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Analyzing textual databases using data mining to enable fast product development processes
Authors:Rakesh Menon  Loh Han Tong  S Sathiyakeerthi
Affiliation:aDesign Technology Institute, E4-B0-01, Faculty of Engineering, National University of Singapore, 10, Kent Ridge Crescent, Singapore 119260;bDepartment of Mechanical Engineering, National University of Singapore, Singapore 119260;cSingapore-MIT Alliance, National University of Singapore, Singapore, Singapore 119260
Abstract:Currently, companies active in the design of high-tech products are confronted with a number of, often conflicting, challenges. Not only do they have to develop increasingly complex products in ever-shorter amounts of time but they also have to produce them cheaply for the local as well as global markets. In order to manage these conflicting trends adequately, as this paper will demonstrate, companies need to have high quality information at the right moment and at the right location. This serves as the motivation of this paper in which various databases within the product life cycle are examined. Due to the fact that unanticipated information plays a more and more dominant role, especially in highly innovative business processes, we focus our attention on textual databases since textual databases offer the best possibility to handle unanticipated free-formatted information. Also their treatment in the literature has thus far been scant. As will be demonstrated in this paper these databases have a huge potential for valuable information. Further, an analysis tool, data mining that could be used to analyse these textual databases so that we could extract information from them quickly and hence be able to access them at the right time when needed, is presented. We also highlight some of the difficulties faced when analyzing textual databases. Thus with the right information from the textual databases and the tools to deliver this information at the right time companies, would definitely be able to shorten development times and hence gain a competitive edge.
Keywords:Product development process  Textual databases  Data mining
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