Predicting cycle times in textile manufacturing using artificial neural network

Erdem Onaran*, Seda Yanık

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

3 Atıf (Scopus)

Özet

In textile manufacturing systems, manual labor is considered as necessity due to difficulty of working with a non-rigid material and constantly changing product types. Using robots which have the ability to work with such materials are still quite expensive compared to manual-labor. Since textile processes depend on human capabilities, it is hard to predict processing times, which is essential for production planning. Many textile manufacturers use time study methods for planning, however it only considers the motion related with the sewing process, causing decreased accuracy for predicted cycle times. Yet, in reality, there are many factors affecting the cycle times, such as type of sewing machine, abilities of workers, material (e.g. fabric) type and product design. Including all these factors increase the complexity of the time model, but they can be necessary to increase prediction accuracy. In this study, multilayer perceptron, which is one of the most widely used approaches in machine learning, is used to predict cycle times of a common operation in textile manufacturing, as many studies have shown that machine learning methods are more effective while dealing with many variables and complex relationships compared to statistical methods.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIntelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference
EditörlerCengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga
YayınlayanSpringer Verlag
Sayfalar305-312
Sayfa sayısı8
ISBN (Basılı)9783030237554
DOI'lar
Yayın durumuYayınlandı - 2020
EtkinlikInternational Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey
Süre: 23 Tem 201925 Tem 2019

Yayın serisi

AdıAdvances in Intelligent Systems and Computing
Hacim1029
ISSN (Basılı)2194-5357
ISSN (Elektronik)2194-5365

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???International Conference on Intelligent and Fuzzy Systems, INFUS 2019
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot23/07/1925/07/19

Bibliyografik not

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Parmak izi

Predicting cycle times in textile manufacturing using artificial neural network' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

Alıntı Yap