FACT: A new neural network-based clustering algorithm for group technology

被引:35
作者
Kamal, S
Burke, LI
机构
[1] Orefield, PA, 18069
关键词
D O I
10.1080/00207549608904943
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper introduces the FACT (Fuzzy art with Add Clustering Technique) algorithm which is a new neural network-based clustering technique. FACT can be trained to cluster machines and parts for cellular manufacturing under a multiple objective environment. The existing GT clustering techniques are mainly concerned with grouping parts and machines based on only one criterion which is the parts' processing routes. The FACT algorithm is able to consider several similarity criteria such as parts' processing routes, design requirements of parts, processing time on each machine, and demand for each part. The FACT algorithm, which is based on the fuzzy ART neural network, is powerful enough to solve problems of real-world sized complexity.
引用
收藏
页码:919 / 946
页数:28
相关论文
共 63 条
[1]  
ABE S, 1992, INT JOINT C NEUR NET, V1, P619
[2]  
ANDERBERG M, 1973, CLUSTER ANAL APPLICA
[3]  
[Anonymous], 1980, Automation, production systems, and computer-integrated manufacturing
[4]   A GRAPH PARTITIONING PROCEDURE FOR MACHINE ASSIGNMENT AND CELL-FORMATION IN GROUP TECHNOLOGY [J].
ASKIN, RG ;
CHIU, KHS .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1990, 28 (08) :1555-1572
[5]   A WITHIN-CELL UTILIZATION BASED HEURISTIC FOR DESIGNING CELLULAR MANUFACTURING SYSTEMS [J].
BALLAKUR, A ;
STEUDEL, HJ .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1987, 25 (05) :639-665
[6]   QUANTIFYING DATA FOR GROUP TECHNOLOGY WITH WEIGHTED FUZZY FEATURES [J].
BENARIEH, D ;
TRIANTAPHYLLOU, E .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1992, 30 (06) :1285-1299
[7]  
Burbidge J.L, 1975, INTRO GROUP TECHNOLO
[8]  
Burke L., 1992, P C ARTIFICIAL NEURA, V1, P779
[9]   CLUSTERING CHARACTERIZATION OF ADAPTIVE RESONANCE [J].
BURKE, LI .
NEURAL NETWORKS, 1991, 4 (04) :485-491
[10]   FUZZY ART - FAST STABLE LEARNING AND CATEGORIZATION OF ANALOG PATTERNS BY AN ADAPTIVE RESONANCE SYSTEM [J].
CARPENTER, GA ;
GROSSBERG, S ;
ROSEN, DB .
NEURAL NETWORKS, 1991, 4 (06) :759-771