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

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

Analytic hierarchy process : An overview of applications

Theory of fuzzy integrals and its applications

Quality function deployment: A literature review

Many quality improvement (QI) programs including six sigma, design for six sigma, and kaizen require collection and analysis of data to solve quality problems. Due to advances in data collection systems and analysis tools, data mining (DM) has widely been applied for QI in manufacturing. Although a few review papers have recently been published to discuss DM applications in manufacturing, these only cover a small portion of the applications for specific QI problems (quality tasks). In this study, an extensive review covering the literature from 1997 to 2007 and several analyses on selected quality tasks are provided on DM applications in the manufacturing industry. The quality tasks considered are; product/process quality description, predicting quality, classification of quality, and parameter optimisation. The review provides a comprehensive analysis of the literature from various points of view: data handling practices, DM applications for each quality task and for each manufacturing industry, patterns in the use of DM methods, application results, and software used in the applications are analysed. Several summary tables and figures are also provided along with the discussion of the analyses and results. Finally, conclusions and future research directions are presented.

Review: A review of data mining applications for quality improvement in manufacturing industry

Regression analysis is a widely used statistical method for modelling relationships between variables. Multivariate adaptive regression splines (MARS) especially is very useful for high-dimensional problems and fitting nonlinear multivariate functions. A special advantage of MARS lies in its ability to estimate contributions of some basis functions so that both additive and interactive effects of the predictors are allowed to determine the response variable. The MARS method consists of two parts: forward and backward algorithms. Through these algorithms, it seeks to achieve two objectives: a good fit to the data, but a simple model. In this article, we use a penalized residual sum of squares for MARS as a Tikhonov regularization problem, and treat this with continuous optimization technique, in particular, the framework of conic quadratic programming. We call this new approach to MARS as CMARS, and consider it as becoming an important complementary and model-based alternative to the backward stepwise algo...

CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization

A Quality Function Deployment (QFD) approach to improve industrial engineering (IE) education quality at the Middle East Technical University (METU) is presented. Major stakeholders of IE education are identified as students, faculty members and future employers of the students. Requirements of these groups from an IE graduate are determined by surveys and interviews with them. These requirements are prioritized. Main education requirements are identified to meet the stakeholders' requirements. Finally, the results and plans for future studies are given.

Planning and design of industrial engineering education quality

http://mmf2.ogu.edu.tr/sanagun/Docs/Dok36.pdf

Determination of optimal product styles by ordinal logistic regression versus conjoint analysis for kitchen faucets

In this study, Data Envelopment Analysis is used to measure relative efficiencies of academic departments of an engineering college Input and output criteria are determined and measured utilizing the academic personnel performance measurement scheme of the College New measures are developed to compare departments of different disciplines The discriminating power of the measurement models is improved by restricting criteria weights directly and by using a multiple criteria decision making approach Sensitivity of the results to exclusion of a criterion and changes in relative importance of the criteria is analyzed Evaluation of the results jointly by the college administration and the departments is explained for a successful efficiency improvement mechanism

Gülser Köksal

Papers

Review: A review of data mining applications for quality improvement in manufacturing industry

CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization

Planning and design of industrial engineering education quality

Determination of optimal product styles by ordinal logistic regression versus conjoint analysis for kitchen faucets

The relative efficiency of departments at a Turkish engineering college: A data envelopment analysis