SAFETY PERFORMANCE INDICATORS (SPIs) FOR NIGERIAN
MARITIME SAFETY MANAGEMENT.
ABSTRACT
In this research, the researcher focuses on Safety Performance
Indicators (SPI) which would influence the usefulness in safety
management in Nigerian Maritime as a tool for safety measurement and
development. Since it is difficult to directly measure the success of actions
taken to improve safety and thereby develop alternative means to measure
performance. By this means, the regulatory bodies of maritime in Nigeria
(such as NPA, NSC and the NIMASA) can help identify what actions
have been (or are likely to be) successful in improving safety management.
Over the years, it has been observed that the Nigerian maritime domain
needs a set of indicators that can measure the actual and future level of
safety management. The actual values of the indicators are not intended
to be direct measures of safety, although safety performance can be
inferred from the results achieved. In this research the aim is to find
Safety Performance Indicators, existing or newly developed, that can
be used successfully as tools in Nigerian maritime safety management.
Although, lacks some analyses of data (such as the annual number of
accidents per some time in Nigerian maritime), which are paramount in
such research, due to the limited time of the research work.
Keywords
Maritime domain, Safety, Safety management, Safety Performance
Indicators.
Buhari, C. M. B. Tech (Maritime Technology Page 6
TABLE OF CONTENTS
Title page ……………………………………………………………..…………i
Dedication page …………………………….……………………………………ii
Acknowledgment page ………………………………………………………….iii
Abstract …………………………………………………………..……………v
Table of Contents …………………………………………………………..…vi
List of Tables ……………………………………………………….…………viii
List of Figures …………………………………………………………………ix
Definitions…………………………………………………………………………………………x
Acronyms……………………………………………………………………………………….xii
CHAPTER ONE
1 INTRODUCTION……………………………………………………………………. 1
<
CHAPTER TWO
2 REVIEW OF RESEARCH……………………………………………………… 4
CHAPTER THREE
3.0 METHODOLOGICAL FUNDAMENTALS OF BASIC SAFETY THEORY. 9
3.1 Review of the Development of Accident Models ………………………………. 11
3.1.1 Domino Models…………………………………………………………………………………. 12
.
3.1.2 Fault Tree Model ……………………………………………………………. 13
3.1.3 Event Tree Model ………………………………………………14
3.1.4 Bowie Model ……………………………………………………15
3.1.5 Energy Model ……………………………………………………15
Buhari, C. M. B. Tech (Maritime Technology Page 7
3.1.6 Review of other Modern Accident Model ………………………17
3.2 Risk Model ……………………………………………………………20
3.3 Formal Safety Assessment ……………………………………………24
CHAPTER FOUR
4 SAFETY PERFORMANCE INDICATORS ……………………………………. 30
4.1 General information……………………………………………………….. 30
4.2 SPIs in Safety Programmes ………………………………..… 35
4.3 Leading and Lagging Indicators………………………………………. 36
4.4 Maritime Safety Performance Indicators………………………………………………..42
4.5 Port State Control ……………………………………………. 43
4.5.1 Inspections and Deficiencies of vessels …………………… 43
CHAPTER FIVE
5 SUMMARY, CONCLUSIONS AND RECOMMENDATION….50
5.1 Summary.…………………………………………………………50
5.2 Conclusion and Recommendation ……………………………….53
BIBLIOGRAPHY……………………………………………………………………………55
APPENDIX
Letter for Application for collection of Statistical Data ……………………58
Buhari, C. M. B. Tech (Maritime Technology Page 8
LIST OF TABLES
Table 1: Description of main Deficiency code ………..…………….. 47
Table 2: Basic Statistics of the Paris MOU on Port State Control …….. 47
Buhari, C. M. B. Tech (Maritime Technology Page 9
LIST OF FIGURES
Figure 1: Essential Elements of a Safety Management System ………………………. 2
Figure 2: The Players and Stakeholders of the Maritime Safety ………………………. 6
Figure 3: Illustration of the Early Domino Theory ………..………………………….. 13
Figure 4: Illustration of the Refined Domino Theory …..……………………………. 13
Figure 5a: Fault Tree Model (FTM) ………………………………………………… 14
Figure 5b: Event Tree Model (ETM) ………………………………………………….14
Figure 6: The Bowtie Model ………………………………………………………….15
Figure 7: Energy Model ………………………………………………………………16
Figure 8: “Swiss-Cheese” Accident-Causation Model ……………………………. ..18
Figure 9: Mark 3 version of Reason’s Accident Causation Model ……………………19
Figure 10: Risk Contribution Tree …………………………………………………… 20
Figure 11: The Structure of the Formal Safety Assessment process ………………… 27
Figure 12: The Safety Stakeholders Triangle …………………………………….…. 35
Figure 13: Identifying Safety Performance Indicators ……………………………… 35
Figure 14: Leading and Lagging Safety Performance Indicators …………………… 40
Buhari, C. M. B. Tech (Maritime Technology Page 10
DEFINITIONS
ACCIDENT: An unplanned sequence of events leading to a certain
consequence in terms of damage to humans, environment, and
even reputation or assets, in the case of a company.
ACTIVITIES INDICATORS: Are measures of actions taken for prevention,
preparedness, and response programmes, which should lead to
improvements in safety (as measured by the outcome indicators).
BARRIER: Barrier is something that can prevent harm from being caused.
HAZARD: A condition or physical situation with a potential for an
undesirable consequence, such as harm to life, environment or
assets.
INCIDENT: An unplanned sequence of events with potentially important
safety-related effects, which, in the end, are prevented from
developing into actual adverse consequences or harm.
OUTCOME INDICATORS: Are measures of the extent of improvement in
performance or, in other words, reduction in the risks to human
health or the environment from accidents.
RELIABILITY: The probability that an item will perform a required function
without failure under stated conditions for a stated period of
time.
RISK: Risk is defined as a measure of the probability of a
hazards- related incident occurring, and the severity of
harm or damage that could result.
SAFETY: Safety is the state in which the risk of harm to persons or
property damage is reduced to, and maintained at, or below, an
ALARP level through a continuing process of hazard
identification and risk management.
SAFETY
PERFORMANCE: Measured outcome of safety efforts, that indicate
frequency and severity of incidents in time or in other scale.
SHIP: Any seagoing or non-seagoing water craft, including those
used on inland waters, used for the transport of hazardous
Buhari, C. M. B. Tech (Maritime Technology Page 11
(such as toxic waste) substances.
STAKERHOLDER: Any individual, group or organisation that is involved, interested
in, or potentially affected by maritime (in this context of research)
accident prevention, preparedness and response.
PERFORMANCE
INDICATOR: To indicate safety performance in prevention, preparedness
and/or response, or to understand the process that leads to
accidents.
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ACRONYMS
AIS: Automatic Identification System
ALARP: As Low As Reasonably Practicable
BA: Barrier Analysis
COLREG: Convention on the International Regulations for Preventing
Collisions at Sea
EEC: Euro-control Experimental Centre
ETA: Event Tree Analysis
FSA: Formal Safety Assessment
FSC: Flag State Control
FTM: Fault Tree Model
FTA: Fault Tree Analysis
GBS: Goal Based Standards
HOFs: Human and Organisational Factors
IMO: International Maritime Organisation
ISM: International Safety Management
MTS: Maritime Transport System
NWPERS: North West European Project on Ro-Ro Safety
NPA: Nigerian Ports Authority
NSC: Nigerian Shippers’ Councils
NIMASA: Nigerian Maritime Administrative and Safety Agency.
PMOU: Paris Memorandum of Understanding
PSC: Port State Control
SMS: Safety Management System
SOLAS: Convention for the Safety of Life at Sea
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SPIs: Safety Performance Indicators
STCW: Convention on Standards of Training, Certification and
Watchkeeping for Seafarers
VTS: Vessel Traffic Service
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CHAPTER ONE
1. INTRODUCTION
The phrase, ‘‘Safety has often been considered as a critical feature in
almost all maritime operations and its environs’’ has remained a truism.
The researcher believes is true due to the technicality involved in its
operation. For the maritime environs have become ultra-sensitive faced
with the growing need for the protection of cargoes (goods) and persons
(crews or personages in the case of a cruise vessel) against multiple
threats or hazards coming from the sea. The growth and diversification of
maritime activities has lead to an increase and an evolution of threats; this
new situation requires the consideration of individual threats (from,
navigation, accidents, terrorism, immigration, illicit traffic and pollution)
and environmental threats (from, human error, natural resources and
disasters (God’s Act). The hostile environment set many challenges not
only to the ship itself, as a technical artefact, and the people onboard, but
also to the higher levels of safety management. The management of an
organization should be arranged to be able to keep sufficient control of the
safety and make plans to overcome the hazards, that is be prepared for all
foreseeable situations that can be encountered and that may possibly
cause harm to the organization, its employee’s, environments (work
place), to its customers and other stakeholders. The risk should be below
the limits set by the regulators (NPA {Such as Port State Control},
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NIMASA, and NSC) and concurrently as low as reasonably practicably
(ALARP), taking into account the relevant stakeholders.
In order to manage safety in a proper way the top management needs
salient information to support the process of decision-making. Sufficient
information is needed to identify the hazard (if any) in time and planning
the actions required and giving orders and allocating premises for the
enforcement of them. The essential elements of a safety management
system are (see figure 1). These includes: safety measures or programmes,
safety performance indicators, measures of final outcomes, and measures
of the social costs of accidents and injuries. In this research, it is assumed
that maritime transport has instituted a safety management system that
enables a sensible choice of safety performance indicators to be made.
Social cost
Final outcomes (killed, injured)
Safety Performance Indicator (Immediate outcome)
Safety measures and
Safety programmes
Figure 1: Essential elements of a safety management system
It is not unusual for ‘final outcomes’ and ‘social cost’ to be considered together within a safety
management programme as, say, accident cost rate or accident cost density.
An efficient safety management system gives sufficient support for the
operators to be aware of the state and variations of safety margins. If
necessary, the safety management system should be able to react to
Buhari, C. M. B. Tech (Maritime Technology Page 16
warning signals to change an adverse development of safety towards
the desired direction in a confused variety of different constant and
dynamic parameters and more or less easily identifiable trends. In its
entirety, safety is a complex concept. The many features of safety, e.g.
dynamics, latent errors, human and organizational errors etc., claim for a
vigilant, skilful and agile safety management system. To keep all risks in
good control is a challenging task for the safety management.
The couch “You can’t manage it, if you can’t measure it” is a widely cited
slogan (in its different versions). It can be applied also to safety
management. Managers may sometimes need to base their decisions on
sixth sense, which helps them to make the required decisions quickly. Time
can be critical, so if there aren’t any better groundings even this basis
seems to be acceptable. However, it can also be claimed that pure sixth
sense is not necessarily the best basis for decision-making, if reliable
indicators for decision support are available. For good indicators give
information of the safety level and of the trends having influence on it or
can be developed. “Measurement is an absolute prerequisite for control,
whether this be the control of production quality, accidents, or any other
component of an industrial system” claims (Rouhiainen, 1990), who
refers in this statement to (Johnson, 1980) and (Tarrants, 1963). Safety
management will probably reach its goals more easily, if good safety
performance indicators (SPIs) are available and properly used for control
Buhari, C. M. B. Tech (Maritime Technology Page 17
and guidance. Therefore, it seems beneficial to develop such indicators in
good time.
One goal of this research as earlier affirmed is to start discussion about the
applicability of various safety performance indicators for maritime
transportation and the possibilities to develop them further in this respect.
Buhari, C. M. B. Tech (Maritime Technology Page 18
CHAPTER TWO
2. REVIEW OF RESEARCH
The maritime is a very challenging environment exposing considerable
physical risk/hazards on ships, their cargoes and people onboard. All
hazards related to the maritime environment are not always easy to keep in
mind or to be detected on a calm and sunny day. Knowledgeable and well
learned sailors are aware of that the conditions can be quite different e.g.
during a winter storm, in a dense fog, in the vicinity of unmarked
underwater rocks or in compressive ice, which are referred to as the “Acts
of God” in Marine Insurance Act 1906. These hazards, and a vast number
of other hazards, related to the development and operation of the sociotechnical system. For this single reason, certain assessment must be
taken into consideration in the shipping operations. Risks related to
collision, contact and grounding, fire and explosion, capsize and sinking
as well as the damage in the categories of cargo, hull and engine are not
unknown to the people involved.
All the countermeasures to avoid the risk seem to have created a positive
trend in the accident statistics during the last decenniums. The descending
trend in accident statistics has been a general phenomenon in the context of
various industries as identified by (Duffey et Saull, 2003).
Safety is a perception which may easily get in danger of extinction. Safety
cannot genuinely be improved only by looking to the past and taking
Buhari, C. M. B. Tech (Maritime Technology Page 19
precautions against the accidents that have happened (Hollnagel, 2008).
Thus, vigilance and continuous efforts, preferably proactive and
sometimes also reactive actions of the safety management are required in
order to keep the situation under control.
Globally, maritime safety is governed by the combination of International
Rules and Regulations, National Regulations of the Flag States and Port
States, Port Regulations, Rules of the Classification Societies and
Insurance Companies. International Conventions like, MARPOL’73/78,
STCW ‘95, and SOLAS ‘74/80 have a very important role in this
framework. This regulatory system, which is supported by the Safety
Management Systems of the shipping companies, is very complicated due
to the many players (and stakeholders) involved, see Figure 2. The line
between the actual ship owner, operator or technical manager of the vessel
is not completely clear in shipping and therefore complicates enforcement
of the legal instruments (Knapp, 2006).
Figure 2: The players and stakeholders of the maritime safety.
Buhari, C. M. B. Tech (Maritime Technology Page 20
Bigger improvements or any modifications to the maritime regulatory
system, most often to the specific rules, are most easily carried out after a
major accident. Due to this reason some critic claims that the system is
“disaster-driven”.
However, if there would not be any changes in the regulatory system after
a major accident, the whole system would be too stable. The accident
investigation usually reveals a number of problems in the system so it is
natural to react on them. However, a proactive way to proceed would be
more fruitful. Fortunately, some development of the regulatory system is
going on all the time and there is an emergent trend to apply risk
assessments in the safety management. The process of making
improvements in international or even national legislation is slow, but it
should be remembered that the safety standards are usually just minimum
standards. The shipping companies may set their own higher standards,
too.
The Port State Control is a rather new regulatory system that has been
established to handle this problem. Inspectors in one Port State inspect
a certain portion of the ships visiting the port(s) of that state, as well as
the certificates, the crew onboard, the safety management system, i.e.
the conformity to all necessary rules and regulations. If the deficiencies
onboard are too gross, the ship may be detained. This system creates lots
of useful information related to ship safety, including statistics, see e.g.
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(PMOU, 2007). The effects of the Port State Control inspections have been
recently discussed e.g. by (Knapp et Frances 2007 and 2008) and (Cariou
et al. 2008).
In addition to the inspections of the Port State Control -system, there has
been some market for vetting inspections which are performed by private
vetting organizations. The vetting inspections create a strong commercial
incentive for the ship owner to comply with the vetting inspection
requirements since the outcome of these inspections will determine if the
ship gets cargo or not (Knapp et Frances, 2007).
The organizations within the maritime transportation sector need to attain a
certain minimum level of safety in their operations. In minimum this level
is set by the rules of the regulators such as MARPOL73/78, which
provides minimum standard for pollution of sea from vessels. However,
some pioneering shipping companies have clearly acted for and
manifested in their goals and policy to e.g. give a higher priority to the
environmental issues with an attempt to exceed the general minimum
standards.
Buhari, C. M. B. Tech (Maritime Technology Page 22
CHAPTER THREE
3.0 METHODOLOGICAL FUNDAMENTALS OF SAFETY THEORY.
The researcher describes safety as a state in which the risks (hazards,
sometimes unchangeably by other authors or researchers) are at an
acceptable level or as low as reasonably practicably (ALARP). Risk is a
word that can have many meanings. For the purpose of this research, the
researcher adopted definition from (Manuele, 1997): Risk is defined as a
measure of the probability of a hazards- related incident occurring, and the
severity of harm or damage that could result. This harm can be directed to
persons (crew/passengers/others), environment (nature) and/or property
(ships/port facilities/other). In some cases the harm may even affect the
reputation of the establishment. According to (Hollnagel, 2008) in practice
it is impossible to completely prevent unwanted events completely, so the
two approaches (risk and safety) are best used together. There are several
difficulties to observe safety, due to the fact that safety is not an easily
observed by a directly measurable state. Therefore, indirect measurements,
risk assessments, are required for this purpose. Risk fundamentally
involves uncertainty (Manuele, 1997). Thus, it seems to be inevitable that
some uncertainty is always involved with safety.
Risto and Kim (2009) gave a simplified Concept of Safety as:
Failures will occur, in spite of the most accomplished
prevention efforts.
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No human endeavour or human-made system can be free from
risk and error.
Controlled risk and error is acceptable in an inherently safe
system.
The elimination of accidents (and serious incidents) is
unachievable.
Failures will occur, in spite of the most accomplished
prevention.
Risk and safety analysis/assessments are widely used in i n d u s t r i e s
t h a t a r e hazardous in nature. The main targets are usually in preventing
(and/or mitigating) unwanted events, such as occupational/ or work-place
accidents, major accidents, disasters and loss of reputation. These
industries (and services) could comprise of the various modes of transport,
chemical industry, manufacturing company, etc. A typical feature of all
these (and some other) industries is that they have an inherent potential to
cause large losses, when an accident occurs.
In order to have the risks under control, at least ALARP all hazards should
be identified, the risks involved should be assessed and effective risk
control options against most remarkable risks developed are also taken
into operation. In the Formal Safety Analysis-process, which has been
applied already in several areas of the maritime industry, cost-benefit
Buhari, C. M. B. Tech (Maritime Technology Page 24
analysis has also been included in the phases to ascertain the feasibility of
the selected risk control measures. Reliable risk models enabling
(quantitative) risk assessments are in the core of this process. However,
a premise for the development of such models is that the mechanisms
leading to accidents are known.
3.1 REVIEW OF THE DEVELOPMENT OF ACCIDENT MODELS
Accident model, like any model, is always a simplified representation of
reality. It draws attention to the most essential characteristics of the
phenomenon and reveals its most relevant functions.
There is a wide range of different accident models, but a universallyapplicable, uniform theory is still lacking (Harms-Ringdahl, 1993),
(Manuele, 1997). Several models have been developed serving different
purposes in different frameworks. The extremes of the thinking in the
various accident causation models in the papers titled ‘On the Practice of
Safety’ by (Manuele, 1997) in the following statements:
A. “90 percent of accidents are caused by unsafe acts, and the proper
solution for them is to modify employee behaviour and
B. Causal factor for 90 percent of accidents are systemic and the
proper solution for them is to modify the work system”
The earliest accident “theory” may be represented by the belief that fate,
mere chance, or the act of some supernatural force or spirit, is the major
Buhari, C. M. B. Tech (Maritime Technology Page 25
causal explanatory factor for accidents. There seems to be nothing to do by
the safety management, if these fatalistic theories would be valid. The
“Accident-proneness” of the victim was another commonly accepted
theory during the early years of the past century.
Three different types of accident models can be distinguished today: a) the
sequential accident models, b) epidemiological accident models and c)
systemic accident models.
3.1.1 DOMINO THEORY
Domino theory is one of the earliest accident models of modern times
presented by Heinrich already in the 1930’s (Heinrich, 1950). According to
the domino theory, the events leading up to accidents are like a row of
dominoes. Once one domino has been knocked over, the next event quickly
follows.
Its core is the chain of multiple events, the Domino-effect which is
characterized by the sequence of events following each other. This chain of
multiple events ends up to the accident and finally its consequences, e.g. an
injury, see figure 3. The early ‘Domino theory’ has been criticized because
it does not account for multiple causalities (Kjellen, 2000).
Buhari, C. M. B. Tech (Maritime Technology Page 26
Figure 3: Illustration of the Early Domino Theory.
The above i.e. earlier Domino theory is of very little value in accident
model terms as it always focuses on the fault of the person. A person may
be at fault, but usually there are other causes involved as well. This
criticism led to a more refined Domino model as shown below in Figure 4,
which is of more value and focuses on more emphasis on management
failure.
Figure 4: Illustration of the Refined Domino Theory.
3.1.2 FAULT TREE MODELS
FTM were started to be developed in the 1960s. Descriptions of the method
are presented e.g. in (Vesely et al, 1981) and (Kumamoto & Henley, 1996).
Buhari, C. M. B. Tech (Maritime Technology Page 27
The fault tree model, see Figure 5a), can be often utilized even for a
quantitative risk analysis of the accident probability a complicated technical
system if the probabilities of the “failure events” are known. This method,
based on the use of AND- and OR- gates (Vesely et al, 1981), is well
known and widely applied, but it has been criticized for being difficult to
use, see e.g. (Harms-Ringdahl, 1993). It may not be a suitable model for the
analysis of man-machine interaction or for the analysis of the organization
(Harms-Ringdahl, 1993).
a) b)
Figure 5a) Fault tree model and b) Event tree
model
3.1.3 EVENT TREE MODELS
A fault tree can often be supplemented by an event tree, which can be
described as being the opposite of a fault tree. An introduction to event
trees was given by (Suokas et Rouhiainen, 1993). An event tree, see
Figure 5b), starts from the initiating event and then describes all the
possible outcomes of this. It offers possibilities for carrying out
probabilistic estimates of the consequences (Harms – Ringdahl, 1990).
Buhari, C. M. B. Tech (Maritime Technology Page 28
3.1.4 BOWTIE MODELS
Bowtie model can be built of the combination of a fault tree model and
an event tree (or consequence) model, thus it integrates the elements and
options affecting on the probability/ frequency of an accident with its
outcome. A bowtie model, see Figure 6, demonstrates clearly how a
critical event may have several precursors as well as several
consequences (Delvosalle et al, 2005). Thus, it accounts for multiple
causalities, which can be considered as important feature.
Figure 6: The bowtie model (adopted from [Hollnagel, 2008]).
3.1.5 ENERGY MODEL
Energy model can be classified as being an epidemiological accident
model. It is rooted in epidemiology, representing an effort by the
medical discipline to systematize the analysis of accident causes in a way
that is similar to the way the causes of diseases are analyzed (Kjellen,
2000). The core of energy model lies in the fact that the consequences of
an accident are always based on the transfer of energy (in one or another
form: mechanical, chemical, thermal, electrical, etc.), which is affected by a
Buhari, C. M. B. Tech (Maritime Technology Page 29
barrier. The pioneering work with energy model was based on (Gibson,
1961) and this model was developed by (Haddon, 1980).
Figure 7: Energy model
The widely used concept of a barrier, which protects the target (or victim,
usually human life or limb) from the hazardous effects of energy, see
figure 8, is another key concept in the energy model, and has had an
important effect on many other accident models too. Different types of
strategies that can be applied in the framework of energy models are
(Haddon, 1980): prevention from build-up of the energy, modifying
the qualities, limiting the amount, preventing the release, modifying the
rate and spatial distribution, separating in time and space, separating by
barriers, making the victim more resistant, using counter measures and
rehabilitation.
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3.1.6 REVIEW OF OTHER MODERN ACCIDENT MODELS
Understanding of the causal factors of an accident with the linkage to
human error was greatly improved with the structural division of the
human performance on: the skill-based level, the rule-based level and the
knowledge-based level (Rasmussen et Jensen, 1974), (Rasmussen, 1980).
Still, modern models also often include the violations, too. A violation
can be categorized as a further type of human error, provided that the
intention was not to damage the system. The socio-technical approaches
developed during the last 20 years do take into account the background
of human and organizational errors. Reason (1990), in his research work
on Human Error gave the “Swiss-cheese” model and adopted in various
forms as in Figure 8, has become a classical representation of
deficiencies in the safety barriers.
According to the present trend in relevant legislation and regulation the
general aim seems to get away from prescriptive rules to performancecentered objectives (Rasmussen, 1997). This kind of development is in
favour of the use of more process- oriented accident models.
Figure 8 “Swiss-cheese”-accident-causation model.
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In a two year old study (EEC, 2006) the background and philosophy of the
“Swiss- cheese” –model were discussed in order to describe the suitability
and limitations of the model with a reply to some of its critics. The model
has been further developed from its origin (Reason, 1990) and the current
Mark 3 version of it, see Figure 9, has a changed the appearance of the
model significantly. Most of the accident models presented in this chapter,
including the two portrayed in Figure 8 and Figure 9, are good examples
of generic and descriptive models. According to (Reason, 1997) the defects
in the safety barriers, the holes in the “Swiss cheese” are not static. Thus,
they can expand or shrink, move, come and go, depending on the local
conditions, as a response to operator actions and local demands.
Figure 9 Mark 3 version of the Reason’s accident causation model.
3.2 Risk models
Risks can be modelled using accident models as a basis, but a sufficient
risk model is usually much more comprehensive than a pure accident
model. The risk models can be descriptive, qualitative or quantitative
models. Descriptive risk models can in some cases be used to facilitate
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better understanding of the risk mechanisms and the information needed
for more sophisticated qualitative and quantitative risk models. It is
important that the risk model includes at least the most important
parameters and contributing factors.
Figure 10 R i s k Contribution Tree, including all types of marine accidents with type specific fault tree and
event tree, adopted from (Kristiansen, 2001).
A risk contribution tree can be formed by collecting all relevant risk models
together, see figure 10. This kind of tree can be developed either as a
qualitative model or as a quantitative model. The latter option is possible
if the fault trees and event trees can be equipped with quantitative data
related to the risk contributors. Then, the risk contribution tree may be used
e.g. for focusing the risk control options to areas, where their impact is
greatest and do it in a cost-effective way.
The possibilities to improve the outcome i.e. decrease the probability and
or the consequences depend on the stakeholder. A crew member, ship
designer, owner of the ship and the administrator do not have similar
alternatives available for risk reduction. However, by the use of proper risk
models it will be easier to select the best alternative(s) in each case.
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Quantitative modelling of the risks requires reliable risk models, preferably
based on physical, first-principle modelling, thus producing good
numerical estimates for the probability of the accident and also for the
consequences. However, if it takes too much effort and a too long time to
develop a physical model, expert judgments and statistical data are often
used, as shown e.g. by (Rosqvist et al. 1998) and (Vanem et al. 2008).
When quantitative input data for a quantitative risk model is available (or
can be obtained) then it is also possible to get quantitative output data, i.e.
a numerical assessment of the risk, as a result. The sensitivity of the risk
model should be assessed too, and the model should be validated in order
to confirm that it is a reliable tool.
Various physical risk models with their background in the modeling of the
physical accident process, requiring understanding of the applied methods
in engineering sciences, applications of e.g. Finite Element Method (FEM)
and Monte Carlo simulations, have been presented during the last five
ten years, see e.g. (Jalonen, 2003) and (Jalonen, 2007).
The results of a risk assessment are often presented in a form of a risk
matrix, where both measures (the probability and the consequences) of the
risk are easily perceivable.
The consequences, the various types of consequences and the various
classes of their severity, are very important when safety (or the risk) is
Buhari, C. M. B. Tech (Maritime Technology Page 36
considered. They have also been often taken into account in some safety
indicators by utilizing some relevant measure of the consequence. The
number of victims, injured persons or lives lost, as well as the number of
days out of work (e.g. more than three days) are just some examples.
Environmental damage is more difficult to assess, but of course the number
of victims is naturally one valid option. The number of endangered
species and the area of contaminated soil or even the length of polluted
shoreline can be used when assessing the environmental damage. In some
cases non-reversible changes to the ecosystem may take place. Fortunately
the populations of various species may often able to recover after some
time, but the whole ecosystem may change, if some important part of it
does not recover. The spoiled opportunities for e.g. fishing or other
coastal activities may be assessed in monetary units.
Money is in many cases a well-known measure and the total amount of
costs involved are often used when capital or property losses due to
accidents are assessed. The material damage may vary from a total loss
(or even more) to zero. Explosion in a ship has caused, not only the loss
of the ship itself, but significant devastation in the surroundings e.g. in the
accident starting from a fire onboard of a ship loaded with dangerous cargo
in Texas City in 1947 (Perrow, 1984).
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Buhari, C. M. B. Tech (Maritime Technology Page 38
3.3 Formal Safety Assessment
Risk models are in an important role in the process of Formal Safety
Assessment (FSA). In order to replace the less rational methodologies in
the traditional approach of disaster-driven rule-making, a new, more
systematic methodology in rule-making process was introduced to the
maritime regulators in IMO by the United Kingdom in 1993
(MSC62/24/3193).
FSA was developed by the UK Marine Safety Agency (MSA) as a
response to Lord Carver’s report (HoL, 1992). This report recommended
applying a scientific approach safety regulation, based on quantified
assessment of risk, on analysis of costs and benefits and on international
agreement as to what level of risk is acceptable. In essence, the report
recommended a performance based approach to safety aspects in ship
design and technology. It also presented a vision of a long term move to a
so- called “safety case”, which is a widely applied approach to safety in
other industries, such as in the chemical, nuclear and offshore industries.
The apparent problems of creating an internationally governed, but still
uniform concept of a “safety case” lead MSA to develop the idea further
and to apply the same analytical processes to rule-making.
Formal Safety Assessment is a risk-based, systematic and sturdy approach
to safety management. It is a rather new methodology for rule-
Buhari, C. M. B. Tech (Maritime Technology Page 39
making, which applies a scientific approach of thinking. If correctly
applied, FSA applications are transparent, traceable and repeatable.
Recommendations for rule-making prepared by independent FSA-teams on
some area of interest should therefore not be contradictory. FSA acts in a
pro-active way: it should put emphasis not only on risks which have lead to
accidents, but also on risks which may have severe consequences.
An ideal FSA has been characterized with the following attributes
(Skjong, 1998):
* Well structured, systematic, comprehensive
* Objective, rational
* Auditable, repeatable, well documented
* Defensible, reliable, robust
FSA consists of the following five steps (see Figure 11):
1. Identification of hazards
2. Assessment of risks
3. Generation of risk control options
4. Cost benefit assessment of the risk control options
5. Decision making recommendations concerning the options available
All relevant grounds and arguments, models and data
applied by the FSA-team leading to recommendations for
decision making in regulatory work should be documented in a
systematic-way.
Buhari, C. M. B. Tech (Maritime Technology Page 40
Thus they can be discussed and, if necessary, revised later, if essential
changes in the shipping or its environment take place. The application of
FSA should lead to cost-efficiency in rule-making, which probably
leads to a better balance in the development of safety even if the funds
available for this purpose are limited.
Figure 11: The structure of the Formal Safety Assessment -process
Passenger Ro-Ro ships have been under scrutiny in a FSA-study carried
out in a North West European project on Ro-Ro-Safety (NWPERS,
1996) and quite recently in a FSA for ROPAX-ships, which was
submitted by Denmark (IMO, 2008a). In the end of nineties, two trial
applications of FSA were performed concerning High-Speed Craft. The
first one was submitted by MSA (UK) (IMO, 1997) and the other by
Sweden (JNP/HSCO, 1998). The former concentrated on catamarans,
whereas the latter, which was the result of the work of the Joint Nordic
Project (JNP/HSCO, 1998) had a wider scope, including monohulls.
Buhari, C. M. B. Tech (Maritime Technology Page 41
The very specific topic of Helicopter Landing Area (HLA) on Passenger
Ships was the target of two other FSA-studies (DNV, 1997) and
(ICGHLA, 1998). Bulk carriers have also been studied in many FSAstudies; see e.g. (Lee et al. 2001). A Formal Safety Assessment for
containerships was presented by (Wang et Foinikis, 2001). Generic
AFRAMAX-class oil tankers have been under examination in a FSAstudy carried out in the EU-project SAFEDOR (MO, 2008b) and e.g. in the
risk assessments presented by (Cross et Ballesio, 2003).
The guidelines regarding the FSA-procedure were updated in 2002, when
IMO published “Guidelines for Formal Safety Assessment (FSA) for use in
the IMO rule- making process” in MSC /Circ.1023-MEPC/ Circ.392
(IMO,2002).
Based on all the other realized Formal Safety Assessments it can be
claimed now that the FSA- methodology has been accepted into wide use
by the maritime safety researchers and safety practitioners.
Due to the generic nature of FSA it should be clear for everyone that when
assessing the safety or risk of a ship on a certain route, or ships in a certain
sea area, the local conditions should be taken into account.
When applied by this way, the process of carrying out a quantitative risk
assessment and the results of it may produce very useful safety
performance indicators (SPIs). The reliability of these SPIs depends on the
Buhari, C. M. B. Tech (Maritime Technology Page 42
validity of the risk models and the validity data, input parameters and
constant values.
It can be stated that those parameters that have the biggest effect on the
outcomes are probably the most important safety (performance) indicators.
The most important indicators can be found by the use of sensitivity
analysis. Any change in these parameters will have either a favourable or
unfavourable effect on the risk and safety (unless there is no effect at all).
Thus, if there are not any changes present that would necessitate a change
of the risk model, the most important input parameters of valid risk models
should be used as the safety performance indicators.
Buhari, C. M. B. Tech (Maritime Technology Page 43
CHAPTER FOUR
4.0 NATURE OF SAFETY PERFORMANCE
INDICATORS
4.1 General information
For purposes of this research, the term “indicators” is used to mean
observable measures that provide insights into a concept (safety) that is
difficult to measure directly. There are basically two types of indicators.
There are:
1) Activities indicators: There are designed to help identify
whether organisations are taking actions believed to lower risks;
and
2) Outcome indicators: are designed to help measure whether
such actions are, in fact, leading to less likelihood of an accident
occurring and/or less adverse impact on human health or the
environment from an accident.
Since it is difficult to directly measure the success of actions taken to
improve safety, Safety Performance Indicators was designed to help
organisations develop alternative means to measure performance. In so
doing, organisations can help identify what actions have been (or are likely
to be) successful in improving safety. It can also improve understanding
of whether goals established (by law/regulation {either at National or
International level}, corporate policies, or community objectives) are
Buhari, C. M. B. Tech (Maritime Technology Page 44
being met.
Therefore, Safety Performance Indicators simply means any measurement
that is causally related to accidents or injuries, used in addition to a count
of accidents or injuries, in order to indicate safety performance or
understand the process that leads to accidents.
A large number of potential safety performance indicators exist. Not all of
them are equally important. In general, the importance of a safety
performance indicator can be assessed in terms of the strength of its
relationship with accident or injury occurrence, if it makes a major
contribution to accidents and if it can be influenced by maritime safety
measures or programmes.
Safety performance indicators (SPIs) are widely used within some safetycritical industries, e.g. Maritime industry or Shipping companies. The
purpose of using such indicators is to keep track on the trends and
developments of safety. Safety performance indicators can be used by the
industry itself but also by the authorities, whose responsibility it is to look
after that the operation of the industry is safe enough. In these two cases
the indicators may be the same, but this may not always be necessarily so.
At its best the use of safety performance indicators can give useful support
for decision-making regarding risk management and in directing
resources aimed for improvements in some specific areas where proactive
Buhari, C. M. B. Tech (Maritime Technology Page 45
development is needed.
One of the most easily observed indicators of (deficient) safety today is the
number of accidents. Trends in the development of the statistical data
based e.g. on the annual number of accidents may in some cases (but not
always!) be used as an indicator of the development of the safety.
The general descending trend in the accident statistics within most sectors
of transportation and other industries, too, has been clearly demonstrated to
follow the mathematical formulation presented e.g. by (Duffey et Saull,
2003). This general decrease in the number of accidents is based on the
lessons learned from the previous accidents, the efficiency and distribution
range of the dissemination of this new knowledge. Other important factors
affecting the trend are technological changes and changes in the legislation,
the latter belonging to a wider framework of sociological changes. If a
sociological change, e.g. a new rule is efficiently taken into worldwide use
at a time, it may lead to an abrupt change of the accident statistics.
In some cases the indicators cannot be based on statistics. The withdrawal
of water from the beaches of Phuket on Boxing Day in 2005 was clearly a
leading indicator, or a precursor of the tsunami that shortly afterwards hit
the people and buildings at the waterfront with full fierce. In this case the
earthquake was another, even earlier, single indicator of a tsunami,
although generally not as reliable indicator as the other. However,
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application of both seismology as well as technology has made it possible
to build dedicated warning systems against tsunamis. They may not predict
a tsunami with a reliability of 100 percent, but are still very useful when
being able to give an early warning of a significant hazard.
Accidents can often be classified according to their sub-type and on the
basis of their consequences. The number of accidents (per time unit) is the
simplest type of safety performance indicator. New indicators can be
derived from the number of registered accidents, e.g. the number of
accidents per some time unit, e.g. one year. Thus, it is possible to obtain
the annual frequency of accident occurrence. Other derivatives may
include the number of accidents divided by some other characteristic
quantity. Such quantities can be e.g. in transport safety the cumulative
distance travelled, the number of voyages or the size of the fleet.
The exposure (time or some other characteristic parameter) per unit should
be somehow included in the derivative (SPI) in order to make them more
comparable to similar SPIs elsewhere. In some other industries, the
specific type and amount of production defines the quantity by which the
number of accidents is divided, e.g. energy in power production. In
occupational safety one relevant quantity is the number of individuals and
their time of exposure (to the hazards).
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A clear distinction should be made between personal safety indicators
(related to occupational or work-related safety) and process safety
indicators (related to major hazards). The reasonable accentuation
between the different types of safety indicators is an important
question, due to the difference between various industries, processes, sites,
structural arrangements, operations, operators, environments and
conditions. An unbalanced portfolio of indicators with too much emphasis
on personal (occupational or work-related) safety performance indicators
may have negative effect on the industry, especially, if this is the case at
the expense of process safety in an installation running under the risk of
a major accident.
The purpose, effectiveness and reliability should always be considered
when selecting the safety indicators. According to (Grabowski et al. 2007)
a primary purpose in measuring safety is to develop intervention strategies
to avoid future accidents.
The selection of safety performance indicators should be soundly based on
an underlying model of safety and the precursor forces that lead to the
failures of concern (Wreathall, 2008). To develop effective interventions
(to promote safety), indicators are needed to identify where to direct the
limited resources (Körvers et Sonnemans, 2008). Several indicators are
always needed, because focusing just on a single aspect can often be
inefficient or even misleading (Mengolini et Debarberis, 2008).
Buhari, C. M. B. Tech (Maritime Technology Page 48
The use of safety performance indicators can facilitate communities’
relationship with industry and public authorities by, for example,
providing a basis for motivating industry and public authorities to improve
safety. In addition, safety performance indicators might provide a basis
for facilitating communication with other stakeholders concerning safety
and can help to identify weaknesses.
Figure 12: THE SAFETY STAKEHOLDERS TRIANGLE
4.2 Safety Performance Indicators in Safety
Programme.
This programme illustrates the role of safety performance indicators in
a wider context and serves as a device for identifying important safety
performance indicators.
! (Targeted) safety programmes
❙
❙ Safety measures implemented
❙ ”
❙ Operational conditions of transport production (performance indicators)
❙ ”
❙ Consequences of operational conditions (accidents) ↔ social costs
❙
$ Safety targets (policy intentions)
Figure 13: Identifying Safety Performance Indicator
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Targeted safety programmes produce a set of safety measures to be
implemented. These measures result in certain operational conditions of
transport production, which in addition to the safety measures, are also
influenced by a broad set of environmental and societal factors. The term
‘operational conditions’ comprises measures of operator behaviour and the
technical condition and quality of the infrastructure and the vessels used.
The operational conditions of transport production result in a certain
accident rate and number of casualties, usually taking into account the
differing severity of accidents. These numbers are compared to safety
targets, in order to monitor progress in achieving them.
4.3 leading and lagging indicators
According to (Allford, 2008) the development of safety performance
indicators is currently a hot topic within the process safety community. A
wide compilation of the views of several researchers and practitioners of
process safety has been published quite recently with various views
regarding the taxonomy (Hale, 2008a). This interesting debate, consisting
of short presentations of individual views on the issue, was initially
inspired by an article by (Hopkins, 2008a), discussing the dimensions of
leading and lagging indicators.
In the reply to the comments regarding his article (Hopkins, 2008b)
highlights the diversity of understandings of leading and lagging indicators.
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One example concerns the sufficient number of events to make it possible
to measure an increase or decrease. According to (Hopkins, 2008b) a
single event cannot be counted as an indicator on the selected basis.
However, several of his respondents have taken the opposite view by
claiming that even a single warning event can be described as an
indicator. Hopkins admits the possible importance of such weak
signals, giving even an example of a single warning event, but keeps
strictly to his selected principle: “indicators are based on a sufficient
number of instances to be able to identify change over time”. Thus,
(Hopkins, 2008b) defines an indicator as a slope of a trend in time. A
partition of leading and lacking indicators as before and after accident
indicators, illustrated to Reasons ”Swiss-cheese” model, see figure 14, is
one of the approaches to simplify and facilitate understanding of
differentials between leading and lagging indicators.
Figure 14 Leading and lagging safety performance indicators in the context of the
“Swiss-cheese” accident model of Reason.
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(Hopkins, 2008b) states that the main point of his earlier article (Hopkins,
2008a) was that “the distinction between leading and lagging indicators is
not clear” and “it may not be important to make this particular
distinction”. However, most of his respondents consider that the
distinction is important. (Hopkins, 2008b) states also that it is not helpful
to call performance measures, like number of component failures, rates of
Personal Protective Equipment usage and frequency of walk-arounds, lead
indicators or even indicators. He continues by explaining that this is
because each one measures how well the particular risk control is
performing.
Sudgen et al. (2007), Grabowski et al. (2007), Körvers et Sonnemans
(2008) and Mengolini et Debarberis, (2008). Have all written topics on
Leading and lagging safety performance indicators in resent time.
Although the shift of the main focus of some safety authorities from
mainly technical aspects to human error and later to safety management
and safety culture, i.e. organizational aspects as a whole, can be clearly
seen and referred to (Mengolini et Debarberis, 2008), none of the
different sectors and levels should be grossly neglected. Due to the
many ubiquitous changes in our environment, in society, in technology,
and in their interactions, there will always be a need for frequent updates of
the information and data of safety critical parameters and indicators. Thus,
older models like the one presented by (Tuovinen et al. 1983), may still be
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valid today. As the potential number of causal factors and their
combinations associated in marine accidents is high (Tuovinen et al. 1983),
there might still be use for new approaches in marine accident modelling
4.4 Maritime Safety Performance Indicators
In maritime environment various hazards and risks have been prevalent for
many centuries. Ships, cargoes and their crews have been lost during
storms, sometimes during good weather, too. Experience that has been
gathered during the past centuries and the new knowledge, closely related
to the results of scientific research have both been utilized in developing
today’s internationally regulated maritime safety management system. Best
practices of good seamanship have thus developed as a process of
evolution. They have now been included in the ISM code, which gives
general framework for guidelines related to operational practices. The
education of seamen and officers has been based on practical and
theoretical education. Long intervals for gathering work experience
between promotions have ensured the existence of sufficient experience
among the higher ratings, officers and masters. Today, the educational
requirements for the crew are included and described in STCW-code. The
educational level and experience of the crew might be possible to be
described as numerical indicators, but the measurement of real skills and
capabilities is a bit more difficult task.
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In the good old days of sailing ship era the ship systems were seldom,
if ever, as complicated as today and extra hands were always available just
in case some sailors would have been lost during the long journeys.
Although the navigational aids were much simpler and had more
limitations than the current integrated systems, they were more easily
understood and used, once their principles of operation were learned.
Even though the principle of international shipping, based on the United
Nations Convention on the Law of the Sea (UNCLOS) is the freedom of the
seas, some legislation actually reduces it by form of authorized
inspections. Due the observed lack of proper inspection by some flag states
a Memorandum of Understanding on Port State Control (MoU) was signed
in 1982 by 19 European states and Canada. This first Memorandum was
named Paris MOU and it has been followed by others. (Kristiansen,
2001)
4.5 PORT STATE CONTROLS
Port State Control (PSC) is an inspection regime for vessels calling at the
ports of those states that are signatories to the Paris Memorandum of
Understanding (MOU). With the purpose of eliminating substandard
vessels, the aim is to inspect each vessel in a period of two years.
4.5.1 Inspections and Deficiencies of Vessels.
An inspection covers many aspects
such as:
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Ships’ certificates.
Crew matters (certificates of
competency, minimum crew, etc.)
Working spaces.
Lifesaving appliances (lifeboats,
rafts buoys, EPIRBs (a
locating device in emergency
conditions), etc)
Fire fighting appliances
Accident prevention (personal
equipment, protective equipment,
pipes, etc.)
General safety (watertight doors,
safety plans and signs, escape
routes, steering gear, pilot
ladders, etc.)
Alarm signals (general alarm and
fire alarm)
,
Currently there are ten safety regimes, which cover most of the
coastal states, including Nigeria (West and Central Africa coast state),
imposing Port State Controls (PSC). These regimes are (Knapp, 2006):
– Europe and North Atlantic (Paris MoU)
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– Asia and the Pacific (Tokyo MoU)
– Latin America (Acuerdo de Viña del Mar)
– Caribbean (Caribbean MoU)
– West and Central Africa (Abuja MoU)
– Black Sea (Black Sea MoU)
– Mediterranean (Mediterranean MoU)
– Indian Ocean (Indian Ocean MoU)
– Arab States of the Gulf (Riyadh MoU)
– US (US Coast Guard)
All above regimes divide inspection following way
(Knapp, 2006):
– Priority inspections
– Initial inspections
– More detailed inspections in case of “clear grounds”, if the
inspector feels it is necessary:
Clear grounds are defined by the IMO (Knapp, 2006)
as follows:
1. The absence of principal equipment or
arrangements,
2. Ship’s certificates are clearly
invalid,
3. Certificates are incomplete, not maintained or falsely
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maintained,
4. Evidence from general impression and observation reveals serious
hull or structural deterioration that may place at risk the structural,
watertight or weather tight integrity,
5. Evidence from general impression and observation reveals
serious deficiencies in the area of safety, pollution prevention or
navigational equipment,
6. Master or crew is not familiar with essential shipboard operations
relating to the safety of ships or the prevention of pollution,
7. Key members cannot communicate with each
other,
8. Emission of false distress alerts followed by proper cancellation
procedures,
9. Receipt of a report of complaint containing information that the
ship is substandard
According to Kristiansen (2001),
Inspection may result in:
Deficiency: a non –conformity, technical failure or lack of
function. A deadline for correction will be given.
Detention: a serious deficiency or multitude of deficiencies
that must be corrected before the vessel is allowed to leave
the port.
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Banning: ship having a multitude of detentions or lacking an
ISM certificate may be banned from particular waters.
Paris MoU have introduced deficiency codes, see table 1, which have
been more or less followed by other regimes, with the exception of US
Coast Guard. This coding system facilitates in finding of critical and
repeating lacks, thus the system can be used as a source of safety
performance indicators.
Table 1 Description of Main Deficiency Codes, Adopted from (Knapp, 2006)
,
The table below indicates the major statistics of the Paris MOU on Ports
state.
Table 2: Basic Statistics of the Paris MOU on Port State Control (Paris MOU 1999)
Year Calls Ships Inspections. Ships with
Deficiencies
Detained
ships
# deficiencies
1997 10719 16813 8863 1624 53311
1998 11168 17643 9677 1598 57831
1999 66210 11248 18399 10255 1684 60670
The second column of Table 2 shows the number of calls in Member
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States used to determine the inspection effort. One should note that these
numbers are not the values of the number of ship calls: this is in excess of
300,000 per year. The third column indicates the number of individual
vessels inspected. The number of inspections increases with the number of
detentions. Vessels with non-serious deficiencies that are allowed to depart
need to show in the next port of call that the defects have been remedied
also increasing the number of inspections. This leads to a new inspection
of the vessel on top of the agreed 25 percent. The fifth column indicates the
number of inspected vessels having one or more deficiencies and the
number of detentions is given in column 6. The total number of
deficiencies is given in the last column. Of those vessels with deficiencies,
the average number of defects is six.
In 1999, the Port State Control Committee decided that the detention
percentage should be used to classify countries, listing them as black,
grey or white according to the level of risk associated with their vessels.
According to Paris memorandum of understanding
The following marine safety performance indicators have been defined:
Number of inspections related to the estimated
number of calls.
Number of inspections with deficiencies related to
the number of inspections.
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Number of detentions related to the number of
inspections.
Number of deficiencies per inspection.
Number of individual deficiencies related to the
number of inspections.
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Buhari, C. M. B. Tech (Maritime Technology)
CHAPTER FIVE
5.0 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1 SUMMARY
The indicators selected in the toolbox of maritime safety management
should be able to indicate relevant changes in all different areas of
maritime transportation having influence on safety. Safety management
will probably reach its goals more easily, if good safety performance
indicators (SPIs) are available and properly used for control and guidance.
Therefore, it seems beneficial to develop such indicators in good time.
For every master knows that the navigation of a ship requires observations
regarding the sea area ahead of the vessel. The use of lookouts is
familiar to most masters and mates. On the other hand, a chief engineer
may sometimes need to take a look at the wake of his vessel. Similarly, the
use of leading and lagging indicators as a tool of the safety management
system onboard, in a shipping company or the maritime administration
should not be a totally new idea within this context.
The traffic intensity, e.g. the frequency of port calls could be one of the
indicators. Similarly, the number of passengers and the type and amount of
cargo onboard should have some effect on the safety. The proportion of
sub-standard ships is for certain an indicator of safety, but it must be
remembered that although the age of the ship may have a general
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diminishing effect on the safety level of ships, there are exceptions, vessels
that are kept in good condition regardless of the age. Therefore, some
general trends may be more difficult to assess what one would at first
glance assume.
History has taught us that many accidents may have had a long series of
similar type of incidents before the disaster. Some stakeholders may have
reacted to the incident data realizing its significance and carrying out
the required actions to avoid the danger, or reduced the probability or
the consequences. Unfortunately, in maritime sector the flow of the safety
critical information and the execution of required countermeasures have
not been ideal (Hänninen, 2007).
The use of technical equipment for measuring traffic density used routes
and nearby accidents should not be overlooked as a possible indicator
donor.
It is beneficial to identify safety threats before they realize themselves in
an accident. If such systems are considered worth of while to be
established, as they are, it is utmost important that these systems do not
only act as data storages, but an element of a well working system of
incident data analysis and synthesis refining the most important
information to the levels of Nigerian Maritime industries where the
decisions concerning the use of sufficient resources to the required
countermeasures can be made.
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5.2 CONCLUSIONS AND RECOMMENDATIONS
For ages, the concept of utilising indicators for the continuous monitoring
and analysis of processes has been standard practice in industrial quality
management. The Nigerian Maritime safety community should exploit
this simple and robust concept. As soon as it has been introduced and
established, the application of safety performance indicators will further
stimulate safety work and thus reduce accident rates across Nigerian
maritime sector.
In the maritime sector the most widely used safety performance indicators
is the lagging indicators. Since such indicators are most often related to the
number of accidents, accident frequencies and the consequences, measured
by the loss of life, persons injured, total losses, material damage in terms of
costs and environmental damage.
One major limitation of with lagging safety performance indicators is the
fact that the approach is reactive and not proactive. Thus, something bad
(such as a near miss or an accident, itself) must first happen to make a
change in the indicator. Efficient accident investigations provide us with
information regarding the cause(s) and contributing factors related to the
accident under scrutiny. This is important to make it possible to avoid
similar accidents in the future. However, the problem with accidental
losses might be avoided if an efficient information system based on
efficient development and use of risk models with significant leading and
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lagging indicators would be available. Therefore, the development of such
a proactive system for the Nigeria maritime sector should be known.
An ideal safety information system would facilitate analysis and synthesis
of data taking into account accident investigation reports, accident
statistics, incident reports, developments in science and trends in society,
technology and traffic on several levels:
Global level (internationally)
EU (PMOU)
Sea area (Baltic Sea)
Fleet (of a shipping company)
Ship type
Ship
Stakeholder (Individual, Organisation, or Government)
It is believed that a solution to the problems might be in systems based on
risk models facilitating a less viscous flow of information.
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Campbell, D.J., Connelly, E.M., Arendt, J.S., Perry, B.G. and Schreiber, S. (1998)
Performance Measurement of Process Safety Management Systems.
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APPENDIX
P.O. Box 141,
Festac town
Lagos, state.
10th of October, 2011.
Managing Director,
Thou: Public Relation Department
Nigerian Ports Authority
Marina, Lagos.
Dear Sir,
APPLICATION FOR COLLECTION OF STATISTICAL DATA
I humbly wish to apply for a collection of data on the annual number of accidents per some
time, say a study period of ten years.
This is as a result of it necessity in my research work on “Safety Performance Indicators (SPIs) in
Nigerian Maritime Safety Management”.
A complimentary report of this research will be available for your comments, if you so desire.
Yours faithfully,
…………………………
Buhari, Chima Momoh
(B.Tech, Maritime Technology)
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