Özet
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.
Orijinal dil | İngilizce |
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Ana bilgisayar yayını başlığı | Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference |
Editörler | Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari |
Yayınlayan | Springer Science and Business Media Deutschland GmbH |
Sayfalar | 197-204 |
Sayfa sayısı | 8 |
ISBN (Basılı) | 9783030855765 |
DOI'lar | |
Yayın durumu | Yayınlandı - 2022 |
Etkinlik | International Conference on Intelligent and Fuzzy Systems, INFUS 2021 - Istanbul, Turkey Süre: 24 Ağu 2021 → 26 Ağu 2021 |
Yayın serisi
Adı | Lecture Notes in Networks and Systems |
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Hacim | 308 |
ISSN (Basılı) | 2367-3370 |
ISSN (Elektronik) | 2367-3389 |
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???event.eventtypes.event.conference??? | International Conference on Intelligent and Fuzzy Systems, INFUS 2021 |
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Ülke/Bölge | Turkey |
Şehir | Istanbul |
Periyot | 24/08/21 → 26/08/21 |
Bibliyografik not
Publisher Copyright:© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.