Production Scheduling of Small Batch Materials Based on BP Neural Network

DOI

10.2991/978-94-6463-447-1_19How to use a DOI?

Keywords

ABC classification; BP neural network; Demand forecast; Error rate

Abstract

In view of the production process of multi variety and small batch materials, six main materials were selected as the research object by using ABC classification method. On this basis, a prediction model based on BP neural network is constructed. The model is applied to six important material demand forecasting, and the results show that the average prediction error of BP neural network is only 1.96%. This method can help enterprises make reasonable production plans, so as to obtain greater profits.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Guanghui Yan
AU  - Lianjun Cheng
PY  - 2024
DA  - 2024/07/14
TI  - Production Scheduling of Small Batch Materials Based on BP Neural Network
BT  - Proceedings of the 2024 3rd International Conference on Engineering Management and Information Science (EMIS 2024)
PB  - Atlantis Press
SP  - 166
EP  - 172
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-447-1_19
DO  - 10.2991/978-94-6463-447-1_19
ID  - Yan2024
ER  -