作者: N. N. Z. GINDY , T. M. RATCHEV , K. CASE
DOI: 10.1080/00207549508904828
关键词: Computer-integrated manufacturing 、 Component (UML) 、 Data mining 、 Basis (linear algebra) 、 Measure (data warehouse) 、 Fuzzy clustering 、 Cellular manufacturing 、 Fuzzy logic 、 Group technology 、 Mathematics 、 Artificial intelligence
摘要: The variety of the currently available component grouping methodologies and algorithms provide a good theoretical basis for implementing GT principles in cellular manufacturing environments. However, practical application approaches can be further enhanced through extensions to widely used development criteria partitioning components into an ‘optimum’ number groups. Extensions fuzzy clustering algorithm definition new validity measure are proposed this paper. These aimed at improving applicability approach family formation Component is based upon assessing compactness within group overlapping between developed methodology experimentally demonstrated using industrial case study several well known examples from published literature.