Affiliation:
1. Materials Science and Technology Division, Oak Ridge National Laboratory, MS-6155, Building 4500-S, Oak Ridge, TN 37831
2. Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK
3. Structures and Materials Division, NASA Glenn Research Center, 21000 Brookpark Road, MS 49-7, Cleveland, OH 44135
Abstract
This paper discusses key principles for the development of material property information management software systems. The growing need for automated material information management is fueled, in part, by the demand for higher efficiency in material testing, product design, and engineering analysis. But equally important, organizations are being driven by the need for consistency, quality, and traceability of data, as well as control of access to proprietary or sensitive information. Further, the use of increasingly sophisticated nonlinear, anisotropic, and multiscale engineering analyses requires both processing of large volumes of test data for the development of constitutive models and complex material data input for computer-aided engineering software. Finally, the globalization of economy often generates great needs for sharing a single “gold source” of material information between members of global engineering teams in extended supply chains. Fortunately, material property management systems have kept pace with the growing user demands and have evolved into versatile data management systems that can be customized to specific user needs. The more sophisticated of these provide facilities for (i) data management functions such as access, version, and quality controls; (ii) a wide range of data import, export, and analysis capabilities; (iii) data “pedigree” traceability mechanisms; (iv) data searching, reporting, and viewing tools; and (v) access to the information via a wide range of interfaces. In this paper, the important requirements for advanced material data management systems, future challenges, and opportunities, such as automated error checking, data quality characterization, identification of gaps in data sets, as well as functionalities and business models to fuel database growth and maintenance are discussed.
Subject
Mechanical Engineering,Mechanics of Materials,Safety, Risk, Reliability and Quality
Cited by
1 articles.
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