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Journal of Intelligence and Information Systems, Vol. 2, No. 1, June 1996
Feature Recognition of Prismatic Parts for Automated Process Planning : An Extended AAG Approach |
Won Chul Jhee, and Min-Sik Kim
Vol. 2, No. 1, Page: 45 ~ 58
Keywords : CAPP, Extended AAG, Composite Feature Recognition
Abstract
This paper describes an a, pp.oach to recognizing composite features of prismatic parts. AAG (Attribute Adjacency Graph) is adopted as the basis of describing basic feature, but it is extended to enhance the expressive power of AAG by adding face type, angles between faces and normal vectors. Our a, pp.oach is called Extended AAG (EAAG). To simplify the recognition procedure, feature classification tree is built using the graph types of EEA and the number of EAD's. Algorithms to find open faces and dimensions of features are exemplified and used in decomposing composite feature. The processing sequence of recognized features is automatically determined during the decomposition process of composite features.
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Job Route Selection Expert System for Workload Balancing in Flexible Flow Line |
Ho-Sang Ham, and Sung-Bae Han
Vol. 2, No. 1, Page: 93 ~ 107
Keywords : flexiable flow line (FFL), workload balancing, route selection model
Abstract
A flexible flow line(FFL) consists of several groups of identical machines. All work-orders flow along the same path through successive machine groups. Thus, we emphasized the balancing of workloads between machine groups in order to maximize total productivity. On the other hand, many different types of work-orders, in varying batch or lot sizes, are produced simultaneously. The mix of work-orders, their lot sizes, and the sequence in which they are produced affect the amount of workload. However, the work-orders and their lot sizes are prefixed and cannot be changed. Because of these reasons, we have developed an optimal route selection model using heuristic search and Min-Max algorithm for balancing the workload between machine groups in the FFL.
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