340
2005 total of 20 and the 2001-2005 average of 25.
On the other hand, analysis and discussions on the
statistical reports have been performed within
various studies (Esbensen et all 1985; Wagenaar &
Groeneweg 1987; UK P&I, 1997; Rothblum, 2000,
O'Neil, 2003, Darbra & Casal 2004) in literature.
Existing analyses on statistical data are clearly
indicates that human error is still continue to be the
most critical factor in maritime accidents. In
addition, the investigations on reducing the human
error in maritime accidents have been continued
eagerly both in industrial base and academic field.
Parallel to the distribution of the main causes of
maritime accidents, it can be recognized as an
effective approach to investigate the root-causes of
the human error in maritime accidents.
The urgent needs on solving of human-related
errors in ship operations are outlined to increase the
motivation on this research. The remains of the
paper are organized as follows: Section 2 reviews
the taxonomies on the root causes of maritime
casualties; in addition, human error evaluation
models are introduced. The Human Factors Analysis
and Classification System (HFACS) are determined
to structure an evaluation model and the evaluation
stages are originally interlinked with the illustrative
examples on human errors and maritime casualties
in Section 3. Additional unit are integrated into the
existing evaluation model based on HFACS to be
able to investigate the influences of design and
installation of system on human error. This paper is
concluded with discussing of the originality and
expected contributions of the integrated model on
examining human errors and expressing the
significance and methodology of managing of group
consensus between investigators as further research.
2 TAXONOMIES ON HUMAN ERROR
IN MARITIME ACCIDENTS
Human error has been cited as a cause or
contributing factor in maritime accidents in many of
the studies in literature (Hetherington et al. 2006).
For identifying the potential role of the human error
in casualties, the syntheses on the statistical data and
the relevant casualty reports, have been performed in
existing studies, are reviewed. As a result of their
analysis, Esbensen et al. (1985) argue that the actual
figure of incidents involving human error may be as
high as 80%. Wagenaar and Groeneweg (1987)
analyzed 100 accidents heard by the Dutch Shipping
Council between 1982 and 1985, and determined
to only 4 of them occurred with no human error
causes. Examining the data of Major Hazard
Incident Data Service (MHIDAS), human factors
were cited in 16% of all in port accidents by Darbra
& Casal (2004). Based on Baker & McCafferty
(2005), human error was primarily responsible
for approximately 46% of maritime accidents.
Engineering failures, weather related failures, and
material failures, with the percentage of 41%, 11%,
and 2% in a correspondence manner, are recognized
as other top level failures by considering United
States Coast Guard (USCG) database over the period
1991 to 2001. The outcomes of the various
evaluations on the maritime accident reports are
reviewed in this section. As a general tendency of
the researchers, human error continues to be a
dominant factor in approximately 80 to 85% of
maritime accidents.
Much more effort on investigating the causes of
human error is required to clearly identify the
preventive actions and urgent precautions. For
investigating the root causes of shipboard accidents,
the complexity of the issue increases due to the
complicated systems, components, and various user
interfaces. The operational requirements of technical
system and social environment of crewmembers
onboard ships should be considered as significant
points of the human error analysis. The scope and
complexity of the problem is addressed utilizing of
systematic evaluation methodology to manage the
effective analysis and applicable outcomes on
reducing human error in maritime accidents. As
understanding the main causes of the human errors
in accidents, a number of human error models and
frameworks have been developed and cited by
various authors (Edwards 1972; Rasmussen 1982;
Wickens & Flach’s 1988; Reason 1990; Moray
2000; O’Hare 2000; Wiegmann & Shapell 2001a).
Table 1 illustrates the results of bibliographic survey
on human error analysis model.
Table 1. Human error evaluation models
Model Author(s)
SHEL model Edwards, (1972)
Skills rules- knowledge
model
Rasmussen (1982)
Four-stage information
processing model
Wickens & Flach (1988)
Generic Error Modeling
System (GEMS)
Reason (1990)
Socio-technical model Moray (2000)
Wheel of Misfortune O’Hare (2000)
HFACS Wiegmann & Shapell (2001)
After introducing the existing model, it is
determined to refer in this paper to The Human
Factors Analysis and Classification System
(HFACS), based on Reason’s (1990a, b) model of
latent and active failures, for designing an evaluation
system on maritime accidents and related causes.