This research article demonstrates the use of constraint networks for modelling the knowledge which is necessary for concurrent product and process design. A knowledge;based constraint network system has been developed to maintain design consistency and to support the selection of appropriate manufacturing processes according to pre-defined constraints. A number of constraints related to existing manufacturing facilities and expertise are formulated and modelled using the rules of the knowledge-based toolkit. These constraints are implemented to identify the appropriate machining processes and to show the feasibility of a product's design as it progresses and before making the final prototype. The combination of design and manufacturing constraints enables designers to examine whether the designed part can be manufactured with the available manufacturing facilities. (C) 1998 Elsevier Science Ltd. AII rights reserved.
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页码:459 / 462
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Bowen J., 1992, Artificial Intelligence in Engineering, V7, P199, DOI 10.1016/0954-1810(92)90013-R
机构:Group for Intelligent Systems in Designing and Manufacturing, Department of Industrial Engineering, North Carolina State University, Raleigh, NC, 27695-7906
YOUNG, RE
GREEF, A
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机构:Group for Intelligent Systems in Designing and Manufacturing, Department of Industrial Engineering, North Carolina State University, Raleigh, NC, 27695-7906
GREEF, A
OGRADY, P
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机构:Group for Intelligent Systems in Designing and Manufacturing, Department of Industrial Engineering, North Carolina State University, Raleigh, NC, 27695-7906
机构:Group for Intelligent Systems in Designing and Manufacturing, Department of Industrial Engineering, North Carolina State University, Raleigh, NC, 27695-7906
YOUNG, RE
GREEF, A
论文数: 0引用数: 0
h-index: 0
机构:Group for Intelligent Systems in Designing and Manufacturing, Department of Industrial Engineering, North Carolina State University, Raleigh, NC, 27695-7906
GREEF, A
OGRADY, P
论文数: 0引用数: 0
h-index: 0
机构:Group for Intelligent Systems in Designing and Manufacturing, Department of Industrial Engineering, North Carolina State University, Raleigh, NC, 27695-7906