Articles by Human
Reliability
Computer-based tools for identifying and preventing human error
Causal models which affect the quality of incident investigations
Consensus based Approach to Risk Management (CARMAN)
Data collection systems
Getting at the underlying systemic causes of SPADS: A new approach
Incorporating management & organisational factors
Introduction to performance influence factors
System for predictive error analysis
Task analysis techniques
Understanding human behaviour and error
A set of computer based tools identifying and preventing human error in plant operation
by David Embrey, Sara Zaed
This paper describes a set of techniques, supported by computer based tools, for predicting and preventing human errors in gas plant operations. The first two tools allow an analysis of the task structure and prediction of the errors that could arise at a task or subtask level, together with the potential consequences of these errors. The third tool develops a profile of the factors in the situation (e.g. workload, fatigue, distraction levels) that affect error probability, and the most cost effective interventions to reduce errors. The software is able to provide an estimate of the likelihood of the errors occurring. A simple graphical analysis method is provided as part of the toolset to support the analysis of accident sequences in retrospective analyses. The paper includes case studies illustrating the application of the tools to gas plant operations and the measurement of mental workload of bridge crews in shipping operations.
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Causal models
which affect the quality of incident investigations
by Karen Wright, Claire Whittington, Jamie Henderson
Human Reliability was commissioned by the
Health & Safety Executive to carry out a survey of current industry
practice in incident investigation, given the proposed new duty to investigate.
This article outlines how the model of accident causation that an organisation
or individual holds can have an impact on the overall quality of an investigation.
Two approaches to incident investigation based on causal models at opposite
ends of a spectrum are discussed and illustrated with case studies.
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paper (pdf)
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CARMAN - A Consensus
based Approach to Risk MANagement
by David Embrey
The first section of the paper discusses the relationship between 'Best
Practice' and formal procedures in high-risk systems such as chemical
processing, aerospace and transportation. The results of a survey, which
addressed the factors influencing the use of procedures in a high-risk
industry, are described. This and other evidence shows that there is often
a wide disparity between the formal written procedures in an organisation
and the ways in which the work is actually carried out. This has major
implications for the control of risks and the maintenance of quality.
The paper describes how a culture can be created in which operations staff
actively participates in assessing the risks in the system and developing
best practices to control these risks. The buy-in provided by this process
creates a culture where best practices become the preferred practices.
A comprehensive description of this process, called CARMAN (Consensus
based Approach to Risk Management) is provided, together with a set of
case studies illustrating its application.
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Data Collection
Systems
by David Embrey
The function of this document is to provide an overall framework within
which to describe the important aspects of data collection systems. The
emphasis on data collection in this document will be on methods for identifying
the causes of errors that have led to accidents or significant near misses.
This information is used to prevent the reoccurrence of previous accidents,
and to identify the underlying causes that may give rise to new types
of accidents in the future. Data collection thus has a proactive accident
prevention function, even though it is retrospective in the sense that
it is usually carried out 'after the event' (an actual accident or near
miss).
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Getting at the
underlying systemic causes of SPADS: A new approach
by Karen Wright, David Embrey & Martin Anderson
Now, more than at any other time in the history of the railways, there
is an urgent need for the industry to learn lessons from near misses and
incidents. In this first of two articles, we examine the extent to which
the current procedures for gathering data on accidents such as SPADs provide
support for the identification of underlying causes. An alternative approach
is outlined, which we believe has the potential to allow a much more comprehensive
and structured assessment of underlying causes to be made during SPAD
investigations. This process is based on the research findings on the
causes of SPADs, combined with the practical knowledge possessed by experienced
personnel such as drivers and Driver Standards Managers.
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Incorporating
management and
organisational factors
by David Embrey
This paper is concerned with how management and organisational influences
can be factored into risk assessments. A case study from the rail transportation
sector illustrates how organisational factors can act as high level influences
which are manifest as operational errors giving rise to major accidents.
A model is proposed which describes the interrelationships between management
influences, immediate causes and operational errors. This model can be
used for organisational auditing, monitoring and system design. A strategy
is described for collecting data from an existing organisation to develop
a specific form of the generic model. The final issue addressed is the
use of the model to quantify the effects of organisational influences
on risk arising from human error. A numerical case study is provided to
illustrate the approach.
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Introduction
to performance influencing factors
by David Embrey
Performance Influencing Factors, or PIFs, are factors that combine with
basic human error tendencies to create error-likely situations. In general
terms PIFs can be described as those factors which determine the likelihood
of error or effective human performance. It should be noted that PIFs
are not automatically associated with human error. PIFs such as quality
of procedures, level of time stress, and effectiveness of training, will
vary on a continuum from the best practicable (e.g. an ideally designed
training program based on a proper training needs analysis) to worst possible
(corresponding to no training program at all). When PIFs relevant to a
particular situation are optimal then performance will also be optimal
and error likelihood will be minimised.
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Systems for predictive
error analysis
by David Embrey
It is widely recognised that human error in industrial operations is
a major source of risk that needs to be considered when plants are designed,
modified or operated. The increasing interest in this area has arisen
partly from the occurrence of a number of major accidents where human
error has played a significant role, but also as a direct result of recent
safety legislation. A means for the proactive identification of areas
where the potential for these errors exist would therefore be very useful.
The paper presented here describes such a tool, the programme for its
introduction to a site, and some results of its application and use. The
tool itself assesses the potential for error by systematically assessing
the factors which influence human performance and has been designed to
be used by plant personnel with minimum training. It is introduced into
a plant in conjunction with the work force, who have an active part in
its application, and once this has been done they become owners and users
of the tool.
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Task analysis
by David Embrey
Task analysis is a fundamental methodology in the assessment and reduction
of human error. A wide variety of different task analysis methods exist,
and it would be impracticable to describe all these techniques here. Instead,
the intention is to describe representative methodologies applicable to
different types of task.
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Understanding
human behaviour and
human error
by David Embrey
A paper concerning error types and
classifications with a focus on a number
of models of human performance such as Generic Error
Modelling System and
the Step Ladder Model.
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(pdf)
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