Data Mining for Design and Manufacturing

Data Mining for Design and Manufacturing PDF

Author: D. Braha

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 530

ISBN-13: 1475749112

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Data Mining for Design and Manufacturing: Methods and Applications is the first book that brings together research and applications for data mining within design and manufacturing. The aim of the book is 1) to clarify the integration of data mining in engineering design and manufacturing, 2) to present a wide range of domains to which data mining can be applied, 3) to demonstrate the essential need for symbiotic collaboration of expertise in design and manufacturing, data mining, and information technology, and 4) to illustrate how to overcome central problems in design and manufacturing environments. The book also presents formal tools required to extract valuable information from design and manufacturing data, and facilitates interdisciplinary problem solving for enhanced decision making. Audience: The book is aimed at both academic and practising audiences. It can serve as a reference or textbook for senior or graduate level students in Engineering, Computer, and Management Sciences who are interested in data mining technologies. The book will be useful for practitioners interested in utilizing data mining techniques in design and manufacturing as well as for computer software developers engaged in developing data mining tools.

Data Mining

Data Mining PDF

Author: Yong Yin

Publisher: Springer Science & Business Media

Published: 2011-03-16

Total Pages: 320

ISBN-13: 184996338X

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Data Mining introduces in clear and simple ways how to use existing data mining methods to obtain effective solutions for a variety of management and engineering design problems. Data Mining is organised into two parts: the first provides a focused introduction to data mining and the second goes into greater depth on subjects such as customer analysis. It covers almost all managerial activities of a company, including: • supply chain design, • product development, • manufacturing system design, • product quality control, and • preservation of privacy. Incorporating recent developments of data mining that have made it possible to deal with management and engineering design problems with greater efficiency and efficacy, Data Mining presents a number of state-of-the-art topics. It will be an informative source of information for researchers, but will also be a useful reference work for industrial and managerial practitioners.

Data Mining for Scientific and Engineering Applications

Data Mining for Scientific and Engineering Applications PDF

Author: R.L. Grossman

Publisher: Springer Science & Business Media

Published: 2001-10-31

Total Pages: 632

ISBN-13: 9781402001147

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Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Data Preparation for Data Mining

Data Preparation for Data Mining PDF

Author: Dorian Pyle

Publisher: Morgan Kaufmann

Published: 1999-03-22

Total Pages: 566

ISBN-13: 9781558605299

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This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mining in order to maximize mining performance.

Data Mining for Design and Marketing

Data Mining for Design and Marketing PDF

Author: Yukio Ohsawa

Publisher: CRC Press

Published: 2009-01-26

Total Pages: 338

ISBN-13: 1420070223

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Data Mining for Design and Marketing shows how to design and integrate data mining tools into human thinking processes in order to make better business decisions, especially in designing and marketing products and systems.The expert contributors discuss how data mining can identify valuable consumer patterns, which aid marketers and designers in de

Computational Intelligence in Design and Manufacturing

Computational Intelligence in Design and Manufacturing PDF

Author: Andrew Kusiak

Publisher: John Wiley & Sons

Published: 2000-05-22

Total Pages: 562

ISBN-13: 9780471348795

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Von der Produktidee über den Prototyp und die Modellsimulation bis zur Analyse: Dieser Band hilft Entwicklern und Designern beim Verständnis aller Abläufe im Zuge des Designs neuer Produkte, Prozesse und Systeme. Eine Fülle von Beispielen industrieller Anwendungen, realer Probleme und zugehöriger Lösungen hilft beim Vertiefen und Umsetzen des Stoffes. (05/00)

The Handbook of Data Mining

The Handbook of Data Mining PDF

Author: Nong Ye

Publisher: CRC Press

Published: 2003-04-01

Total Pages: 720

ISBN-13: 1410607518

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Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, The Handbook of Data Mining presents comprehensive coverage of data mining concepts and techniques. Algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials. This book is organized into three parts. Part I presents various data mining methodologies, concepts, and available software tools for each methodology. Part II addresses various issues typically faced in the management of data mining projects and tips on how to maximize outcome utility. Part III features numerous real-world applications of these techniques in a variety of areas, including human performance, geospatial, bioinformatics, on- and off-line customer transaction activity, security-related computer audits, network traffic, text and image, and manufacturing quality. This Handbook is ideal for researchers and developers who want to use data mining techniques to derive scientific inferences where extensive data is available in scattered reports and publications. It is also an excellent resource for graduate-level courses on data mining and decision and expert systems methodology.

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