THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Economic Control of Quality of Manufactured Product.

THE NEED FOR QUALITY The first thing that we need to consider, in any organization, is that quality is the most important thing. The quality of your work defines you.  Whoever you are,  Whatever you do,  I can find the same products and services cheaper somewhere else. But your quality is your signature. Developing and delivering high quality products and services means that you are doing things correctly from the beginning. As a consequence, you are reducing the need for additional services, from verification to warranty.

Total quality management.

Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications

Dynamic optimization: The calculus of variations and optimal control in economics and management: Morton I. KAMIEN and Nancy L. SCHWARTZ Volume 4 in: Dynamic Economics: Theory and Applications, North-Holland, New York, 1981, xi + 331 pages, Dfl.90.00

This paper presents a synthetic control chart that is an integration of the Shewhart X chart and the conforming run length chart. Like the Shewhart X chart, the synthetic chart is used to detect ...

A Synthetic Control Chart for Detecting Small Shifts in the Process Mean

Adaptive CUSUM charts, referred to as ACUSUM charts, have attracted considerable attention from the research community. By adjusting the reference parameter k dynamically, an ACUSUM chart may achieve a better performance over a range of mean shifts than conventional CUSUM charts that are designed for maximal detection effectiveness at a particular level of process shift. This article studies a new feature of the ACUSUM chart related to an additional charting parameter w, i.e., the exponential of the sample mean shift in (x t – μ 0) w . The ACUSUM chart can be enhanced by adapting this parameter w according to the on-line estimated value of the mean shift, in conjunction with the reference parameter k. The testing cases reveal that this new adaptive CUSUM chart not only outperforms the earlier ACUSUM chart to a substantial degree, but also works as well as the most effective combined schemes consisting of a few CUSUM and/or charts. Furthermore, this enhanced ACUSUM chart is easier to design and implement in a computerized environment compared with those combined schemes. In addition, a general-purpose optimization algorithm is proposed to assist the designs of various CUSUM charts. This paper demonstrates that this algorithm can significantly improve the performance of many CUSUM charts over the entire process shift range. Moreover, a systematic performance comparison of eight CUSUM charts is presented. The findings from this comparison are useful aids for SPC practitioners to select an appropriate CUSUM chart for real applications.

An enhanced adaptive CUSUM control chart

Swarm intelligence applied in green logistics: A literature review

A comparison study of effectiveness and robustness of control charts for monitoring process mean

An algorithm was developed for the optimization design of control charts based on the probability distribution of the random process shifts (e.g. mean shift). The design objective was to minimize the overall mean of Taguchi's loss function per out-of-control case (denoted as ML) by adjusting the sample size, sampling interval and control limits of the chart in an optimal manner. The optimal chart was therefore named as the ML chart. A three-phase operational scenario for statistical process control (SPC) was also proposed to design and operate the ML chart. The probability distribution of the mean shifts can be modelled by a Rayleigh distribution based on the sample data of the mean shifts acquired in the three-phase scenario. Unlike in the economic control chart designs, the design of the ML chart only requires a limited number of specifications that can be easily determined. The results of the comparison studies show that the ML chart is significantly superior to the Shewhart control chart in view of ov...

https://www.tandfonline.com/doi/pdf/10.1081/00207540310001614169

Zhang Wu

Papers

A Synthetic Control Chart for Detecting Small Shifts in the Process Mean

An enhanced adaptive CUSUM control chart

Swarm intelligence applied in green logistics: A literature review

A comparison study of effectiveness and robustness of control charts for monitoring process mean

Optimization design of control charts based on Taguchi's loss function and random process shifts