Open AccessOperational failure assessment of Remotely Operated Vehicle (ROV) in harsh offshore environments
Author(s) -
Samson Nitonye,
Sidum Adumene,
Cyril U. Orji,
Anietie Effiong Udo
Publication year - 2021
Publication title -
pomorstvo
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.197
H-Index - 8
eISSN - 1846-8438
pISSN - 1332-0718
DOI - 10.31217/p.35.2.10
Subject(s) - remotely operated underwater vehicle , fault tree analysis , subsea , mean time between failures , failure mode and effects analysis , reliability engineering , engineering , reliability (semiconductor) , probabilistic logic , remotely operated vehicle , computer science , marine engineering , failure rate , automotive engineering , robot , artificial intelligence , mobile robot , power (physics) , physics , quantum mechanics
For an effective integrity assessment of marine robotic in offshore environments, the elements’ failure characteristics need to be understood. A structured probabilistic methodology is proposed for the operational failure assessment (OFA) characteristics of ROV. The first step is to assess the likely failure mode of the ROV system and its support systems. This captures the interaction and failure induced events during operation. The identified potential failure modes are further developed into logical connectivity based on the cause-effect relationship. The logical framework is modeled using the fault tree analysis technique to predict the ROV operational failure probability in an uncertain harsh environment. The fault tree analysis captured the logical relationship between the primary, intermediate, and top events probability. The importance measure criteria were adopted to identify the most probable events, links, and their importance on the failure propagation. The model was demonstrated with an ROV for deep arctic water subsea operations. The result identified the control system, communication linkages, human factor, among others, as most critical in the ROV operational failure. The methodology’s application provides core information on the Mean time between failure (MTBF) of the ROV system that could aid integrity management and provides a guide on early remedial action against total failure.