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

Yağcıoğlu E., Tekin A. T., Çebi F.

International Conference on Intelligent and Fuzzy Systems, INFUS 2021, İstanbul, Turkey, 24 - 26 August 2021, vol.308, pp.197-204 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 308
  • Doi Number: 10.1007/978-3-030-85577-2_23
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.197-204
  • Keywords: Demand forecast, Machine learning, Mass customization
  • Istanbul Technical University Affiliated: Yes


© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.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.