Issue No. 05 - October (1996 vol. 11)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/64.539020
<p>Polymer composites--lightweight, strong, and energy-efficient materials--offer significant advantages to durable-goods manufacturers and to performance-driven markets such as the aerospace industry. In describing a knowledge-based architecture they've developed for automating the design of such materials, the authors trace the evolution of their approach to polymer composites design.</p> <p>Over the last several years, an effort has been underway in the Intelligent Systems Laboratory at Michigan State University to develop a knowledge-based system for designing polymer composite materials. The Composite Materials & Structures Center, also at Michigan State, has helped facilitate much of this work. The Advanced Computing Thrust (ACT) combines the generic task approach of the ISL with the expert composites knowledge of the CMSC and has led to the development of several successful prototypes for the design of polymer composite materials. This article looks at the development and evolution of both the ideology and methodology behind the work on this project.</p> <p>Polymer composites consist of a reinforcing structural constituent and a protective polymer matrix. The properties of the combined material are significantly better than the sum of the properties of each component, giving materials with high strength-to-weight ratios. As a result, polymer composite parts are generally 20 to 30% lighter than the corresponding metal parts. The study of polymer composites focuses on the properties and fabrication of materials and is based largely on polymer science and chemical engineering. This area is inherently multidisciplinary. A key to realizing the potential of polymer composite materials is enabling a rapid transition from the setting of material specifications to the successful commercial manufacturing of a material that meets those specifications. Presenting an intelligent decision-support system for composites design to address this challenge becomes increasingly important as polymer composite materials penetrate the durable goods markets and as performance-driven markets, such as aerospace, become more cost-conscious. Knowledge-based systems, in the context of polymer composites design, facilitate the use and reuse of engineering design knowledge, thus enabling the transfer of expertise and freeing design engineers for more creative tasks. </p> <p>We approach the intelligent decision-support system for polymer composites design from the perspective of generic tasks. For example, in designing materials, we use routine design (a generic task). This type of design is possible in a domain where effective problem decomposition and compiled design plans are explicitly known. Such a situation exists for polymer composite materials. Material design for polymer composites involves mapping from environmental and performance requirements (mechanical, thermal, optical, electrical, and chemical) to choices for fiber, matrix, and chemical agents. The issues of manufacturing technology choice, processing parameters, and specific part architecture are also important in the design of polymer composites, and we considered these issues in developing the decision-support systems.</p> <p>Others have applied a knowledge-based approach to the design of materials. Ingemar Hulthage et al. used both qualitative and quantitative information in designing aluminum alloys. Rangarajan Pitchumani et al. and Andreas Nitsche et al. each focused on an integrated design system for composites, except that they addressed ceramic and metal matrix composites instead of polymer matrix composites. The first of these employed a routine-design methodology of sorts, but considered the decomposition of composites design in a different manner than what we present. The latter used a more traditional approach to composites design: coupling finite-element modeling (FEM) with a database and a model of material behavior.</p> <p>This article summarizes the salient points of routine design employed throughout the development of the composites design architecture, and looks at the four material designers that the architecture implements using ParcPlace-Digitalk's Smalltalk. We compare these material designers by examining the dynamic global view of polymer composites design and of material design. We also elucidate notable features of each system through a benchmark design example. Finally, by comparing the initial and current approaches, we illustrate the differences in both methodology and ideology that have arisen in the evolution of this knowledge-based system.</p>
J. K. McDowell, J. Sticklen, A. Kamel, T. J. Lenz and M. C. Hawley, "The Evolution of a Decision Support Architecture for Polymer Composites Design," in IEEE Intelligent Systems, vol. 11, no. , pp. 77-83, 1996.