A neural network and CBR-based model for Sewing Minute Value

Author

Lai, Lucas K C ; Liu, James N K

Author_Institution

Dept. of Comput., HongKong Polytech. Univ., Kowloon, China

fYear

2009

fDate

14-19 June 2009

Firstpage

1696

Lastpage

1701

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.

Keywords

case-based reasoning; costing; forecasting theory; neural nets; product development; production planning; sewing machines; CBR-based model; business data; case based reasoning technique; costing; forecasting theory; machine speed; neural network; product development; production efficiency; production planning; sewing minute value; Costs; Databases; Machinery production industries; Manuals; Motion analysis; Neural networks; Power engineering and energy; Predictive models; Robustness; Time measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2009. IJCNN 2009. International Joint Conference on

Conference_Location

Atlanta, GA

ISSN

1098-7576

Print_ISBN

978-1-4244-3548-7

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2009.5178803

Filename

5178803