z-logo
open-access-imgOpen Access
Fuzzy FMEA model for risk evaluation of ship collisions in the Malacca Strait: based on AIS data
Author(s) -
Muhammad Badrus Zaman,
Eiichi Kobayashi,
Nobukazu Wakabayashi,
S Khanfir,
Trika Pitana,
Adi Maimun
Publication year - 2014
Publication title -
journal of simulation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.294
H-Index - 24
eISSN - 1774-7786
pISSN - 1747-7778
DOI - 10.1057/jos.2013.9
Subject(s) - automatic identification system , china , fuzzy logic , identification (biology) , computer science , geography , computer security , artificial intelligence , botany , biology , archaeology
Maritime safety in the Malacca Strait is an important issue. The Strait of Malacca is the longest strait in the world (1120 km) and is classified as a high-risk area for navigation. The 800-km (500-mile) long Malacca Strait, linking Europe and the Middle East to the Asia-Pacific, carries about 40% of world trade. The strait is the main shipping channel between the Indian Ocean and the Pacific Ocean, linking major Asian economies such as those of India, China, Japan, and South Korea. In this paper, hazard identification and risk evaluation are established as steps of a formal safety assessment for ship collisions. The inputs of a fuzzification are obtained from a failure mode and effects analysis, which includes risk factors such as occurrence (O), severity (S), and detection (D). The risk factors O, S, and D are evaluated using the fuzzy method. The actual sea-traffic condition data are collected by means of Automatic Identification System equipment that is installed at Kobe University, Japan, and the Universiti Teknologi Malaysia (UTM) Johor, Malaysia. Those data are applied to establish the methods with the help of the Geographic Information System .

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom