A Proposed Approach for Production in ERP Systems Using Support Vector Machine Algorithm

ElMadany, Hassan and Alfonse, Marco and Aref, Mostafa (2021) A Proposed Approach for Production in ERP Systems Using Support Vector Machine Algorithm. International Journal of Intelligent Computing and Information Sciences, 21 (1). pp. 49-58. ISSN 2535-1710

[thumbnail of IJICIS_Volume 21_Issue 1_Pages 49-58.pdf] Text
IJICIS_Volume 21_Issue 1_Pages 49-58.pdf - Published Version

Download (885kB)

Abstract

Using machine learning in Enterprise Resource and Planning system, enable the organization to store, manage and analyze their data to get the right decisions and gain valued visions that were previously unimaginable. One of the most usages of machine learning in Enterprise Resource and Planning is forecasting. There are many industries and lines of business that contain large volumes of data such as manufacturing, finance, healthcare…etc. This paper introduces a proposed approach to how to use machine learning in the production module in Enterprise Resource and Planning systems. This approach is considered a novel attempt to enable Enterprise Resource and Planning system to make an automatic or semi-automatic decision in critical issues in manufacturing. The proposed approach is used for recommending a new combination of product raw materials using machine learning. It reduces the cost, time, and efforts to produce a new product design that will help the organization to improve its profitability.

Item Type: Article
Subjects: Archive Science > Computer Science
Depositing User: Managing Editor
Date Deposited: 27 Jun 2023 06:52
Last Modified: 22 Jun 2024 09:28
URI: http://editor.pacificarchive.com/id/eprint/1275

Actions (login required)

View Item
View Item