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Article Details

  • Article Code : FIRAT-AKADEMI-14448-5792
  • Article Type : Araştırma Makalesi
  • Publication Number : 1A0500
  • Page Number : 113-128
  • Doi : 10.12739/NWSA.2025.20.4.1A0500
  • Abstract Reading : 138
  • Download : 34
  • Atıf Sayısı : 0
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Issue Details

  • Year : 2025
  • Volume : 20
  • Issue : 4
  • Number of Articles Published : 6
  • Published Date : 1.10.2025

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Dergi Kapağı
Engineering Sciences

Serial Number : 1A
ISSN No. : 1308-7231
Release Interval (in a Year) : 4 Issues

TEKSTİL ENDÜSTRİSİNDE GİZLİ KAPASİTENİN ORTAYA ÇIKARILMASI: GELENEKSEL ZAMAN ETÜDÜ VE KÖK NEDEN ANALİZİ ENTEGRASYONU

Ethem Sefa KUCUKYILMAZ1 , Erhan AKIN 2 , Gizem Öztürk3

Bu çalışmanın amacı, hazır giyim sektöründe darboğaz oluşturabilen otomatik serim makinelerinin operasyonel verimliliğini ölçmek, gizli kapasite kayıplarını belirlemek ve bu kayıpların kök nedenlerini analiz etmektir. Metodolojik olarak, Phakphonhamin (2018) tarafından önerilen "Adam-Makine Şeması" ve "Kayıp Zaman Analizi" yöntemleri temel alınmış, bu geleneksel yöntemler Makine Öğrenmesi (Random Forest ve K-Means) algoritmaları ile desteklenmiştir. Elde edilen bulgular, işletmeler arasında önemli performans farkları olduğunu göstermektedir; benchmark olarak belirlenen işletme %89.4 verimlilik oranına ulaşırken, diğer işletmelerde verimlilik oranlarının %18,6 ile %64,6 arasında değiştiği tespit edilmiştir. Veri analizi sonuçlarına göre, en büyük verimlilik kaybı kalemi, toplam işlem süresinin %51,1'ine kadar ulaşabilen "Rulo Değişim Süreleri"dir. Çalışma kapsamında geliştirilen Random Forest tabanlı simülasyon modeli, rulo değişim süreçlerinde sağlanacak %50'lik bir iyileştirmenin, genel işletme verimliliğinde yaklaşık %6 puanlık (net %31,67'den %37,66'ya) bir artış sağlayacağını öngörmektedir. Sonuç olarak bu çalışma, serim operasyonlarında makine hızından ziyade hazırlık (setup) süreçlerinin verimlilik üzerindeki belirleyici etkisini nicel verilerle kanıtlamaktadır.

Keywords
Otomatik Serim Makinesi, OEE, Verimlilik Analizi, Makine Öğrenmesi, Tekstil Endüstrisi,

REVEALING HIDDEN CAPACITY IN THE TEXTILE INDUSTRY: INTEGRATION OF TRADITIONAL TIME STUDY AND ROOT CAUSE ANALYSIS

Ethem Sefa KUCUKYILMAZ1 , Erhan AKIN 2 , Gizem Öztürk3

The aim of this study is to measure the operational efficiency of automatic spreading machines that may create bottlenecks in the ready-to-wear apparel industry, to identify hidden capacity losses, and to analyze the root causes of these losses. Methodologically, the Man–Machine Chart and Loss Time Analysis methods proposed by Phakphonhamin (2018) were adopted as the foundational approaches, and these traditional techniques were further supported by Machine Learning algorithms, namely Random Forest and K-Means. The findings reveal significant performance differences among the enterprises: while the benchmark company achieved an efficiency rate of 89.4%, efficiency levels in the other companies ranged between 18.6% and 64.6%. According to the data analysis results, the largest source of efficiency loss was identified as Roll Changeover Times, accounting for up to 51.1% of the total operation time. The Random Forest–based simulation model developed within the scope of the study predicts that a 50% improvement in roll changeover processes would result in an approximately 6 percentage-point increase in overall operational efficiency (from a net efficiency of 31.67% to 37.66%). In conclusion, this study quantitatively demonstrates that, in spreading operations, preparation and setup processes have a more decisive impact on efficiency than machine speed itself.

Keywords
Automatic Spreading Machine, OEE, Efficiency Analysis, Machine Learning, Textile Industry,

Details
   

Authors

Ethem Sefa KUCUKYILMAZ (1) (Corresponding Author)
Fırat Üniversitesi
eskucukyilmaz@firat.edu.tr | 0009-0008-6912-1851

Erhan AKIN (2)

Fırat Üniversitesi
eakin@firat.edu.tr | 0000-0001-6476-9255

Gizem Öztürk (3)

SERKON Makina Sanayi A.Ş.
ozturkggizem@gmail.com | 0009-0008-2328-4903

Supporting Institution

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Project Number

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Thanks

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References
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