Historically, the term quality was used to measure performance in the context of products, processes and systems. With rapid growth in data and its usage, data quality is becoming quite important. It is important to connect these two aspects of quality to ensure better performance. This book provides a strong connection between the concepts in data science and process engineering that is necessary to ensure better quality levels and takes you through a systematic approach to measure holistic quality with several case studies. Features: Integrates data science, analytics and process engineering concepts Discusses how to create value by considering data, analytics and processes Examines metrics management technique that will help evaluate performance levels of processes, systems and models, including AI and machine learning approaches Reviews a structured approach for analytics execution

The book presents a systematic and efficient method to design high quality / reliability and high performance products / processes at low cost. Contains case studies from diverse engineering fields to describe Robust Design / Taguchi method.Some topics covered are: orthogonal arrays, Signal-to-Noise ratios as design quality metric, computer-aided robust design techniques, and more.

This book is written primarily for engineers and researchers who use statistical robust design for quality engineering and Six Sigma, and for statisticians who wish to know about the wide range of applications of experimental design in industry. It is a valuable guide and reference material for students, managers, quality improvement specialists and other professionals interested in Taguchi's robust design methods as well as the implementation of Six Sigma. This book can also be useful to those who would like to learn about the role of Robust Design within the Six Sigma (Improve phase) methodology and Design for Six Sigma (DFSS) (Optimize) methodology. It combines classical experimental design methods with those of Taguchi's robust designs, demonstrating their prowess in DFSS and suggesting new directions for the development of statistical design and analysis.

Powerful and elegantly simple. Achieve higher quality...lower costs...faster time to market Companies worldwide have used the methods of quality expert Genichi Taguchi for the past 30 years with phenomenal product development cost savings and quality improvements. Robust Engineering, by this three-time Deming Prize winner, along with Subir Chowdhury and Shin Taguchi, is the first book to explain and illustrate his newest, most revolutionary methodology, Technology Development. It joins Design of Experiments and Robust Design as the framework on which your company can build a competitive edge. Case studies of real-world organizations Ford, ITT, 3M, Minolta, NASA, Nissan, Xerox and 9 others show you how the techniques of all three methodologies can be successfully applied. You'll hammer flexibility into your manufacturing organization to minimize product development costs, reduce product time-to-market, and fully satisfy customers needs. Project Management is going to be huge in the next decade...--Fortune Busy managers single-source guide to planning, organizing and controlling projects At last there's a concise, compact (5Ó x 8Ó) hands-on guide that puts state-of-the-art management concepts and processes at your fingertips. Project Manager's Portable Handbook, by David I. Cleland and Lewis R. Ireland, is your step-by-step guide to the nuts-and-bolts details that spell project management success. YouÕre shown how to organize and manage everything from small to multiple projects...lead and coach project team members...and manage within a strategic context from project partnering to dealing with the board of directors and other stakeholders. You'll find out how to: Select and use PM software; Develop winning proposals; Handle legal considerations; Come out on top in contract

This book is written primarily for engineers who want to use statistical designs for quality engineering, and for statisticians who want to know the wide range of applications of experimental design in the manufacturing industry. Significantly, Robust Design and Analysis for Quality Engineering addresses the following techniques: Taguchi's quality engineering approaches, concepts of robustness in experimental designs, response surface design and its applications, Pareto-type ANOVA for analysis of parameter design, and strategies of quality improvement efforts through robust design and analysis. Through a series of real case studies, these important techniques are made readily accessible to all readers. This is also the key text for senior undergraduate and postgraduate students studying engineering and experimental design.

From the researcher who was one of the first to identify and analyze the infamous industrial control system malware "Stuxnet," comes a book that takes a new, radical approach to making Industrial control systems safe from such cyber attacks: design the controls systems themselves to be "robust." Other security experts advocate risk management, implementing more firewalls and carefully managing passwords and access. Not so this book: those measures, while necessary, can still be circumvented. Instead, this book shows in clear, concise detail how a system that has been set up with an eye toward quality design in the first place is much more likely to remain secure and less vulnerable to hacking, sabotage or malicious control. It blends several well-established concepts and methods from control theory, systems theory, cybernetics and quality engineering to create the ideal protected system. The book's maxim is taken from the famous quality engineer William Edwards Deming, "If I had to reduce my message to management to just a few words, I'd say it all has to do with reducing variation." Highlights include: - An overview of the problem of "cyber fragility" in industrial control systems - How to make an industrial control system "robust," including principal design objectives and overall strategic planning - Why using the methods of quality engineering like the Taguchi method, SOP and UML will help to design more "armored" industrial control systems.

Quality control is changing along with the manufacturing environment. A series of revolutionary changes will occur in management contents, methods, capabilities, and real-time effectiveness and efficiency of management. As an essential factor in intelligent manufacturing, quality control systems require real and comprehensive innovation. Focused on new trends and developments in quality control from a worldwide perspective, this book presents the latest information on novel approaches in quality control. Its thirteen chapters cover three topics: intelligent manufacturing, robust design, and control charts.