construction and interpretation of these quantities. The authors also offer altematives, including much practical advice on how to conduct a process capability study.

The last paper is "Achieving Quality Results Through Blended Management" by D. E. Parvey. The author observes that in order to effectively implement quality improvement in most organizations, management must fully understand employee motivation and utilize all of the resources of the organization. Effective quality management is a blend of top-down management direction and bottom-up employee involvement.

Rcfercnces

Keats, J. B. and Hubele, N. F. (1989), Statistical Process Control in Automated Manufacturing, Marcel Dekker, New York.

Keats, J. B. and Montgomery, D. C. (1991), Statistical Process Control in Manufacturing, Marcel Dekker, New York.