Analyzing factors influencing the severity of occupational accidents in textile industry using decision tree algorithms

Mutlu N. G., ALTUNTAŞ S.

Cluster Computing, cilt.27, sa.1, ss.787-825, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 27 Sayı: 1
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s10586-022-03958-9
  • Dergi Adı: Cluster Computing
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Sayfa Sayıları: ss.787-825
  • Anahtar Kelimeler: Turkish textile industry, Risk management, Occupational accidents, Decision tree algorithm
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Analysis of factors influencing the severity of occupational accidents in manufacturing systems is of vital importance for sustainable manufacturing in a business environment. The aim of this study is to identify occupational health and safety risks in the Turkish textile manufacturing industry, which includes “manufacturing of textiles,” “manufacturing of wearing apparel,” and “manufacturing of leather and related products”. There is no study in the literature that examines the risks related to occupational health and safety in Turkish textile manufacturing based on occupational accident records from 2013 to 2019. To fill this gap in the literature, data-driven modeling is conducted to analyze 139,092 accident records including enterprise information, accident information, injured person information, and accident outcome information, which are obtained from the Ministry of Family, Labor, and Social Services in Türkiye. The result of this study showed that there are 50 injury accident decision rules based on 15 distinct accident predictors, which will support decisions for the efficient use of limited resources, the development of effective accident prevention policies, and the stability of the sector.