Knowledge-based material selection for injection-molded, thermoplastic parts

作     者：Alexander Porsch René Andrae Johannes Wortberg Peter Köhler 

作者机构：1University of Duisburg-Essen Institute of Product Engineering Department of Engineering Design and Plastics Machinery Lotharstraße 1 47057 Duisburg Germany 2University of Duisburg-Essen Institute of Product Engineering Department of Computer Aided Engineering Lotharstraße 1 47057 Duisburg Germany 

出 版 物：《AIP Conference Proceedings》 

年 卷 期：2019年第2055卷第1期

学科分类：07[理学] 0702[理学-物理学] 

摘      要：Material selection is an important but often an arbitrary process at the beginning of the development of injection-molded parts. Due to the absence of a sufficient documentation, it cannot be retraced and optimized by other engineers. The use of expert systems, which apply a comprehensive knowledge base, is a possibility to reduce mistakes and make decisions more transparent. In this paper, a knowledge-based method for material selection is presented. Basis of the method is a knowledge base containing information about the properties of thermoplastics. This includes for example single- and multi-point-data, or facts like chemical resistances. Moreover, additional information concerning the modification of the properties, correlations, or the exact definitions are stored in the knowledge base. It also contains knowledge about production processes like standard injection molding, MuCell, or injection-compression molding restricting the number of suitable materials. Additional knowledge about the influence of part design for material selection completes the knowledge base. Considering the vast amount of available thermoplastics, the presented knowledge base includes selected examples. Based on this knowledge, a multistage method is developed using questionnaires to refine requirements and to exchange information between engineer and expert system. During the selection process, additional information, as it has been mentioned before, is given. At the end of the process, the user gets a ranking of possible materials. In addition, more detailed knowledge about their properties, advantages, and disadvantages are provided. For the development and the visualization of the method, System Modeling Language diagrams are used. These allow different views to the material selection method, the stages, and links between knowledge base and selection process. Finally, the results are discussed, and an outlook for development potential is given.