This textbook provides the tools, techniques, and industry examples needed for the successful implementation of design of experiments (DoE) in engineering and manufacturing applications. It contains a high-level engineering analysis of key issues in the design, development, and successful analysis of industrial DoE, focusing on the design aspect of the experiment and then on interpreting the results. Statistical analysis is shown without formula derivation, and readers are directed as to the meaning of each term in the statistical analysis. Industrial Design of Experiments: A Case Study Approach for Design and Process Optimization is designed for graduate-level DoE, engineering design, and general statistical courses, as well as professional education and certification classes. Practicing engineers and managers working in multidisciplinary product development will find it to be an invaluable reference that provides all the information needed to accomplish a successful DoE. Presents classical versus Taguchi DoE methodologies as well as techniques developed by the author for successful DoE; Offers a step-wise approach to DoE optimization and interpretation of results; Includes industrial case studies, worked examples and detailed solutions to problems.

This book offers a step-by-step guide to the experimental planning process and the ensuing analysis of normally distributed data, emphasizing the practical considerations governing the design of an experiment. Data sets are taken from real experiments and sample SAS programs are included with each chapter. Experimental design is an essential part of investigation and discovery in science; this book will serve as a modern and comprehensive reference to the subject.

A new breed of modern designers is on the way. These non-traditional industrial designers work across disciplines, understand human beings, as well as business and technology thus bridging the gap between customer needs and technological advancement of tomorrow. This book uncovers prospective designer techniques and methods of a new age of industrial design, whose practitioners strive to construct simple and yet complex products of the future. The novel frontiers of a new era of industrial design are exposed, in what concerns the design process, in illustrating the use of new technologies in design and in terms of the advancement of culturally inspired design. The diverse perspectives taken by the authors of this book ensure stimulating reading and will assist readers in leaping forward in their own practice of industrial design, and in preparing new research that is relevant and aligned with the current challenges of this fascinating field.

This book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments and statistical quality control. It is shaped by the experience of the two teachers teaching statistical methods and concepts to engineering students, over a decade. Practical examples and end-of-chapter exercises are the highlights of the text as they are purposely selected from different fields. Statistical principles discussed in the book have great relevance in several disciplines like economics, commerce, engineering, medicine, health-care, agriculture, biochemistry, and textiles to mention a few. A large number of students with varied disciplinary backgrounds need a course in basics of statistics, the design of experiments and statistical quality control at an introductory level to pursue their discipline of interest. No previous knowledge of probability or statistics is assumed, but an understanding of calculus is a prerequisite. The whole book serves as a master level introductory course in all the three topics, as required in textile engineering or industrial engineering. Organised into 10 chapters, the book discusses three different courses namely statistics, the design of experiments and quality control. Chapter 1 is the introductory chapter which describes the importance of statistical methods, the design of experiments and statistical quality control. Chapters 2–6 deal with statistical methods including basic concepts of probability theory, descriptive statistics, statistical inference, statistical test of hypothesis and analysis of correlation and regression. Chapters 7–9 deal with the design of experiments including factorial designs and response surface methodology, and Chap. 10 deals with statistical quality control.

This book is about survival. It is about survival in a world that is changing. It is about survival in an occupation - management - that is almost unrecognizable from the viewpoint of only a few years ago, and one that will change even more rapidly in the future. It is about the ultimate survival tool: that of making oneself useful. Managers can be useful, but maybe not in the traditional sense. This book is written for managers who want to be useful by adding value to society in the form of useful products and services. It is not written for those who view personal advancement or wealth as their primary goal. Former Speaker of the US House of Representatives Thomas P. O'Neill was fond of saying 'All politics is local. ' I would like to appropriate that statement and paraphrase it for this book as 'All management is local. ' By that I mean that ultimately, after the global financing and market strategies are in place, and after the top-level missions and purpose of the organization are stated, the value-added manager must know what to do on Monday morning to get the product into the hands of the customer as quickly and efficiently as possible, and to be sure that the customer is successful in using the product. Increasingly, the top-level executive who creates the grand vision is also the manager who must implement it.

Offering invaluable insights from a chemist with over 35 years experience in the industry, this practical guide incorporates numerous practical examples and case studies to explain the concepts included here. The author explains the processes involved in product design, how to set up experiments, and ultimately how to scale-up. Among the host of topics covered is a discussion of recent advances in the fundamentals and innovative technologies leading to new and improved products. Industrial Product Design of Solids and Liquids: A Practical Guide is essential reading for the pharmaceutical, cosmetics and personal care, food, fragrance, paints, plastics and agricultural industries.

This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.

Failure modes and effects analysis (FMEA); Reliability; Product Development; Design Process; Test Procedures "Explore Product Design and Testing for Automotive Engineering: Volume II, an essential guide reshaping vehicle manufacturing with unprecedented reliability. As part of SAE International’s DOE for Product Reliability Growth series, this practical resource introduces cutting-edge methodologies crucial for predicting and improving product reliability in an era of automotive electrification. The book navigates statistical tolerance design, showcasing how variability in part fabrication and assembly can enhance reliability and sustainability. Key topics include: - Statistical tolerance design's impact on manufacturing and material selection, focusing on non-normal distributions' effects on product assembly and cost. Methods like maximum likelihood estimators and Monte Carlo simulations are used for assembly strategy synthesis. - Reliability DOEs using log-location-scale distributions to estimate lifetimes of non-normally distributed components, especially in accelerated life testing. It covers transformations optimizing parts and system designs under the lognormal distribution. - Weibull distribution (DOE-W) for characterizing lifetimes affected by various failure modes, detailing parameter assessment methods and real-world applications. The book also introduces reliability design of experiments based on the exponential distribution (DOE-E). - Importance of predicting lifecycles and enhancing reliability through qualitative and stepwise accelerated life tests. Integration of physics of failure with statistical methods like Weibull statistics and lognormal approximation enhances analysis credibility. - Inferential mechanisms such as the Arrhenius and Eyring models in predicting automotive component lifecycles, refining product life prediction based on reliability DOEs. Whether you're an engineer, researcher, or automotive professional, this book equips you to navigate reliability engineering confidently. Revolutionize your approach to product design and testing with Product Design and Testing for Automotive Engineering, your definitive companion in shaping the future of automotive reliability." (ISBN 9781468607703 ISBN 9781468607697 ISBN 9781468607727 DOI 10.4271/9781468607697)