Demand Forecasting of a Company that Produces by Mass Customization with Machine Learning

Abstract

Machine Learning (ML) algorithms are designed to extract information from existing data. The application of ML in production; can provide the acquisition of new information from existing data sets that can form a basis for the development of approaches about how the system should be in the future. This further information can support company managers in their decision-making processes or can be used directly to improve the system. Given the challenge of a rapidly changing and dynamic production environment, ML; As part of artificial intelligence, it can learn about changes and adapt to them. Mass customization; recently, has started to influence the textile sector as in many sectors. As A result of changing consumer habits and developing technology; companies have begun to focus on this area to meet the increasing number of mass customized demands.This study aims to make demand estimation by using ML algorithms of a textile workshop that performs mass customization. The results show that ML algorithms have the result of successful demand forecast in organizations implementing mass customization when there is enough data.