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

ElMadany, Hassan; Alfonse, Marco; Aref, Mostafa

doi:10.21608/ijicis.2021.60741.1057

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

Document Type : Original Article

Authors

¹ Ph.D. student at Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

² Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

10.21608/ijicis.2021.60741.1057

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.

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