Abstract
This paper examines cell quality performance improvement through the integration of data mining using Artificial Neural Network (ANN) techniques and cellular manufacturing. The aim of this paper is to study and predict the factors that impact quality product in cellular manufacturing, such as used material, material complexity, operation type (lathe, mill, thread, groove, bore, etc.), machine, machinist and quantity to improve cell performance. The outcome suggests improvement in the part processing sequence, machining process capability, formation of family products, design, the machine operator performance and work schedule in order to improve the machine performance in cellular manufacturing.
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