A structured planning process that systematically incorporates the voice of the customer into product design, Quality Function Deployment (QFD) has proven itself a highly effective development tool for creating globally competitive products - in software, hardware, services, and many other industries. This book not only explains QFD fundamentals clearly and concisely, it takes you well beyond the basics to provide the advanced techniques, specific information, and concrete examples you need to implement QFD successfully and derive its full benefits. Of course, the book contains detailed information about the House of Quality, the most commonly used QFD matrix that relates customer needs to technical solutions. But rather than stopping there, it goes even further to explore the many possibilities for matrices that you can apply to every phase in product development - including multiple levels of design detail, quality improvement planning, process planning, manufacturing equipment planning, and value engineering planning. In addition, you will find concise, experienced-based guidance on all the practical aspects of implementing QFD from start to finish, including such issues as establishing organizational support, creating a schedule, and gathering customer data. The book also covers QFD's relationship to the product development cycle, as well as its impact on various functions within an organization.

Quality Function Deployment: How to Make Qfd Work for You

Business & Money

Cohen, Lou

Management & Leadership

PRENTICE/HALL

Practical Statistics for Field Biology

Provides an excellent introductory text for students on the principles and methods of statistical analysis in the life sciences, helping them choose and analyse statistical tests for their own problems and present their findings. An understanding of statistical principles and methods is essential for any scientist but is particularly important for those in the life sciences. The field biologist faces very particular problems and challenges with statistics as "real-life" situations such as collecting insects with a sweep net or counting seagulls on a cliff face can hardly be expected to be as reliable or controllable as a laboratory-based experiment. Acknowledging the peculiarites of field-based data and its interpretation, this book provides a superb introduction to statistical analysis helping students relate to their particular and often diverse data with confidence and ease. To enhance the usefulness of this book, the new edition incorporates the more advanced method of multivariate analysis, introducing the nature of multivariate problems and describing the the techniques of principal components analysis, cluster analysis and discriminant analysis which are all applied to biological examples. An appendix detailing the statistical computing packages available has also been included. It will be extremely useful to undergraduates studying ecology, biology, and earth and environmental sciences and of interest to postgraduates who are not familiar with the application of multiavirate techniques and practising field biologists working in these areas.

Science & Math

Fowler, Jim

Jarvis, Phil

Biological Sciences

wiley

Provides an excellent introductory text for students on the principles and methods of statistical analysis in the life sciences, helping them choose and analyse statistical tests for their own problems and present their findings. An understanding of statistical principles and methods is essential for any scientist but is particularly important for those in the life sciences. The field biologist faces very particular problems and challenges with statistics as "real-life" situations such as collecting insects with a sweep net or counting seagulls on a cliff face can hardly be expected to be as reliable or controllable as a laboratory-based experiment. Acknowledging the peculiarites of field-based data and its interpretation, this book provides a superb introduction to statistical analysis helping students relate to their particular and often diverse data with confidence and ease. To enhance the usefulness of this book, the new edition incorporates the more advanced method of multivariate analysis, introducing the nature of multivariate problems and describing the the techniques of principal components analysis, cluster analysis and discriminant analysis which are all applied to biological examples. An appendix detailing the statistical computing packages available has also been included. It will be extremely useful to undergraduates studying ecology, biology, and earth and environmental sciences and of interest to postgraduates who are not familiar with the application of multiavirate techniques and practising field biologists working in these areas.

Jarvis, Philip

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