Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31352
Title: A neural network and CBR-based model for sewing minute value
Authors: Lai, KCL
Liu, JNK
Keywords: Case-based reasoning
Costing
Forecasting theory
Neural nets
Product development
Production planning
Sewing machines
Issue Date: 2009
Publisher: IEEE
Source: International Joint Conference on Neural Networks, 2009 : IJCNN 2009, 14-19 June 2009, Atlanta, GA, p. 1696-1701 How to cite?
Journal: International Joint Conference on Neural Networks, 2009 : IJCNN 2009, 14-19 June 2009, Atlanta, GA 
Abstract: Sewing minute value (SMV) is a benchmark to measure the production efficiency. It is an important business data for costing, production planning as well as key reference for product development. The traditional method to calculate SMV is complicated and not robust. There are so many rules to calculate SMV such as the speed of the machine or the motion of the machinist. It lacks randomness and flexibility. We proposed a new model which is based on neural network forecasting theory and case based reasoning technique. We will demonstrate the advantage of using the new method in this paper with better result representing an increase of 11% in accuracy compared to that of the old method.
URI: http://hdl.handle.net/10397/31352
ISBN: 978-1-4244-3548-7
978-1-4244-3553-1 (E-ISBN)
ISSN: 1098-7576
DOI: 10.1109/IJCNN.2009.5178803
Appears in Collections:Conference Paper

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