Understanding Human Error in Industry

Abstract

It is proved that most of industrial accidents are related to some kind of human failure, sometimes with catastrophic consequences. The present paper refers to human error probability in industrial activities. The paper intends to make a literature revision referring important concepts about human behaviour and human reliability. It is fundamental to identify tasks, actions or activities that depend on human behaviour or even determine the conditions that influence human error and thus increasing risk. With this goal, the most important methods, techniques and tools to assess human failure (error) are referred showing their potential applicability.

Full text

1
Mech
a
2
Cent
r
Abstract.
accidents
a
s
ometimes
present
p
a
p
industrial
literature
about hum
f
undament
a
that depen
d
the condit
i
increasing
methods,
t
f
ailure (er
r
applicabili
Key words
machine i
n
1. INTRO
D
It is know
n
one of the
risk anal
y
(HOFs) se
t
several m
e
years. Se
v
straight
r
maintenan
c
Industry i
s
new meth
o
decrease t
h
The paper
refers to a
n
importanc
e
HRA an
d
UND
a
nical Engine
e
r
e for Marine
It is prove
d
a
re related to
s
with catast
r
p
er refers to
h
activities. Th
e
revision ref
e
an behaviour
a
l to identify
d
on human b
e
i
ons that influ
e
risk. With th
i
t
echniques a
n
r
or) are refer
r
ty.
:
H
uman Reli
a
n
teraction.
D
UCTION
n
that human
r
most difficul
t
y
sis. Human
a
t
a huge chall
e
e
thodologies
v
eral accident
s
r
elationship
c
e and ope
r
s
searching a
n
o
ds and strate
g
h
e probability
o
is structured
n
introductio
n
e
of the the
m
d
makes ref
e
ERSTAN
D
e
ring Depart
m
Technology
Univ
d
that most
s
ome kind of
h
r
ophic conse
q
h
uman error
p
e
p
aper inten
d
e
rring import
a
and human r
e
tasks, action
s
e
haviour or e
v
e
nce human e
r
i
s goal, the m
o
n
d tools to
a
r
ed showing t
h
a
bility, Huma
n
r
eliability anal
y
t
issues when
a
nd organiza
t
e
nge to risk a
n
that appeare
d
s
are reporte
d
with huma
n
r
ation (M&
O
n
d investing
i
g
ies, in order
t
o
f a human fai
l
into 5 sectio
n
n
to describe t
h
m
e. Section 2
e
rence to so
m
D
ING HU
M
J.
S
m
ent, Institut
o
P
o
a
nd Ocean E
n
e
rsidade de
L
jsobral
@
of industrial
uman failure,
q
uences. The
p
robability in
d
s to make a
a
nt concepts
e
liability. It is
s
or activities
v
en determine
r
ro
r
and thus
o
st important
a
ssess human
h
eir
p
otential
n
Error, Man-
y
sis (HRA) is
dealing with
t
ional factors
n
alysts despite
d
in the last
d
referring a
n
error on
O
) activities.
n developing
t
o mitigate or
l
ure.
n
s. Section 1
h
e scope and
is related to
m
e methods,
M
AN ER
R
S
obral
1,2
o
Superior d
e
o
rtugal
n
gineering (
C
L
isboa, Lisbo
a
@
dem.isel.ipl.
p
techniq
u
b
ehavi
o
referre
d
the mo
s
section
2. HU
M
Reliabi
l
success
.
of an i
g
iven c
o
also be
is main
l
probabi
l
reliabili
t
more c
o
make
a
factors
experie
n
There
i
reliabili
t
in acco
r
states
t
p
robab
i
with su
c
“huma
n
based
o
analysi
s
reliabili
t
“it is t
h
accomp
deman
d
R
OR IN IN
D
e
Engenharia
d
C
ENTEC), In
s
a
, Portugal
p
t
u
es and to
o
o
ur of humans
w
d
in section 3.
S
s
t common m
e
5 some concl
u
M
AN RELIA
B
l
ity is strictly
.
In fact, relia
b
tem to perfo
r
o
nditions for
a
defined as a
p
l
y focused on
l
ity of surviv
a
t
y is frequen
t
o
mplex conce
p
a
n error is d
i
such as th
e
n
ce, the perso
n
i
s not a un
i
t
y. However,
s
r
dance with th
e
t
hat “human
i
lity of a wor
k
c
cess in a giv
e
n
reliability i
s
o
n the know
l
s
”. A more
c
t
y is mention
e
h
e probability
lishment of a
d
ed, in a given
p
D
USTRY
d
e Lisboa (I
S
s
tituto Super
i
o
ls currently
w
hen perform
i
S
ection 4 refer
e
thods and to
o
u
sions are state
d
B
ILITY
related to th
b
ility is defin
e
r
m a require
d
a
given time i
n
p
robability” [1
]
physical asset
a
l upon a giv
e
t
ly described
p
t. The probab
i
rectly influe
n
e
ability, th
e
n
al correctness
i
versal defini
t
s
everal author
e
ir point of vi
e
reliability is
k
or task to
b
e
n time”. Kir
w
s
a discipline
l
edge of reli
a
c
omplete defi
n
e
d by Pallerosi
of a person n
required tas
k
p
eriod of time
,
S
EL), Lisboa,
i
or Técnico,
applied. T
i
ng an activit
y
s some details
o
ls and finally
d
.
e probability
e
d as “the abil
d
function un
d
n
terval and m
]
. This definiti
s rega
r
ding th
e
e
n time. Hu
m
as a wider a
n
ility of someo
n
ced by seve
r
e
training,
t
and the aging.
t
ion for hu
m
s try to defin
e
e
w. Meister [
1
linked to
t
b
e accomplish
w
an [7] says t
h
of Ergonom
i
a
bility and r
i
n
ition of hu
m
[13] saying t
h
ot to fail on
t
k
(action), wh
,
under adequ
a
he
y
is
of
in
of
ity
d
er
ay
on
e
ir
m
an
n
d
ne
r
al
t
he
m
an
e
it
1
0]
t
he
ed
h
at
i
cs
i
sk
m
an
h
at
t
he
en
a
te
75

environmental conditions and with available
resources to perform it”.
Human reliability is an issue that started with a study
in the 50’s at Sandia National Laboratories (USA) to
determine the feasibility of a defensive armed
system operated by persons [16]. More recently the
concept of HRA emerged in the literature as the way
to identify the error, quantify human reliability
(probability) and find how to mitigate or reduce
human error [7].
The first methods were essentially based on the
person’s behaviour and not on cognitive factors and
thus were considered as “first generation methods”.
It was a mechanical approach and the persons were
identified as mechanisms or components. Later, with
the introduction of cognitive factors as the skills,
knowledge and rules appeared the “second
generation methods” [14]. Nowadays, some methods
are already referred as “third generation methods”.
More than thirty methods, techniques and tools can
be described.
Several works in distinct areas can also be referred,
as for example in the aviation field [15], medicine
[11], nuclear field [5], transportation [2] or
petrochemical facilities [9], among others.
3. HUMAN FAILURE
As stated before, most of HRA relies on human error
events. In accordance to Pallerosi [13] human
failures can be classified into different categories, as
represented in Figure 1.

Figure 1 - Human failure classification.
According to Pallerosi the most common cause of
human failures is error. These errors are dependent
of operator capability, stress factors, motivation and
environmental conditions. Mistakes usually happen
due to fatigue or stress or even bad environmental
conditions or person’s aging but the main reason is
due to lack of training for a specific activity.
Deliberate transgressions are linked to behavioural
procedures and are not related to capabilities,
training of physical characteristics but lack of
responsibility or impunity. The unintentional ones
are often related to lack of knowledge of procedures
or rules. Other classification of human error is done
by Swain and Guttmann [17], as shown in Figure 2.
Figure 2 - Categories of incorrect human outputs in
HRA (adapted from [17]).
It is also relevant to refer the relationship or
interaction between man and machine and point out
how it can affect human error.
Machine controls should be adapted, taking into
account human physical, mental and sensorial
capabilities. The machine must have an adequate
design of controls and panels and environmental
conditions should be supervised and controllable.
All these aspects are very important if one wants to
decrease the probability of human failure (error) and
thus improve safety and production in industrial
activities.
The emergence of new technological concepts leads
to new interfaces man-machine. CPS systems
(Cyber-physical systems) are a new generation of
integrated computational (software) and physical
(hardware) systems that can interact with humans
through many new modalities [8].
The hardware and software must be highly
dependable, reconfigurable and, where required,
certifiable, from components to fully integrated
systems. This can give rise to new types of human
errors, as there must be total reliance on software to
control processes and operations [8].
4. METHODS, TECHNIQUES AND TOOLS
In the present section it will be presented a brief
description of the most known methods, techniques
and tools for HRA.
4.1 Technique for Human Error Rate Prediction
(THERP)
First developments of this methodology started in
the 50s with military purposes in a way to diagnose
the probability of occurrence of human error and
evaluate the degradation of man-machine due to
these errors in high risk industrial facilities.
Although thought at the beginning for application in
the nuclear field, THERP can be used in several
industries with credible results [6]. However, some
disadvantages are pointed out to the method as the
76

high need of resources, excessive detail found in
some evaluations and the absence of enough
instructions for the determination of PSFs
(Performance Shaping Factors) impact on operator’s
performance.
4.2 Accident Sequence Evaluation Program
(ASEP)
ASEP method was developed in 1987 by Swain (the
same author of THERP) also for the U.S. Nuclear
Regulatory Commission due to the necessity to have
a method that could estimate human error
probabilities (HEPs) and response times for tasks
performed during normal operating conditions and
post-accident operating conditions, being
sufficiently accurate for probabilistic risk assessment
(PRA) and requiring only a minimal expenditure of
time and other resources [18]. On the contrary of
THERP methodology, ASEP was specifically
developed for nuclear industry and thus not
applicable to other sectors.
4.3 Human Error Assessment and Reduction
Technique (HEART)
HEART was developed with the aim to be a simple
and quick method to quantify risk related to human
error and to give suggestions on how to proceed to
reduce such error. The first presentation of this
technique was done by Williams at a conference in
UK, in 1985 [19], being developed and detailed in
further works done by the same author [20] [21]. It
is a general technique, recognized as a successful
and cost-effective tool for predicting human
reliability and identifying ways of reducing human
error. It can be also applied to any industrial
operation due to its methodology being centred upon
the human operator rather than the technical process.
4.4 Standardized Plant Analysis Risk - Human
(SPAR-H)
This methodology was also developed by the Idaho
National Laboratory for the U.S. Nuclear Research
Commission in 1994 with the aim to build an
approach and development of probabilistic models
to assess human reliability in NPPs. Various
combinations of contributory factors were examined
and given a rating based on their combined effect on
dependency among tasks. The ratings of the various
combinations correspond to zero, low, moderate,
high, or complete dependency among tasks. A more
detailed explanation of each factor and the
relationship analysis between factors can be
analysed in the reference document [3]. The
methodology is mostly directed to the nuclear
industry.
4.5 Cognitive Reliability and Error Analysis
Method (CREAM)
This method was developed by Hollnagel in the 90s
and presented in a scientific paper in 1998 [4]. It is
described as a bidirectional method and is based on
the distinction between competence and control. The
method classifies human error into causes
(genotypes) and manifestations or effects
(phenotypes), regardless of whether it is for a
retrospective or a predictive purpose.
4.6 A Technique for Human Event Analysis
(ATHEANA)
ATHEANA is an assessment technique that provides
a useful structure for understanding and improving
human performance in operational events. It is the
result from a study of operational events and from an
attempt to reconcile observed human performance in
the most serious of these events with existing
theories of human cognition and human reliability
models, within the context of plant design,
operation, and safety [12]. This technique is
concerned with identifying and estimating the
likelihood of a situation in which operators take
actions that render a plant unsafe. ATHEANA
differs from other methods because it attempts to
identify and determine the probability of a situation
that can trigger an unsecure or unsafe action in plant
personnel.
5. CONCLUSIONS
It is fundamental to assume that the impact of human
reliability is as important as the impact of physical
asset’s reliability when performing an industrial risk
assessment or a generic risk analysis. As it can be
observed from the previous paragraphs, the
estimation of the probability of human error is a
complex task, once it can be influenced by several
factors. Despite all the factors to be considered, it is
also important to recognize how sensorial and
cognitive processes work in humans.
In the last two decades there is a notorious effort in a
way to create methods, techniques and tools that
help analysts to understand and reduce human
failures when performing an activity. For obvious
reasons the nuclear industry has been all over the
years the motor for investigating and developing
new models. Some of these models can be applied in
other fields of industry, being possible to incorporate
this new paradigm into traditional analysis. It was
77

briefly presented a set of methods, techniques and
tools and their main characteristics showing a
variety of concepts and concerns around the human
reliability. Whatever the method used for
determining HEP, the most important is to assure
that human failures are effectively considered in any
HRA and PSAs.
REFERENCES
[1] BSI (2010). EN 13306 - Maintenance
Terminology. British Standards Institution, UK
[2] Dhillon, B. (2007). Human reliability and error
in transportation systems. Springer. London,
UK
[3] ERM (2018). Human Error Assessment &
Reduction Technique (HEART) - Appendix
12.10.
http://www.epd.gov.hk/eia/register/report/eiare
port/eia_2242014/EIA/app/app12.10.pdf.
Accessed in 27-06-2018
[4] Hollnagel, E. (1998). Cognitive Reliability and
Error Analysis Method. Elsevier. Amsterdam,
Netherlands
[5] IAEA (2008). Collection and classification of
human reliability data for use in probabilistic
safety assessments. International Atomic
Energy Agency. Vienna, Austria
[6] Kirwan, B. (1994). A guide to practical human
reliability assessment. Taylor & Francis.
London, UK
[7] Kirwan, B. (1999). Some developments in
Human Reliability Assessment. The
Occupational Ergonomics Handbook. CRC
Press. New York, USA
[8] Lee, J., Bagheri, B. and Kao, H. (2015). A
Cyber-Physical Systems architecture for
Industry 4.0-based manufacturing systems.
Manufacturing Letters, vol. 3, pp. 18–23
[9] López, E., Moura, M., Jacinto, C. and Silva Jr,
M. (2008). A semi-Markov model with
Bayesian belief network based human error
probability for availability assessment of
downhole optical monitoring systems.
Simulation Modelling Practice and Theory,
vol. 16, pp.1713-1727
[10] Meister, D. (1993). Human reliability database
and future systems. Reliability and
Maintainability Symposium Proceedings, pp.
276-280. Atlanta, USA
[11] Montague, M., Lee, M. and Hussain, S. (2004).
Human error identification: an analysis of
Myringotomy and ventilation tube insertion.
Archives of Otolaryngology Head Neck
Surgery, vol. 130, pp. 1153-1157
[12] NRC (2000). Technical Basis and
Implementation Guidelines for A Technique
for Human Event Analysis (ATHEANA) Rev.
1. NUREG-1624. Division of Risk Analysis
and Applications. U.S. Nuclear Regulatory
Commission. Washington, USA
[13] Pallerosi, C. (2008). Confiabilidade Humana:
Nova metodologia de Análise Qualitativa e
Quantitativa. 6º Simpósio Internacional de
Confiabilidade. Florianópolis, Brasil
[14] Rasmussen, J. (1987). The definition of human
error and taxonomy for technical system
design. New Technology and Human Error.
John Wiley & Sons. Chichester, UK
[15] Shappell, S, and Wiegmann, D. (2004).
HFACS analysis of military and civilian
aviation accidents: a North American
comparison. International Society of Air Safety
Investigators, pp. 2-8, Queensland, UK
[16] Swain, A. (1990). Human reliability analysis:
Need, status, trends and limitations. Reliability
Engineering and Systems Safety, vol. 29, pp.
301-313
[17] Swain, A. and Guttmann, H. (1983). Handbook
of human reliability analysis with emphasis on
nuclear power plant applications. NUREG/CR-
1278. U.S. Nuclear Regulatory Commission,
Washington, USA
[18] Swain, A. (1987). Accident Sequence
Evaluation Program Human Reliability
Analysis Procedure. NUREG/CR-4772. U.S.
Nuclear Regulatory Commission, Washington,
USA
[19] Williams, J. (1985). HEART – a proposed
method for achieving high reliability in process
operation by means of human factors
engineering technology. Proceedings of a
Symposium on the Achievement of Reliability
in Operating Plant, Safety and Reliability
Society. Southport, UK
[20] Williams, J. (1986). HEART – a proposed
method for assessing and reducing human
error. Proceedings of the 9th Advances in
Reliability Technology Symposium. Bradford,
UK
[21] Williams, J. (1988). A data-based method for
assessing and reducing human error to improve
operational performance. Proceedings of IEEE
Fourth Conference on Human Factors in Power
Plants, pp. 436-450. Monterrey, USA
78