Prediction of Ship Main Engine Failures by Artificial Neural Networks

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Göksu B., Erginer K. E.

JOURNAL OF ETA MARITIME SCIENCE, cilt.8, sa.2, ss.98-113, 2020 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 2
  • Basım Tarihi: 2020
  • Doi Numarası: 10.5505/jems.2020.90377
  • Dergi Adı: JOURNAL OF ETA MARITIME SCIENCE
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Directory of Open Access Journals, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.98-113
  • Anahtar Kelimeler: Neural Networks, Planned maintenance, Ship engine failures, MAINTENANCE MANAGEMENT-SYSTEM, DESIGN, OPTIMIZATION, RELIABILITY, SELECTION
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Maintenance practices are considered as the means of providing safety and security to environment and quality service, and despite increasing the costs for companies with certain increments, they contribute to their reputation and reliability. Maintenance planning of ships consists of setting priorities and planning the efficient use of the sources. One of the main objectives of this study is to bring up more profits from commercial activities by optimizing the availability of vessels. Operational capacity is ensured by adopting a systematic and proper maintenance policy that increases effectiveness and efficiency by reducing downtime. To reach at such a target, recent failure data is analyzed and through this analysis certain procedures are developed for spare parts availability and these procedures are utilized in maintenance applications.