CFP

   Call for Papers in Book
   DATA MINING FOR DESIGN AND MANUFACTURING:
   Methods and Applications

   Editor: Dr. Dan Braha

   Kluwer Academic Publishers

Data Mining for Design and Manufacturing: Methods and Applications will be
published by Kluwer Academic Publishers. The book is a volume in a series
called "Massive Computing" that is organized by James Abello (AT&T Labs
Research), Panos Pardalos (Univ. of Florida) and Mauricio Resende (AT&T
Labs Research). The book is especially important since it will bring
together the latest research and practice on the relationship between data
mining and design and manufacturing environments.


DESCRIPTION AND PURPOSE OF THE BOOK:

Data Mining for Design and Manufacturing: Methods and Applications will
bring together the latest research and practice on the relationship
between data mining and design and manufacturing environments. Topics
include data warehouses, marts, process, tasks, (e.g., association,
clustering, classification, forecast), methods (e.g., statistics, decision
trees and rules, neural networks, fuzzy learning, and case-based
reasoning); machine learning in design (e.g., knowledge acquisition,
learning in analogical design, conceptual design, and learning for design
reuse); data mining for product development and concurrent
engineering; design and manufacturing warehousing; computer-integrated
manufacturing (CIM) and data mining; data mining for Material Requirements
Planning (MRP); Enterprise Resource Planning (ERP) and Workflow
Management; process and quality control; process analysis; data
representation/visualization; fault diagnosis; adaptive schedulers; and
learning in robotics. The contributors will include leading researchers
and practitioners from academia and industry.

Data Mining is defined as the process of extracting valid, previously
unknown, comprehensible information from large databases in order to
improve and optimize business decisions. Data mining methods have been
used in various industrial fields, and have led to a broad range of
research efforts. Powerful computerized integrated design and
manufacturing tools (such as CAD, CAM, MRP and ERP) for collecting and
managing data are in use in virtually all mid-range and large
manufacturing companies. Over time, more and more product development,
design, operation, and performance data are accumulated and computerized
during product design and manufacturing processes. The abundance of data
generated and collected during daily operations has impeded the ability to
extract useful knowledge. In design and manufacturing environments, this
situation calls for new techniques and tools that can intelligently and
(semi)automatically turn low-level data into high-level and useful
knowledge.

The first of its kind, the objective of this book is to demonstrate the
potential of data mining in design and manufacturing environments. The
book provides an explanation of how data mining technology can be employed
beyond prediction and modeling, and how to overcome several central
problems in design and manufacturing environments. Practitioners can gain
insight on how data mining is integrated with standard CAD/CAM, MRP, and
ERP Systems. The book also presents the formal tools required to extract
valuable information from design and manufacturing data (e.g., patterns,
trends, associations, and dependencies), and thus facilitates
interdisciplinary problem solving and optimizes design and manufacturing
decisions.

For details, contact Dan Braha at brahad@bgumail.bgu.ac.il
or see
http://www.bgu.ac.il/iem/staff/Braha/Data-Mining-Book.htm