Abstract
The application of data mining techniques is an extended practice in numerous domains; however, within the context of maritime inspections, the aforementioned methods are rarely applied. Thus, the application of data-mining techniques for the prediction and ranking of non-conformities identified during vessel inspections could be of significant managerial contribution to the safety of shipping companies, as non-conformities could potentially lead to real accidents if not addressed adequately. Hence, specific data mining methods are investigated and applied in this paper to predict and rank non-conformities on oil tankers using a database recorded by tanker shipping companies in Turkey from 2006 to 2019. The results of this study reveal that specific non-conformities, for instance, inadequate ice operations or inadequate general appearance and condition of hull, superstructure and external weather decks, are not company-based problems, rather they are industry wide issues for all tanker shipping companies.
| Original language | English |
|---|---|
| Pages (from-to) | 687-694 |
| Number of pages | 8 |
| Journal | Ships and Offshore Structures |
| Volume | 17 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2022 |
Bibliographical note
Publisher Copyright:© 2020 Informa UK Limited, trading as Taylor & Francis Group.
Keywords
- Maritime safety
- WEKA
- data mining techniques
- maritime inspections
- non-conformities