Case Study1. Review the information in your textbook ( Leveson,.docx

Case Study
1. Review the information in your textbook ( Leveson, 2011,
pp. 75-100) related to the STAMP model.
2. Download the two peer-reviewed journal articles, located in
the required reading section for this unit, from the CSU Library
(Academic Search Complete database) and read both articles.
3. Use the CSU APA-styled paper as a formatting template.
Click here, to access the template:
a. Compare and contrast the Construction Accident Causation
model and the STAMP model.
b. Identify STAMP model features inherent within the Accident
Causation Management System.
c. Describe the benefits and limitations of the STAMP model,
the Construction Accident Causation model, and the Accident
Causation Management System as each attempt to assist OSHA
in the mission of addressing the aspect of human behavior
within their respective designs.
4. Prepare a minimum three-page Case Study with no fewer than
the three sources identified for the study.
Information about accessing the Blackboard Grading Rubric for
this assignment is provided below.
Running head: INTEGRATION OF MOBILE APPS INTO
EDUCATION 1

Integration of Mobile Apps into Education
Student Name
Columbia Southern University
Sample Research Paper
This is the running head. The words “Running head:”
should only appear on the title page. On all
subsequent pages, the header should consist of the
title in all capital letters. Be sure that the title within
the running head is 50 characters or less including
spaces.
Paper Format
-Times New Roman 12 pt.

INTEGRATION OF MOBILE APPS INTO EDUCATION 2
Abstract
This paper explores the importance of mobility that is expected
in every area of life today.
Students assume that their particular schools’ websites and
learning management systems will be
available on their mobile devices. Schools need to consider how
mobile applications (apps) can
be used within their academic and social realms. The cost and
positive effects will need to be
researched by each institution to discover if mobile apps would
be effective tools to use. A
variety of apps are already available for use as is the technology
for schools to create their own
apps. Geographic locating, instructional, scheduling,
administrative, and e-learning options can
provide additional and more productive learning experiences for
students. Educators and

academic institutions do not need to be left behind in the use of
mobile applications to facilitate
learning and further assist their students in their educational
pursuits.
This is the running head.
Center the word
Abstract. Not Boldface.
The abstract should be between 150-250 words. There is a
subtle difference between an abstract
and an introduction. The introduction introduces the topic,
often in creative ways and with
background information. The abstract summarizes the paper in
a very structured way. You will often
find statements in the abstract that you were taught to never

write in an introduction… “This paper
explores…,” or “This paper defines…,” or even “The articles
examine…” The abstract basically lets the
readers know what is in the paper so they can decide whether it
will be useful to read the entire
paper, or if they should keep looking for an article that better
suits their needs. Abstracts are
typically found in academic journals, so you have to imagine
that the paper you are writing for class
right now might end up in an academic journal someday!
Do not
indent
the
first
line.
Integration of Mobile Apps into Education

Technology has become an important element in almost every
aspect of people’s lives. It
has been integrated into the educational process over and over
again throughout the years and
has given newer and better tools to help facilitate learning. One
such tool, the Internet, has given
the area of distance education digital steroids that have
propelled online learning into a major
league status. In keeping up with emerging technologies,
schools are now hoping to incorporate
mobile learning into both their traditional and distance classes.
Universities are creating mobile
apps to allow students to participate in their classwork in and
out of the classroom (Olavsrud,
2011). The question for educators becomes whether mobile apps
are valid and valuable tools or
are just unneeded additions to their curriculums.
Pros of the Issue
Today people on their phones, email on their phones, shop on
their phones, and look for
the best gas prices on their phones. Anything someone can do
on his or her computer, he or she
can do on his or her phone. In most professions, it would be
difficult to succeed without a

mobile device. It allows for more efficient work. To facilitate
learning, one might ask why not
access and use all that mobile technology has to offer.
Kukulska-Hulme and Traxler (as cited in
Zawacki-Richter, Brown, & Delport, 2009) state that mobile
technologies can “open up new
opportunities for independent investigations, practical
fieldwork, professional updating, and on-
the-spot access to knowledge. They can also provide the
mechanism for improved individual
learner support and guidance, and for more efficient course
administration and management"
(para. 14).
Center the full title of the
document. Not Boldface.
When paraphrasing information, text citations
should include the author(s) and the year of
publication. If no year is available, use n.d. for
no date within the parentheses.
When using information from someone who is quoted within the
source but is not the author of the
source, this is called a secondary source. Here is an example of

how to cite a secondary source. Notice
that Kukulska-Hulme and Traxler are not listed on the reference
page because they are quoted within the
text by Zawacki-Richter, Brown, and Delport. Since this is a
direct quote a page or paragraph number must
be included to show where the quoted information is found and
will come at the end of the quote if the
author(s) and date are at the beginning of the sentence.
This is a level one heading.
Centered, Boldface.
Mobile applications (apps) can be used with campus maps and
GPS location to help
students navigate across campuses as well as access school
directories and event schedules,
Additionally, students can research schools’ libraries and other
facilities, find reference
information, practice needed skills, submit assignments, and
access grades. (Engebretson, 2010).
Campus groups can use apps to send mass messages and conduct
anonymous polling.

“Professors are able to utilize apps to send attendance reports,
send automatic emails to absent
students, and have class or group discussion forums”
(Engebretson, 2010, para. 3). General
educational apps from various authors can be downloaded by
students and can be very
beneficial. Apps in English Language Arts; Mathematics;
Science; History and Geography;
Language Development; Art, Music, and Creativity; Reference,
Productivity, and Collaboration;
and Accessibility could all play significant rolls in many
educational venues (Apple, 2012).
Cons of the Issue
As with any improvement to a system, there are difficulties and
obstacles to overcome.
One issue that surrounds using mobile apps in education is that
educators are trying to fit the
apps into the traditional, centuries’ old version of teaching
(Olavsrud, 2011). This is like fitting
a square peg into a round hole, and less tech-savvy educators
would rather not have to deal with
yet another technological advancement. Within learning
institutions, having apps that are usable
on a variety of systems is also an obstacle (Olavsrud, 2011).

Students and educators are using
varying devices and systems, and apps need to be able to work
efficiently across all these
systems. Long writing assignments are also difficult to
accomplish through an app on a phone or
tablet. Although shorter discussion forums work well, most
would agree that essays and any
kind of creative design are too complex to work out on a mobile
device. Security issues also
have to be recognized and dealt with especially “compliance
with the Family Educational Rights
Direct quotations require the listing
of the author(s), year of publication,
and the page or paragraph number.
If a quote is not a complete thought and
is used as part of sentence, the quote
will NOT begin with a capital letter.
and Privacy Act (FERPA) pertaining to student records”
(Olavsrud, 2011, p. 22). Quillen (2011)
also tells us that there are not many apps out there that have
“content designed to fit the face-to-

face classroom” (p. 16). Most apps designed to run on hand-
held devices do not let teachers
monitor student progress or save student data.
My Position on the Issue
As an educator, I want to use anything that will benefit my
students. Looking at the
overwhelming advantages of mobile apps and their potential use
within academia, I believe they
will become an important asset to education. I would like for
my GED students to be able to use
mobile apps to help them succeed in their test preparation.
There are not any adult basic
education apps, but there are some apps for basic subjects that
could be integrated into our
curriculum. My students might work harder and more often if
they could pull out their mobile
devices while waiting in the doctor’s office or in the car line
and work on skills they need to
build in order to pass the GED exam. Whether for GED, K-12,
or higher education, mobile apps
can be an unparalleled resource for educators and learners alike.
If someone were marketing a fantastic new brand of sneakers,
he or she would study

demographics and put ads in places where the population is
more apt to purchase the sneakers. If
someone running a restaurant was going to add a new sandwich
to the menu, he or she would
add something people really liked to eat. Why is education any
different? We need to take
education to where the students are. Among 18 to 24 year olds
in America, 67 percent own a
smartphone (Lytle, 2012). Students want to have access to their
technology no matter where
they are. Giving them access to their classes on their mobile
devices just makes sense.
The world of mobile applications is the new frontier (Quillen,
2011). As educators
explore it, they will find even better ways to use apps to
facilitate learning. As educators begin
This is another way to cite a direct
quote when using the author’s
name within the sentence.
Academic writing does not include 1st
person (I, me, my) unless the
assignment requires personal opinions.

to deal with those pesky obstacles they encounter, they will
learn how to overcome them. Some
inventive software has already been developed by LanSchool
Technologies (Quillen, 2011). To
combat the issues involving teachers not being able to access
data from student’s work on apps, a
certification procedure has been implemented for apps. Apps
qualifying for certification give
codes to teachers for them to be able to access student progress
and usage (Quillen, 2011).
Mobile apps can transform how students learn. As Mike
Pennington so succinctly says
(as cited in Walker, 2012), “Schools need to embrace mobile
technology and mobile learning.
Students live in this world. These devices belong in the
classroom” (para.3). Whether it is
allowing college students to save money by not having to buy
expensive $100 scientific
calculators (because the app is only $1.99!) or letting GED
students practice basic algebra, apps
can be unparalleled learning resources. It is predicted that in
the next five years, smart phones or

tablets will be in the hands of every student in the United States
(Walker, 2012). Because of this,
using mobile apps in education seems to be inevitable.
If a quote is a complete thought,
it will begin with a capital letter.
References
Apple. (2012). iPad in education. Retrieved from
http://www.apple.com/education/ipad/apps-
books-and-more/
Engebretson, J. (2010, February 3). Universities log on to hand-
held mobile apps. Retrieved from
http://connectedplanetonline.com/topics/distance-
learning/universities-hand-held-mobile-

apps-0203/index1.html
Lytle, R. (2012, September 21). 5 apps college students should
use this school year. U.S. News &
World Report. Retrieved from
http://www.usnews.com/education/best-
colleges/articles/2012/09/21/5-apps-college-students-should-
use-this-school-year
Olavsrud, T. (2011, June 20). Colleges deploying mobile
learning apps. Retrieved from
http://www.schools.com/articles/colleges-deploying-mobile-
learning-apps.html
Quillen, I. (2011). Mobile apps for education evolving.
Education Week, 04(02), 16-17.
Retrieved from
http://www.edweek.org/dd/articles/2011/02/09/02apps.h04.html
Walker, T. (2012). Get smart! Using mobile apps to improve
your teaching. NEA Today
Magazine. Retrieved from http://www.nea.org/home/41992.htm
Zawicki-Richter, O., Brown, T., & Delport, R. (2009). Mobile
learning: From single project
status into the mainstream? European Journal of Open, Distance
and E-Learning.
Retrieved from ERIC database.

The word “References” should
be centered at the top of the
page and is not boldface.
This is an example of a reference list. All text citations must
have a corresponding entry on the reference list.
It is formatted with a hanging indent and double-spacing.
arriers that
d due to lack
m factors
these causal
ent causation
idents—it
analyzes the
haviors—it
uld” follow.
edges the
g
he new
requency of
ts.
Systems Model of Construction Accident Causation
Panagiotis Mitropoulos1; Tariq S. Abdelhamid2; and Gregory
A. Howell3

Abstract: The current approach to safety focuses on prescribing
and enforcing “defenses;” that is, physical and procedural b
reduce the workers’ exposure to hazards. Under this
perspective, accidents occur because the prescribed defenses are
violate
of safety knowledge and/or commitment. This perspective has a
limited view of accident causality, as it ignores the work syste
and their interactions that generate the hazardous situations and
shape the work behaviors. Understanding and addressing
factors that lead to accidents is necessary to develop effective
accident prevention strategies. This paper presents a new accid
model of the factors affecting the likelihood of accidents during
a construction activity. The model takes a systems view of acc
focuses on how the characteristics of the production system
generate hazardous situations and shape the work behaviors, and
conditions that trigger the release of the hazards. The model is
based on descriptive rather than prescriptive models of work be
takes into account the actual production behaviors, as opposed
to the normative behaviors and procedures that workers “sho
The model identifies the critical role of task unpredictability in
generating unexpected hazardous situations, and acknowl
inevitability of exposures and errors. The model identifies the
need for two accident prevention strategies:~1! reliable
production plannin
to reduce task unpredictability, and~2! error management to
increase the workers’ ability to avoid, trap, and mitigate errors.
T
causation model contributes to safety research by increasing
understanding of the production system factors that affect the f
accident. The practical benefit of the model is that it provides
practitioners with strategies to reduce the likelihood of acciden
DOI: 10.1061/~ASCE!0733-9364~2005!131:7~816!
CE Database subject headings: Occupational safety;

Construction site accidents; Accident prevention.
as a
sures
aised
safety
injury
the
the
f
d on
en-
that
f the
iors.”
li-
, en-
t
li-
ance.
acci-
ance
h.
. It
safety
zards
of
eased
dd

table
afety
ts are
s to
ch as
a less
d the
ffec-
ces in
es are
ol of
ment
323.
um,
ssions
te by
ging
pos-
2004.
-
05/
Introduction
In recent years, construction accident rates have declined
result of substantial effort by many parties. Increased pres
from OSHA and owners, and increased cost of accidents r
the contractors’ awareness. In turn, contractors increased
training and enforcement. These efforts have reduced the
and illness rate from 12.2 in 1993 to 7.9 in 2001. However,

rate of fatalities has shown little improvement—since 1997,
number of fatalities per year is consistently over 1,100~Bureau
o
Labor Statistics 2004!.
The current approach to accident prevention is base
OSHA’s violations approach and focuses on prescribing and
forcing “defenses;” that is, physical and procedural barriers
reduce the workers’ exposure to hazards. The violations o
defenses are called “unsafe conditions” and “unsafe behav
This approach emphasizes~a! management commitment and po
1Assistant Professor, Arizona State University, Del E. Webb
Scho
Construction, Tempe, AZ 85287-0204. E-mail: [email protected]
2Assistant Professor, 207 Farrall Hall, Construction Manage
Program, Michigan State University, East Lansing, MI 48824-1
E-mail: [email protected]
3Executive Director, Lean Construction Institute, Box 1003,
Ketch
ID 83340. E-mail: [email protected]
Note. Discussion open until December 1, 2005. Separate discu
must be submitted for individual papers. To extend the closing
da
one month, a written request must be filed with the ASCE Mana
Editor. The manuscript for this paper was submitted for review
and
sible publication on January 8, 2003; approved on September 2,
This paper is part of theJournal of Construction Engineering and
Man
agement, Vol. 131, No. 7, July 1, 2005. ©ASCE, ISSN 0733-
9364/20
7-816–825/$25.00.

816 / JOURNAL OF CONSTRUCTION ENGINEERING AND
MANAGEMENT
cies to prevent unsafe conditions and~b! workers’ training and
motivation to prevent unsafe behaviors.
Safety programs, such as training, inspections, motivation
forcement, penalties, etc., emphasize competency~“competen
person” philosophy! and liability, and aim at increasing comp
ance with safety rules and increasing the cost of noncompli
The violations approach has contributed to the reduction of
dent rates, but it also has limitations, as high levels of compli
are costly and compliance does not ensure safety~Prichard
2002!.
The following are some limitations of the traditional approac
(1) Reactive approach. The violations approach is reactive
manages the hazards with defenses and relies on increased
effort to reduce accidents. A proactive approach avoids ha
~e.g., by using a less hazardous method!, reduces the safety risk
the production system and reduces accidents without incr
safety effort.
(2) Conflict with production . The safety effort does not a
value to production—it only replaces one type of unaccep
loss ~human suffering and financial consequences! with a more
acceptable cost. However, compliance requires significant s
effort and resources and in the short term, safety requiremen
in conflict with production and cost goals. This often lead
noncompliance.
(3) Uncertainty limits the effectiveness of defenses. Com-
pared to the well-structured, high-risk technical systems, su
nuclear and process plants, airplanes, etc., construction is
structured and loosely coupled system~Rasmussen 1997!. The
ill-structured, dynamic nature of the construction process an
large number of poorly defined situational hazards limit the e

tiveness of such defenses, as they create many circumstan
which the needed defenses are absent or existing defens
bypassed. Furthermore, safety defenses cannot address all types
© ASCE / JULY 2005
ot
erous
-
ck of
ives
e
does
What
may
-
il-
vio-
f the
ucture
tion
iola-
oot
elop-
ffec-
y and

f the
pe th
s and
l pre
ased
ts to
in-
era-
not
eling
and
cting
by-
s on
e the
ls of
duc-
that
ation
sents
scuss
new
l
.” A
left
-
ty of

ed in-
t, not
s and
es for
erent
ential
l
gy due
i-
ele-
s
ho-
causa-
-
man
ory
from
amid
ing,
The
t
ctions
e in-
n

tion
-
sors,
. The
fety
s
inci-
of
ided,
d, or
pre-
con-
of hazards~e.g., ergonomic hazards!, and in some cases cann
overcome the legacy of design and the need to work in dang
circumstances~e.g., roofwork!.
(4) Limited view of accident causality. The violations per
spective attributes accidents to the managers’ or workers’ la
safety knowledge and/or motivation. This approach perce
safety as a problem of “right versus wrong”~safe versus unsaf!
choice, and ignores the fact that the dynamic nature of work
not involve conscious decision making or risk assessment.
seems to be a rational act under a particular work situation,
easily be judged as a unacceptable mistake on
hindsight~Rasmus
sen 1990!.
(5) Limited learning . The focus on violations limits the ab
ity to learn from accidents. Accident investigation focuses on
lations and liability and does not increase understanding o
accident phenomenon; rather, it perpetuates the current str
by assigning blame. An evaluation of 17 accident investiga

methodologies used by public agencies found that OSHA’s v
tions approach is among the lowest in its ability to identify r
causes~Benner 1985!.
Better models of accident causation are essential for dev
ing effective accident prevention strategies. We argue that e
tive causation models need to take a systems view of safet
provide better understanding of how the characteristics o
production system generate hazardous situations and sha
work behaviors.
This paper develops a new causation model of the factor
processes that generate construction accidents. The mode
sented here, has the following attributes:
• It focuses on the activity level, as opposed to event-b
models that focus on the incident level. This model attemp
answer the question: “What causal factors and processes
fluence the number of accidents during a construction op
tion?” It is a conceptual model and at this stage it does
operationalize or quantify the variables.
• It takes a systems view of accidents—it is a causal mod
approach that moves away from looking at isolated events
looks at the production as a system made up of intera
variables~Sterman 2000!. Thus, accidents are viewed as
products of the production system and the model focuse
the characteristics of the production system that generat
risks and shape the work behaviors.
• It is based on descriptive rather than prescriptive mode
work behavior. That is, it takes into account the actual pro
tion behaviors, as opposed to the normative behaviors
workers “should” follow.
The model is based on previous research in accident caus

human error, and construction safety. The next section pre
the background literature. We then present the model and di
its implications. Based on the model, the paper proposes
directions for accident prevention.
Background Literature
Definitions
The National Safety Council~NSC! definessafetyas “the contro
of recognized hazards to attain an acceptable level of risk
hazard is defined as “an unsafe condition or activity that, if
uncontrolled, can contribute to an accident.”Risk is a term ap
plied to the individual or combined assessments of “probabili
loss” and “potential amount of loss.” NSC definesaccidentas “an
JOURNAL OF CONSTRUCT
e
-
,
occurrence in a sequence of events that produces unintend
jury, death, or property damage. Accident refers to the even
the result of the event.”
Accident Causation Models
Accident causation models attempt to understand the factor
processes involved in accidents in order to develop strategi
accident prevention. The different models are based on diff
perception of the accident process. Some of the most influ
accident causation models and methodologies are:~1! the Single

Event concept;~2! the Determinant Variable concept;~3! the
Domino Theory ~Heinrich 1936!; ~4! the Fault Tree analytica
methodology; ~5! the Energy-Barriers-Targets model, which
views the accident process as an unwanted release of ener
to inadequate physical or procedural barriers;~6! the Manage-
ment Oversight and Risk Tree, which focuses on “what” barr
ers failed and “why” they failed—that is, what management
ments permitted the barrier failure~DOE 1992!; ~7! Petersen’
Multiple Causation model ~1971!; and ~8! Reason’s ~1990!
‘ Swiss Cheese’ model of human error, and the “resident pat
gens” or “latent failures.”
Construction Safety Literature
Construction researchers have proposed several accident
tion models and root causes. McClay’s~1989! “universal frame
work” identified three key elements of accidents: hazards, hu
actions, and functional limitations. Hinze’s distraction the
~1996! argued that production pressures can distract workers
the hazards and increase the probability of accidents. Abdelh
and Everett~2000! identified management deficiencies, train
and workers’ attitude as the three general root causes.
“constraints-response” model~Suraji et al. 2001! argues tha
project conditions or management decisions~distal factors! can
cause responses that create inappropriate conditions or a
~proximal factors! that lead to accidents.
Organizational factors associated with safety performanc
clude top management’s attitude toward safety~Levitt 1975!, or-
ganizational culture~Molenaar et al. 2002!, safety climate~Mo-
hamed 2002!, superintendent practices~Levitt and Samelso
1987; Hinze and Gordon 1979!, and turnover~Hinze 1978!.
Hinze
and Parker~1978! found that job pressures and crew competi
are related to more injuries. Hinze~1981! found that good work
ing relationships improve safety.

In terms of safety practices, Jaselskis et al.~1996! identified
the frequency of formal safety meetings with project supervi
and safety budget as factors related to lower incident rates
Construction Industry Institute identified five best
practices~Liska
et al. 1993!: preproject and pretask planning for safety, sa
orientation and training, safety incentives~the effect of this ha
been debated!, alcohol and substance abuse programs, and
dent investigations. Toole~2002! identified eight root causes
accidents: lack of proper training, safety equipment not prov
deficient enforcement of safety, unsafe equipment, metho
condition, poor safety attitude, and isolated deviation from
scribed behavior.
Few researchers have emphasized the role of design in
struction safety~Hinze and Wiegand 1992; Gambatese 2000!
and
the importance of task characteristics and work method~Everett
1999! and proposed technological interventions to improve the
ION ENGINEERING AND MANAGEMENT © ASCE / JULY
2005 / 817
r than
n to
ork-
n re-
Rigby
eeds

dg-
c-
Rea-
two
ith
the
-
her
rrect
s
itua-
he
hav-
prac
.
or
acci-
iola-
by
er-
aints
s
ork-
etc.
loser
res-
ly the
effort

d-
sible
man
lim-
ed in
from
ward
rther-
tation
ehav-
s of
hat ac-
rror-
ntrol
k-
s
-
ds on
causa-
bles
tion
signs
rs; a
s, the
r
ect
the
the
ctivi-

ma-
per-
s
n-
ations
l con-
e, as
work-
s to
k-
res
zards.
” and
zard
ntrol
ut do
safety of specific construction operations~Bernhold et al. 2001!.
These approaches focus on reducing the safety risks, rathe
increasing the safety effort.
The construction safety literature has paid little attentio
worker errors and effective ways to manage errors in the w
place.
Human Error
Human error is a central element in accidents and has bee
searched extensively by researchers of high-risk systems.
~1970! defines an error as a set of human actions that exc
some level of acceptability. Traditionally, the standard of ju
ment is the normative~prescribed! behavior. From this perspe
tive, human error is a deviation from a normative procedure.

son~1990! classified unsafe acts in three types of errors, and
types of violations.
Errors. Slips and lapsesare “skill-based” errors and occur w
little or no conscious thought. A slip is an unintended error in
execution of an otherwise correct plan. Mistakes~or decision er
rors! involve the correct execution of a wrong plan. In ot
words, mistakes are intentional behaviors that involve inco
choice of action~inappropriate for the situation!. Perceptual
error
are actions that result from misinterpretation of the actual s
tion.
Violations. Routine violationsare habitual departures from t
rules and often tolerated by supervision. This may involve be
iors that are established practice as opposed to the specified
tice, such as driving 5 – 10 mph faster than the speed limitEx-
ceptional violationsare neither typical of the individual n
condoned by management.
Rasmussen’s Descriptive Model of Work Behavior
Descriptive models of work behavior attempt to understand
dents without reference to normative concepts of errors or v
tions. An important descriptive model is the one proposed
Rasmussen et al.~1994!. According to Rasmussen, workers op
ate within a work system shaped by objectives and constr
~economic, functional, safety related, etc.!. A worker searche
freely within those boundaries guided by criteria such as w
load, cost effectiveness, risk of failure, joy of exploration,
Figure 1 illustrates how the work behaviors tend to migrate c
to the boundary of functionally acceptable performance~limit of
loss of control! due to two primary pressures: the production p
Fig. 1. Rasumussen’s work behavior model~adapted from
Rasmussen et al. 1994!
sures for increased efficiency, and the tendency for least effort,

MANAGEMENT
-
which is a response to increased workload. Managers supp
“cost gradient” and the worker searches and finds a “least
gradient.” The result is a “systematic migration toward the boun
ary of acceptable performance, and when crossing an irrever
boundary, work will no longer be successful due to a ‘hu
error’” ~Rasmussen et al. 1994, p. 149!. A breakdown in work
performance indicates an operation too close to its capability
its and/or the limits of the ability to recover control.
Safety programs attempt to counter the pressures outlin
the Rasmussen model and prescribe “safe behaviors” away
the boundary. However, the pressures that push workers to
the boundary require that safety efforts are continuous. Fu
more, efforts to improve system safety lead to human adap
that compensates for safety improvements. Thus, the work b
ior is likely to be maintained close to the boundary of los
control. To address these problems, Rasmussen proposes t
cident prevention efforts should focus on development of e
tolerant work systems that make the boundary of loss of co
visible and reversible.
Based on Rasmussen’s framework, Howell et al.~2003! iden-
tify three zones of operation:~a! the “safe zone,” where the wor
ers’ behaviors are within the boundary defined by safety rule~b!
the “hazard zone”~or “near the edge”!, and~c! the “loss of con
trol” zone.
Accident Causation Model
Model Overview

Figure 2 presents the accident causation model, which buil
the Rasmussen model and previous construction accident
tion models. This conceptual framework identifies the varia
that influence the likelihood of accidents during a construc
activity. The arrows indicate cause-effect relationships. The
indicate the direction of the relationship between the facto
positive sign indicates that when the causal factor X change
effect Y changes in the same direction~X increase→Y increase
o
X decrease→Y decrease!. A negative sign indicates that the eff
changes in the opposite direction~X increase→Y decrease, X
decrease→Y increase!.
The characteristics of the activity and work context, and
task unpredictability shape the work situations within which
workers operate, and create hazardous situations. Different a
ties involve different hazardous situations, depending on the
terial, tools, location, etc. Furthermore, the same activity
formed under different method or context~physical condition
and surrounding activities! involves different hazards. Task u
predictability leads to unplanned tasks and unexpected situ
that also create hazardous situations. Safety efforts to contro
ditions reduce the hazardous situations.
Workers’ behaviors determine both the production outcom
well as the exposure to hazards. Production pressures and
load and the tendency for competent action drive worker
adopt more efficient work behaviors~such as working faster, ta
ing shortcuts, or working without the required safety procedu!,
which increase production, but also increase exposure to ha
The shaded section where the “hazardous work situations
“work behaviors” overlap indicates work behaviors in the ha
zone that expose workers to hazards. Safety efforts to co
workers’ behaviors reduce exposures to hazards.
Exposures to hazards create the potential for incidents, b

not necessarily lead to incidents. For an incident to occur, the
© ASCE / JULY 2005
dition
igger
ny er
con-
ectio
ver-
lease
pends
tors.
“near
and
s an
e not
with
t and
haz-
onal
r one
etect
situ-
ion is
and

dent.
work
of
an
rent
or
haz-
b-
tools
ent
ity
-
-
c-
fined
ate
bris,
may
nges
efore
tivity
n-
ed as
ated,

s may
hazard must be released. Human errors and changes in con
create a “mismatch” between conditions and actions and tr
the release of hazards. Not all errors release hazards—ma
rors are inconsequential, while other errors are “trapped” and
trol is recovered before the hazard is released. The shaded s
where “Exposures” and “Errors & Changes in conditions” o
lap, indicates the errors under condition of exposure that re
hazards and generate incidents. The likelihood of errors de
on the task, the environment, and the workers’ capacity fac
Depending on the consequences, an incident may be a
miss,” an injury accident, or a fatality.
The causation model in Fig. 2 depicts the key factors
processes that lead to accidents. Several other relationship
feedback loops exist, which are discussed briefly as they ar
as critical for understanding the accident process.
Hazardous Work Situations
In this paper, hazardous situations are defined as “situations
the potential to cause injury, unless the worker can detec
avoid the hazard, without exposing themselves to a greater
ard.” This definition acknowledges the subjective and situati
nature of many hazards. In other words, what is a threat fo
person may not be for another, depending on the ability to d
and avoid the hazard. Furthermore, what is a hazard in one
ation may not be in another. The hazardous situations definit
consistent with NSC’s definition, because the ability to detect
avoid a hazard reduces its potential to contribute to an acci
As shown in Fig. 2, the nature and number of hazardous
situations during an activity depend on the following
factors:~1!
characteristics of the activity and context,~2! safety efforts to
control conditions, and~3! task unpredictability. A discussion

these factors follows.
Activity and Context Characteristics
Different activities involve different hazards. Surveying in
Fig. 2. Accid
empty site involves few hazards, while steel erection includes
s
-
n
d
many more. Furthermore, the same activity involves diffe
hazardous situations if performed with a different method
under different conditions. There are three main sources of
ards:~a! the work technology,~b! the physical conditions,
and~c!
the surrounding activities.
(a) Work technology. The work technology includes the o
jects and actions necessary to perform the task, such as the
and equipment~scaffolds, power tools, cranes, heavy equipm!,
the material~e.g., heavy or sharp objects, chemicals, electric!,
the physical tasks required~material handling!, and the by
products of the production task~scrap metal, etc.!. The same ac
tivity may be performed with different tools and equipment~lad-
ders, scaffolds, or mechanical lifts!, or at different locations~on
the ground or at elevation! and involve different hazards.
(b) Physical conditions. The physical environment of the a
tivity ~such as high elevations, floor openings, trenches, con

space, overhead power lines, and housekeeping conditions! cre-
ates another set of hazards. Environmental conditions~such as
cold, heat, illumination, vibrations, noise, vapors, etc.! may
create
additional sources of hazards.
(c) Surrounding activities. Surrounding activities also gener
“threats,” such as falling objects, heavy equipment traffic, de
etc. The project schedule~sequence and timing of activities! af-
fects the work context. For example, out-of-sequence work
increase the difficulty and the hazards of the activity.
The number and nature of hazardous work situations cha
during the course of an activity. Some hazard sources exist b
the activity starts, while other hazards develop during the ac
~e.g., a trench is excavated!, tools and equipment wear out, co
ditions change, and surrounding activities start and end.
Task Unpredictability
Task unpredictability means that the work cannot be complet
planned—the scope of the task may be different than anticip
the actual conditions are different than expected, or resource
usation model
ent ca
be missing~information, tool, material, etc.!. Workers’ errors
also
2005 / 819
reate
bil-

d the
quired
e.g.,
re an
, the
, un-
more
han-
tasks,
ute”
ction
s” of
, eve
ure.
uces
rs
r ex-
indi-
on
r.
on-
e the
e the
as p
area
s are

rts to
tify
o pro
s and
pro-
age-
e the
ted.
ence
azard
e
nter
cient
s
y
d
hav-
s and
mea-
tion.
ovid-
quip-
vior-
ry of
ures.
time
“risk-
m-

s and
uch
iolate
ally
ce the
der
lead
afety
zards
afety
with
way
d by
y
educe
s to
g in
cam-
-
ad-
. First,
ision
amic
tion
dy-
ures
t-
olved
ely

to-
unter
x and
any
duc-
increase task unpredictability as errors by one crew may c
unpredictable conditions for a following crew. Task unpredicta
ity increases both the likelihood of hazardous situations, an
production pressures and workload.
Unpredictability Generates Hazardous Situations. First, the
resources, equipment, manpower, or safety measures re
may not be available for the unexpected tasks or conditions,
the crew planned for a 6 ft. ladder, but some locations requi
8 ft. ladder. Even if a crew performs safety pretask planning
plan will be inadequate if the task is unpredictable. Second
predictable tasks and conditions require increased effort,
movement of workers and equipment, increased material
dling, increased need to improvise, more out-of-sequence
and involve much chaos and confusion.
Unpredictability Increases Workload and Production Pres-
sures. This generates interruptions and “urgent/last min
problems that have to be resolved promptly, otherwise produ
can be significantly disrupted. This creates temporary “peak
production pressure and sudden changes to production pace
if the overall activity is not under particular schedule press
Furthermore, resolving the interruptions takes time and red
the time available for the planned task.
The increased production pressures may lead the worke~or
supervisors! to do the work in any way they can~“make do”!
without the appropriate safety measures or resources. Fo

ample, lack of adequate manpower may lead a worker to
vidually perform tasks that normally require two people~e.g.,
move heavy material, enter confined space, etc.!. Or, if a ladder
is
not tall enough for all the work locations, the worker may step
the last two steps, rather than look for an appropriate ladde
Much of the complexity and dynamism of the work in c
struction is caused by a failure to reliably plan and coordinat
work activities.
Safety Effort to Control Conditions
Safety measures to control conditions are barriers that confin
hazard sources, and prevent exposure to the hazards, such
rimeter cable, support of deep trenches, and closing-off the
under steel erection. OSHA regulations define what condition
hazardous and what safety barriers are needed. Safety effo
control conditions include training and inspections to iden
hazardous conditions, and the time and resources needed t
vide and maintain the safety measures. Economic pressure
time or personnel shortage may prevent management from
viding and maintaining the required safety measures. Man
ment commitment and policies that support safety increas
likelihood that the safety resources and effort will be commit
Efficient Work Behaviors
Efficient work behaviors increase production, but in the pres
of hazards such behaviors also bring the workers in the h
zone~expose workers to the hazards!, which in turn increases th
likelihood of incidents that may disrupt production and cou
any prior gains. Thus, under hazardous conditions, less effi
work behavior is required to prevent exposure.
Efficient work behavior is shaped by:~1! production pressure
and workload, which increase efficient behavior,~2! the tendenc

for competent action, which increases efficient behaviors, an~3!
safety efforts to control behaviors, which reduce efficient be
iors and consequently exposures.
MANAGEMENT
n
e-
-
Production Pressures and Workload
Rasmussen’s framework illustrates that production pressure
efforts to reduce workload may lead workers to avoid safety
sures, or not follow the safety rules if they slow down produc
Similarly, cost pressures may prevent management from pr
ing the required safety measures or appropriate tools and e
ment.
Tendency for Competent Action
The tendency for efficient, competent action is another beha
shaping factor, which pushes workers close to the bounda
loss of control, even in the absence of high production press
Workers take shortcuts or exert excessive effort to reduce the
to perform a task. These behaviors are typically considered
taking.” However, from the perspective of the worker, it is co
petent action—experienced professionals develop shortcut
tricks of the trade as efficient ways to perform the work. S
behaviors often are established trade practices that may v
prescribed procedures—they are “routine violations” typic
tolerated by supervisors. Such behaviors protect and enhan
workers’ feeling of competency. They are very efficient un
normal conditions, but under special circumstances they may

to accidents.
Safety Effort to Control Behaviors
When hazards cannot be contained with physical barriers, s
procedures are prescribed to prevent exposure to the ha
~lockout-tag out, or testing the air in confined spaces!. “Unsafe
behaviors” are those acts that violate prescribed procedure. S
programs and campaigns attempt to increase compliance
safety rules, and maintain work behaviors in the “safe zone” a
from the boundary.
The prevailing view is that unsafe behaviors are cause
lack of knowledge of the hazards~competent person philosoph!
or poor safety attitude. As a result, management actions to r
unsafe behaviors focus on training and motivating worker
comply with the safety rules. Such practices include trainin
safety rules and procedures, incentives and motivational
paigns~such as safety culture and value-based safety!, enforce
ment and punishments, and behavior-based safety.
The main limitation of these practices is that they do not
dress the systemic forces that push workers near the edge
the dynamic nature of work does not involve conscious dec
making or risk assessment; workers immersed in the dyn
flow of work do not make decisions based on careful situa
analysis but on know-how, heuristics, and a perception of
namic control, and they cannot follow prescriptive proced
prepared by outside experts~Rasmussen 1997!. Second, shor
term conflicts between safety and production are usually res
in favor of production, as efforts for production have relativ
certain outcomes and receive rapid and rewarding
feedback~Rea-
son 1990!. Finally, because the workers’ behaviors migrate
ward the boundary, safety needs to maintain continuous co
pressures. Last, but not least, in an unstructured, comple
dynamic environment like a construction jobsite, there are m

hazardous situations not covered by work rules.
Production
Efficient work behaviors increase production. Increased pro
tion reduces production pressures, which in turn reduce efficient
© ASCE / JULY 2005
hen
s re-
s the
s of
r can
l
rk-
rmal
t the
hout
ning
ive
ith
wer
etc.
t does

cted
ons
ciden
n con
e is a
l to
re re-
l
z-
cci-
fety
mad
is in
f loss
error
error
ystem
the
e ap-
be
the
age-
rrors
s.
a-
n

-
e-
rs
i-
d to
wrong
he
tor
ider-
med
ent
orkers
Error
devel-
-
are-
s to
ision-
s the
, etc.,
tive-
amo-
s is
pera-
se of
ho is
ip-

b-
sce-
quent
near
fast
then
n the
very
situ-
and
work behaviors. Production is also affected by accidents—w
the number and severity of incidents increase, production i
duced.
Exposure to Hazards
Exposure to hazards exists when the work behavior bring
worker in the “hazard zone” and near the boundary of los
control, where events can take place faster than the worke
detect and avoid the danger. Exposure are the result of:~a! effi-
cient behavior that leads to routine violations,~b! exceptiona
violations,~c! proper actions that are near the limits of the wo
er’s ability ~such as physical effort and ergonomic exposures!,
or
~d! unrecognized hazards: if a hazard is not identified, a no
work behavior may expose a worker to the hazard withou
worker’s knowledge.
Examples of exposures are working in a deep trench wit
sloping or trench protection, working near an unprotected ope
at high elevation without fall protection, working with defect
tools and equipment~knowingly or unknowingly!, performing
electrical work without lockout-tag out, working in an area w
heavy equipment traffic, operating equipment close to po
lines, working under another crew, handling heavy material,

Exposure to hazards creates the potential for accident, bu
not automatically lead to accident: a worker near an unprote
edge will not necessarily fall. In other words, “unsafe” conditi
and actions are not sufficient to cause an accident. For an ac
to occur, the hazard must be released. Errors and changes i
ditions trigger the release of the hazard: in both cases ther
“mismatch” between the situation and the action.
Errors and Changes in Conditions
Unlike violations, errors are unintended actions that fai
achieve their intended outcome. As discussed in the literatu
view, human error involves slips~unintentional loss of control!,
mistakes~selection of incorrect course of action! and perceptua
errors. Huang and Hinze~2003! found that misjudgment of ha
ardous situation was a significant factor in over 30% of fall a
dents.
Not all errors release hazards. An error will have no sa
consequences if there is no exposure to a hazard; e.g., errors
in flight simulators are inconsequential. However, if a worker
the hazard zone, an error may push him over the boundary o
of control, and release the hazard. If the worker detects the
soon enough to “trap” the error and recover control, then the
will not release the hazard.
Hazards are also released by changes in the state of the s
such as mechanical failures, loss of soil stability, etc. If
worker can react fast enough and adjust the behavior to on
propriate for the new conditions, then the accident can
avoided. If the change in the conditions is too sudden for
worker to recover control, it results in an accident. Error man
ment and situation awareness increase the ability to correct e
detect changes, and prevent or avoid the release of hazard

Error Inducing Factors
The likelihood of errors depends on the task demands~complex-
ity, dynamism, pressures!, the environment, and the workers’ c
pacity. According to Rasmussen et al.~1981!, causes of huma
“malfunction” include external events~such as distractions, com
ponent failures, or the physical environment!, excessive task d
mands ~due to task characteristics and situation!, performance
t
-
e
,
,
shaping factors~such as work load, skills, and stress facto!,
reduced capacity~due to fatigue, etc.!, or intrinsic human var
ability.
Natural drive toward economy of cognitive effects may lea
wrong assessment of situations and task demands, and
rules to be applied~Reason 1990!. Many perceptual errors are t
result of “cognitive confusion;” that is, the selection of a mo
program to execute a previously learned task while not cons
ing the new conditions of the environment the task is perfor
in or the new dimensions or design of the tools or equipm
being used.
Error Management
Error management is a set of strategies that enable the w
detect and correct errors before onset of consequences.

management strategies for individuals and team have been
oped in other sectors~primarily in military and commercial avia
tion! and have focused primarily on improving situation aw
ness~Endsley 1988!, and developing effective team processe
increase a team’s collective situation awareness and dec
making ~Helmreich et al. 1999!.
In construction, the primary error-management strategy i
use of warnings, such as signs, spotters, backup alarms
which alert workers when approaching a hazard. The effec
ness of such warning measures is limited. Blackmon and Gr
padhye~1995! found that the effectiveness of backup alarm
low because of the general noise level of the jobsite, the o
tors’ reliance on the alarms, and reduced attention.
Incidents and Consequences
An incident is the undesired event that results from the relea
the hazard. A hazard may be released by the same worker w
exposed to the hazard~e.g., a worker loses control of the equ
ment!, or by another worker~e.g., another worker drops an o
ject!. Table 1 lists examples of typical exposure to hazard
narios found on construction sites, and possible subse
scenarios of the release of hazards.
Depending on the consequences, an incident can be a
miss, an injury, or a fatality accident. If the worker can react
enough to avoid the hazard or interrupt the flow of events,
the incident is a near miss. The ability to react depends o
speed of the hazard release: when the loss of control is
sudden, there is no time to react. Worker’s experience and
ational awareness is critical in anticipating hazard release
Table 1. Hazard Scenarios on Construction Operations
Hazard Exposure to hazard Incident

Unprotected edge
~physical condition!
Worker near
unprotected edge
Worker slips and falls
Saw with dull blade
~undermaintained tool!
Worker using saw
with dull blade
Saw jams and kicks
back
Material handling
~activity element!
Worker lifts material A muscle exceeds
functional limit
Surrounding activities Worker in same area
w/excavator
Excavator turns and
hits worker
Surrounding activities Working under
another crew
Object falls and hits
worker

Unsecured power
source~physical
condition!
Working without
lockout-tag out
Another worker turns
on the power
taking appropriate action.
2005 / 821
miti-
equip
-
e
te or
d
d on
azard
from
the
lease
ening
king
hese
r per-
e
son

posed
eavy
nally
rker
lt to
. Al-
afe,”
d by
te the
the
ns.
es
. The
n
have
ow to
since
ani-
lso
they
nset
h are
ety
h in-
m, as
r fo-
under
keli-

onal
model.
ues-
uture
the
es the
nd the
to
could
rther
may
t
5
n
1
ame
tices.
ning
duces
and
s con-
kers
keep
ing:
ffi-
work

ss of
ome
be-
the
, we
s of
es,
Protective measures are “the last line of defense” and can
gate the consequences of an incident. Personal protective
ment increases the error tolerance of the system~e.g., fall protec
tion equipment reduces the consequences of falls!. The
magnitud
of injury also depends on situational factors that may aggrava
mitigate the injury ~including the individual’s tolerance, an
luck!.
Taxonomy of Incidents
The model identifies three different types of accidents, base
the source of exposure and the action that releases the h
This taxonomy is based on etiology of accidents, and differs
OSHA’s classifications.
~a! Loss of control.The first type involves situations where
person who is exposed to the hazard is also the one who re
the hazard. For example, a worker near an unprotected op
may slip or not see the opening and fall. Or a crane is wor
near a power line and comes in contact with the line. In t
cases, the release of the hazard is due to loss of control, o
ceptual failure to detect the boundary~the edge of the slab, th
distance from the power line!.
~b! Coordination.In the second type of incidents, the per
who releases the hazard is different than the one who is ex
to the hazard. For example, a worker is working near h

equipment, and the equipment operator turns and unintentio
strikes him. Or a worker is under another crew, and the wo
above drops an object. What makes such accidents difficu
prevent is that they happen under normal work behaviors
though the actions of both workers may be independently “s
they fail to adjust their behavior in the new conditions create
the presence of the other worker. Safety rules try to separa
crews and determine rules of “priority” and responsibility, but
dynamic conditions on the jobsite create many such situatio
~c! Unrecognized hazard.Another type of accidents involv
situations where the worker is exposed to a “hidden” hazard
hidden hazard can be a component near its functional limit~such
as an unsecured deck! and a normal behavior~such as walking o
the deck! may release the hazard. The hidden hazard may
been created by an error of a previous crew. The issue of h
address unrecognized hazards is a particularly difficult one
many things are not recognized as hazards until after they m
fest themselves~Prichard 2002!. Ergonomic hazards may be a
included in this category, as the workers cannot recognize if
are approaching the limit of physical tolerance~the limit of how
much weight the worker can safely lift, the time before the o
of cumulative trauma disorders such as tendonitis, etc.!.
Other Causal Relationships
Several other relationships and feedback loops exist, whic
not depicted in Fig. 2, such as~a! safety incidents increase saf
efforts, as management typically responds to incidents wit
creased efforts to control conditions and behaviors; and~b!
safety
incidents reduce efficient behaviors, at least in the short ter
workers behave more carefully after an accident. The pape
cused on the causal factors and relationships necessary to
stand the main forces at work. A model that considers the li
hood of accidents over time should take the additi

relationships into account.
MANAGEMENT
-
.
s
-
Model Discussion and Implications
The next section discusses some of the issues raised by the
It provides some supporting evidence, but mostly it raises q
tions, proposes hypotheses, and identifies directions for f
work.
Importance of Task Unpredictability
The model argues that the unpredictability of the task and
environment leads to increased accidents because it increas
number of hazardous situations, the production pressures, a
likelihood of errors. As a result, “unlikely events are likely
happen, because there are so many unlikely events that
happen” ~Per Bak 1996!.
The effect of task unpredictability on accidents requires fu
investigation. However, there is some initial evidence that it
be significant. A recent study~Thomassen et al. 2003! found tha
projects that used the Last Planner System®~LPS! for
production
control ~Ballard and Howell 1998! had an incident rate of 7.8

~12 incidents in 305,604 labor-hours!, while the incident rate o
projects that did not use LPS was 14.13~41 incidents in 580,37
labor-hours!. Both groups of projects were performed by the s
contractor, were of similar nature, and used same safety prac
These initial findings suggest that effective production plan
can have significant effect on safety, possibly because it re
the task unpredictability.
Task Unpredictability, Work Behaviors, and Safety
The model highlights the conflict between safety measures
the pressures for efficient behavior. Current safety measure
straint productive behaviors with a set of rules to keep wor
away from the hazard zone. Instead of asking how can we
workers from acting in more efficient ways, we should be ask
“ How can we make it safe for workers to work more e
ciently?”
Figure 3 proposes a relationship between task conditions,
behaviors, and accidents. The curve indicates the limit of lo
control. The figure illustrates that when task conditions bec
more complex and unpredictable, the efficiency of the work
havior must be reduced to avoid an accident.
In a simple example, the safe speed on a road~for a specific
driver and vehicle! depends on the condition of the road,
visibility, the traffic load, etc. To safely increase the speed
need to create conditions that reduce the likelihood of los
control. This may include increasing visibility around curv
Fig. 3. Work conditions, work behavior, and safe operation
widening the road, reducing the potholes and obstacles, etc. It is
© ASCE / JULY 2005

den
st ef-
ting
ated,
e of
age-
cope
sures
d.
mili-
in-
pro
s and
enti-
with
and
i-
rdless
s
e-
a-
tive
op-
n to
t

here
h as
ntrol
ASA
es in
es in
that
ity of
di-
ty of
was
heir
d on
age-
.
pro-
s
e
ilities
-
tions
r can
fore
and
nti-
way
n or

s-
ve
und-
nd it
influ-
given
ction
t. Of
t
-
ions
not re-
ment
haz-
res-
ap-
any
s the
pre-
ards
npre-
d, the
ions
ing
and
rk
so

ated
ined
r re-
rew
the
important to stabilize the work conditions and prevent sud
deterioration when workers are at a point of high efficiency.
Error Management
As discussed earlier, production pressures, tendency for lea
fort and task unpredictability often result in the workers opera
in the hazard zone. In addition, human error cannot be elimin
especially in complex and dynamic work situations. Becaus
the inevitability of exposures and errors, effective error man
ment is necessary in order to increase the workers’ ability to
with hazardous situations.
Error management provides a set of error countermea
with three lines of defense:~1! error avoidance,~2! error
trapping
~to prevent errors from propagating!, and ~3! error mitigation
to
reduce the consequences of those errors that are not trappe
Error management strategies have been developed first in
tary and commercial aviation and have focused primarily on
creasing situation awareness, and establishing effective team
cesses to increase a team’s collective situation awarenes
decision-making.
Situation Awareness
In aviation, problems with situation awareness have been id
fied as the leading causal factor in accidents associated

human error. Situation Awareness~SA! is the perceptionof the
elements in the current environment within a volume of time
space, thecomprehensionof their meaning~the “forces at work”!,
and the projection of their status in the near future~Endsley
1988!. SA is affected by individual factors~capabilities, exper
ence, fatigue/stress, set expectations, and “press-on-rega
mentality!, task factors~task overload and underload,
objective!,
and environmental factors~complexity, interruptions, and d
graded operating conditions!.
Team Processes (Crew Resource Management)
Crew Resource Management~CRM! was first developed in avi
tion to reduce accidents due to “pilot error.” CRM is an ac
process by crewmembers to identify significant threats to an
eration, communicate them to the pilot and carry out a pla
avoid or mitigate each threat~Helmreich et al. 1999!. In recen
years, CRM has been adopted by other high-risk operations w
effective work performance requires coordinated action, suc
hospital operating teams, oil platforms, and power plant co
centers.
Based on analysis of over 28,000 aviation accidents, N
discovered that over 70% of the accidents were due to failur
team communication and coordination rather than deficienci
technical proficiency. Further simulator studies confirmed
crew performance was more closely associated with the qual
crew communication than with the technical proficiency of in
vidual pilots. No differences were found between the severi
the errors made by effective and ineffective crews, rather, it
the ability of the effective crews to communicate that kept t
errors from snowballing into undesirable outcomes. Base
these findings, NASA developed the Cockpit Resource Man
ment system~later called Crew Resource Management! to im-
prove the crews’ situational awareness and decision making

CRM emphasizes the key nontechnical skills and team
cesses that affect operational safety. CRM training addressesitu-
ation awareness, contingency planningto identify ahead of tim
the proper response to abnormal situations, assign responsib
for handling problems, and predetermine crew roles for high-
-
”
workload phases of flight,stress management, and crew commu
nication such as cross checking and communicating inten
before the execution of actions, so that another crew membe
identify an inappropriate intention or action and correct it be
the error happens, soliciting input from all crew members,
assertivenessin alerting team members and supervisor of ide
fied threats and errors.
Other Error Management Strategies
Error proofing involves design of tools and equipment in a
that they can detect an abnormal condition and shut dow
independently act to prevent failure~such as stability control sy
tems in cars!. Rasmussen~1997! proposed that an alternati
strategy to safety rules is to increase the visibility of the bo
ary. The concept of boundary however is not well defined a
may include a physical boundary~the edge of the slab!, point of
loss of control~the crane’s point of loss of stability!, or a func-
tional limit ~the load a muscle can take!.
Directions for Accident Prevention
The model identifies several potential interventions that can
ence the safety outcome of a construction operation. For a

activity, the hazards can be reduced by changing the constru
method, the work sequence or the physical environmen
course, the activities required depend on design choices~e.g.,
cas
in place concrete versus steel structure!. However, given a con
struction method, the model identifies two important direct
for accident prevention:~1! reduce task unpredictability, and~2!
increase error management capability. These strategies do
place the safety defenses and technical training but comple
them.
Reduce Task Unpredictability
Reducing unpredictability will reduce unexpected tasks and
ardous situations, interruptions and ‘short-term’ production p
sures, and will reduce the likelihood of errors. The current
proach does not deal with the fact that workers face m
unpredictable situations. Safety pretask planning addresse
predictable hazards involved in an activity. However, in an un
dictable task or environment, there will be situations and haz
that safety pretask planning will not address. When task u
dictability is reduced, the task can be executed as planne
hazards will be predictable, and the defenses can be set.
This strategy shifts safety’s focus from controlling the act
of management and workers~follow the rules! to stabilizing the
work conditions.
Unpredictability can be reduced if the production plann
system produces high quality work assignments. Ballard
Howell ~1998! identify five requirements for high quality wo
assignments:~a! definition~work assignment is specific enough
that the right material can be provided, work can be coordin
with other trades, and at the end of the week it can be determ
if the assignment was completed!, ~b! soundness~all design in-
formation, material, prerequisite work, work area and othe

sources needed to complete the assignment are available!, ~c!
se-
quence~work is released in the correct sequence!, ~d! size ~the
assignments are sized to the productive capability of the c!,
and ~e! learning ~assignments not completed are tracked and
reasons identified!.
Only assignments that meet the quality criteria should be in-
2005 / 823
ess
viors
task
indi-
com-
but
team
. The
vi-
om-
at it
rac-
, and
een
e-
con-
to

con-
, the
ment
ch an
ward
s and
igated
push
tions
ener-
sures
egies;
ent
not
that
ropo-
nder-
ping
-
ep
th-
-
-
-

al
u-
en-
.,
.
nt
ion.”
,
,
ites,
The
ts
s-
on
ll
r
.
ruc-
rd
e-

.”
s.
ent
r-
ts.”
ro-
zed
ty.”
om/
in
cluded in the weekly work plans. In addition, the work proc
and conditions must be controlled to support efficient beha
~clear access, layout, location and sequence of subtasks!.
Finally,
during the task, the crew needs to periodically re-evaluate the
and conditions to prevent degradation.
Increase Error Management Capability
Construction has not developed systematic ways to train
vidual and teams in error management. The most developed
ponent is training in hazard identification which is essential,
not sufficient. The skills related to situation awareness and
processes are developed incidentally through experience
need for awareness and effective team processes~within a crew
and between different crews! becomes more important on acti
ties and projects with high uncertainty and complexity, c
pressed schedules, and limited work areas.
CRM’s main difference from existing safety practices is th

focuses on critical nontechnical aspects of the workers’ inte
tion that enable the crew to successfully recognize, cope with
recover from hazardous situations and errors.
A simple version of CRM adapted for construction has b
proposed by Mitropoulos et al.~2003!. In this approach manag
ment requires crewmembers to speak up when they identify
ditions that exceed their “comfort zone” in terms of ability
perform the work effectively and safely. Members can raise
cerns about the work method, the conditions in the work area
sequence of the work, the lack of safety measures and equip
lack of appropriate equipment for the task, etc. To support su
approach, management must take a non punitive policy to
errors, and must create a team environment that support
develops workers’ assertiveness.
Conclusions
The accident causation model presented in this paper invest
the production factors that generate hazardous situations and
the workers into the hazard zone. It also examined the limita
of current safety strategies in counteracting the problems g
ated by the production factors. The paper argued that expo
and errors are inevitable and proposed two alternative strat
reducing task unpredictability and improving error managem
capabilities. A limitation of the model is that it may have
considered other important factors and causal relationships
contribute to accidents. The model should be considered as p
sitions for testing. Future research should focus on better u
standing the effect of task unpredictability, and on develo
error management strategies.
References
Abdelhamid, T., and Everett, J.~2000!. “Identifying root causes
of con

struction accidents.”J. Constr. Eng. Manage., 126~1!, 52–60.
Ballard, G., and Howell, G.~1998!. “Shielding production:
Essential st
in production control.”J. Constr. Eng. Manage., 124~1!, 11–17.
Benner, L., Jr.~1985!. “Rating accident models and
investigation me
odologies.”J. Safety Res., 16, 105–126.
Bernold, L., Lorenc, S., and Davis, M.~2001!. “Technological
interven
tion to eliminate back injury risks for nailing.”J. Constr. Eng.
Man
age., 127~3!, 245–250.
Blackmon, R. B., and Gramopadhye, A. K.~1995!. “Improving
construc
tion safety by providing positive feedback on backup alarms.”J.
Con-
MANAGEMENT
,
str. Eng. Manage., 121~2!, 166–171.
Bureau of Labor Statistics.~2004!. “National census of fatal
occupation
injuries in 2003.” U.S. Department of Labor, Washington, D.C.
Department of Energy.~1992!. “Root Cause Analysis Guidance
Doc
ment.” DOE-NE-STD-1004-92, Washington, D.C.

Endsley, M.~1988!. “Design and evaluation for situation
awareness
hancement.”Proc., HF S, 32nd annual meeting, Santa Monica,
Calif
97–101.
Everett J.,~1999! “Overexertion injuries in construction.”J.
Constr. Eng
Manage., 125~2!, 109–114.
Gambatese, J. A.~2000!. “Safety constructability: Designer
Involveme
in Construction Site Safety.”Proc., Construction Congress VI,
Febru-
ary 20–22, Orlando, Fla., 650–660.
Heinrich, H. W. ~1936!. Industrial accident Prevention,
McGraw-Hill,
New York.
Helmreich, R. L., Merritt, A. C., and Wilhelm, J. A.~1999!.
“The evolu-
tion of crew resource management training in commercial aviat
Int. J. Aviat. Psychol., 9~1!, 19–32.
Hinze, J.~1978!. “Turnover, new workers, and safety.”J. Constr.
Div.
Am. Soc. Civ. Eng., 104~4!, 409–417.
Hinze, J.~1981!. “Human aspects of construction safety.”J.
Constr. Div.
Am. Soc. Civ. Eng., 107~1!, 61–72.
Hinze, J.~1996! “The distraction theory of accident
causation.”Proc., Int.

Conf. On Implementation of Safety and Health on Constr. Sites,
CIB
Working Commission W99: Safety and Health on Construction
S
L. M. Alvez Diaz and R. J. Coble, eds., Balkema, Rotterdam,
Netherlands, 357–384.
Hinze, J., and Gordon, F.~1979!. “Supervisor-worker
relationship affec
injury rate.” J. Constr. Div., Am. Soc. Civ. Eng., 105~3!, 253–
262.
Hinze, J., and Parker, H. W.~1978!. “Safety, productivity and
job pre
sures.”J. Constr. Div., Am. Soc. Civ. Eng., 104~1!, 27–35.
Hinze, J., and Wiegand, F.~1992!. “The role of designers in
constructi
worker safety.”J. Constr. Eng. Manage., 118~4!, 677–684.
Howell, G. A., Ballard, G., Abdelhamid, T., and Mitropoulos,
P.~2003!.
“Rethinking Safety: Learning to Work near the Edge.”Proc.,
Con-
struction Research Congress, March 19–21, Honolulu, Hawaii.
Huang, X., and Hinze, J.~2003!. “Analysis of Construction
Worker Fa
Accidents.”J. Constr. Eng. Manage., 129~3!, 262–271.
Jaselskis, E. J., Anderson, S. D., and Jeffrey, S. R.~1996!.
“Strategies fo
Achieving Excellence in Construction Safety Performance.”J.
Constr
Eng. Manage., 122~1!, 61–70.

Levitt, R. ~1975!. “The effect of top management on safety in
const
tion.” Technical Report No. 196, The Construction Institute,
Stanfo
University, Calif.
Levitt, R. E., and Samelson, N. M.~1987!. Construction safety
manag
ment, McGraw-Hill, New York.
Liska, R. W., Goodle, D., and Sen, R.~1993!. “Zero accident
techniques
Source Document 86, Construction Industry Institute, Austin,
Texa
McClay, R. E.~1989!. “Toward a more universal model of loss
incid
causation.” Professional Safety, January, 15–20.
Mitropoulos, P., Howell, G. A., and Reiser, P.~2003!. “Workers
at the
Edge: Hazard Recognition and Action.”Proc., 11th Annual
Confe
ence on Lean Construction, IGLC, June 22–24, Blacksburg, Va.
Mohamed, S.~2002!. “Safety climate in construction site
environmen
J. Constr. Eng. Manage., 128~5!, 375–384.
Molenaar, K., Brown, H., Caile, S., and Smith, R.~2002!.
“Corporate
culture: A study of firms with outstanding construction safety.”
P
fessional Safety, July, 18–27.
Per Bak. ~1996!. “How nature works—The science of self-

organi
criticality.” Springer, New York.
Petersen, D.~1971!. Techniques of safety management.
McGraw-Hill,
New York.
Prichard, R.~2002!. “Debunking the 13 myths of construction
safe
International Risk Management Institute, May,
http://www.irmi.c
expert/articles/prichard010.asp
Rasmussen, J.~1990!. “Human error and the problem of
causality
analysis of accidents.”Philos. Trans. R. Soc. London, Ser. B,
327,
449–462.
© ASCE / JULY 2005
od-
, M.,
nts
Kir-
ent
w
-

trol
al
.
in a
on
-
Rasmussen, J.~1997!. “Risk management in a dynamic society:
A m
eling problem.”Safety Sci., 27~2/3!, 183–213.
Rasmussen, J., Pesdersen, O. M., Mancini, G., Carnino, A.,
Griffon
and Gagnolet, P.~1981!. “Classification system for reporting
eve
involving human malfunction.” Riso-M–2240, as referenced in
wan, B. ~1994!. A Guide to Practical Human Reliability
Assessm,
Burgess Science, Basingstoke, U.K.
Rasmussen, J., Pejtersen, A. M., and Goodstein, L. P.~1994!.
Cognitive
system engineering, Wiley, New York.
Reason, J. T.~1990!. Human error, Cambridge University Press,
Ne
York.
Rigby, L. ~1970!. “The nature of human error.”Annual
Technical Con
ference Transactions of the American Society for Quality Con,
475–566.

Sterman, J.~2000!. Business Dynamics, McGraw-Hill, New
York.
Suraji, A., Duff, A. R., and Peckitt, S. J.~2001!. “Development
of caus
model of construction accident causation.”J. Constr. Eng.
Manage,
127~4!, 337–344.
Thomassen, M. A., Sander, D., Barnes, K. A., and Nielsen,
A.~2003!.
“Experience and Results from Implementing Lean Construction
Large Danish Contracting Firm.”Proc., 11th Annual Conference
Lean Construction, July 22–24, Blacksburg, Va, 644–655.
Toole, M. ~2002!. “Construction site safety roles.”J. Constr.
Eng. Man
age., 128~3!, 203–210.
2005 / 825
Industrial Applications of Accident Causation
Management System
HYUCKMYUN KWON AND HYUNGJOON YOON
Center for Chemical Plants Safety, Korea Occupational Safety
and Health Agency, Inchon, South Korea
IL MOON

Department of Chemical Engineering, Yonsei University,
Seoul, South Korea
kACMS (KOSHA Accident Causation Management System) has
been developed
to control human errors in Korean chemical industries. kACMS
is a safety manage-
ment system using the Korean GFT (general failure type)
methodology, which has
been found a good approach to eliminating, or at least
minimizing human errors. To
observe the trend of human errors in the chemical industry,
about 5500 near-miss
cases have been collected from a Korean chemical plant. The
analysis of the col-
lected cases shows that the removal of human errors is the key
to preventing these
near-miss cases that have the potential to lead to actual
accidents.
A Korean petrochemical company applied kACMS in its 9
chemical plants.
Fifty-five employees participated in the survey and 12,000
safety data were collected
based on a questionnaire. As a result of each survey, the
average, best, and worst
scores were 85.0, 90.6, and 79.6, respectively. These results led
to a thorough inves-
tigation of the safety systems of the worst scored plant and
directions for improving
safety.
Keywords Human error; Near miss; Korean GFT; kACMS; Risk
causation
Background

Hundreds of thousands of incidents in chemical industries occur
every year all over
the world, often incurring devastating human and economic
costs (U.S. Chemical
Safety and Hazard Investigation Board, 1999). The effects are
indiscriminate. Until
now, with few exceptions, chemical incidents have gone largely
unnoticed, perhaps
due to the lack of definitive shared knowledge of previous
analysis of chemical acci-
dents in different countries. Theoretical models have evolved
from investigations
into the ‘‘why’’ and ‘‘how’’ of case histories. These insights, so
gained, have made
possible better explanations of incident causation. According to
the incident prone-
ness theory, incidents are a result of individual differences
(International Labour
Office, 1998).
Address correspondence to Il Moon, Center for Chemical Plants
Safety, Korea Occu-
pational Safety and Health Agency, 34-9 Kusan-dong Bupyung-
gu, Inchon 403-120, South
Korea. E-mail: [email protected]
Chem. Eng. Comm., 193:1024–1037, 2006
Copyright # Taylor & Francis Group, LLC
ISSN: 0098-6445 print/1563-5201 online
DOI: 10.1080/00986440500352089
1024
A classical example is H. W. Heinrich’s theory of causation,

which has signifi-
cantly influenced practical investigation of process safety
incidents (Heinrich,
1980). Currently, the most widely accepted and adopted theories
rely on the system
theory. According to this theory, an incident is regarded as an
abnormal effect of the
technological or management system.
A fundamental principle in modern incident investigation is to
look for the
underlying causes behind an incident. Furthermore, one axiom
of systematic incident
investigation is that human factors play an important role in
incident causation
(Peterson, 1984). Human error is the most common cause,
accounting for at least
90% of all industrial accidents (U.K. Health and Safety
Executive, 1991).
While purely technical errors and=or uncontrollable physical
circumstances may
also contribute to accident causation, human error is the largest
source of failures.
The increased sophistication and reliability of machinery means
that the relative pro-
portion of accident causes attributed to human error increases as
the actual fre-
quency of accidents decreases. Changes and new technologies
always introduce
hazards as well as benefits. Computers are no exception. Many
computer experts
find it hard to write in a language that can be readily understood
by the operating
staff. As far as computer controls are concerned, the errors are
most often human

failures such as a failure to foresee or allow for faulty
equipment or software bugs,
failure in understanding what the system could and could not
do, or failure to realize
how people respond to displays. As we shall see, certain
characteristics of computer-
controlled systems tend to induce human errors (Center for
Chemical Process Safety,
1993a, 1998). INPO (Institute of Nuclear Power Operation)
made a significant
announcement that ‘‘till now, statistically, cause factors and
situation factors when
nuclear power station accidents happened, they are similar to
those of near-miss inci-
dents relatively to the comparison of the two factors [INPO-84-
027]’’ (Genizzi,
1998). There is no difference between the cause of actual
accidents and the cause
of near-miss incidents (Yoon et al., 1999a).
Fifty-five hundred pieces of accident data have been collected
from a petro-
chemical plant and analyzed by ySIMS (Yonsei Safety
Information Management
System) (Yoon et al., 2000). The survey indicated that human
factors in general
are the major contributors to near-miss incidents. In response to
a request for an
efficient and forceful method of human factor analysis kACMS
(Korean Occu-
pational Safety and Health Agency Accident Causation
Management System) was
developed to reduce and eliminate human error and ultimately
near-miss incidents.
Methods of Human Factor Analysis

The development of kACMS includes various analytical
methods for predicting and
reducing human errors. They are classified in the following four
groups.
. Techniques for the acquisition of information about the
worker’s actions and the
chain of events in an accident
i) DTE (discussions and interviews with experts) technique: The
analysis of com-
plex tasks is usually best done in collaboration with a task
expert (Bainbridge,
1987). They are useful in checking the accuracy of the
information that has
been collected (Bainbridge, 1974).
Accident Causation Management System 1025
ii) CI (critical incident) technique: This technique is used to
collect data about
near-miss incidents and critical events that were experienced by
the operating
team (Flanagan, 1954).
iii) AA (activity analysis) technique: Data about the plans and
routines that are
used by workers in controlling a process are obtained by means
of an activity
analysis, a type of input and output analysis (Crossman et al.,
1974).
. Various task analysis techniques

i) HTA (hierarchical task analysis) technique: A systematic
method of describing
how the job process is organized to suit the overall objective of
the job
(Shepherd, 1985).
ii) OAET (operator action event trees): Tree-like diagrams that
represent the
sequence of various decisions and actions that the operating
team is expected
to perform when confronted with a particular event (Kirwan and
Ainsworth,
1993).
iii) OSD (operational sequence diagram): Flow-charting
techniques that represent
any sequence of control movements and activities concerning
information collec-
tion that are executed in order to perform a particular task
(Kirwan et al., 1988).
. Approaches to quantification
i) THERP (technique for human error rate prediction): Identical
to the aforemen-
tioned event tree method (Swain and Guttmann, 1983).
ii) SLIM (success likelihood index method): The chemical,
transportation, and
various other industries utilize this technique. Tasks within the
SLIM technique
are numerically rated on the influence and the probability of
error, these rat-
ings being combined for each task to give an index called the
SLI (success like-

lihood index) (Embrey, 1986; Kirwan, 1990).
iii) IDA (influence diagram approach): A technique used to
evaluate human error
probabilities as a function of the complex network of
organizational influences,
among others, that have an impact upon these probabilities
(Embrey, 1992).
. Various checklists of factors that can influence human
reliability: It is important
to identify the human component using the general failure type
(GFT) analysis for
effective safety management systems and risk identification
programs, wherein
various checklists are used to identify general failures
potentially hidden in the
working procedure, design, facilities, etc. (International Labour
Office, 1998).
i) PIFs (performance influencing factors): PIFs are defined as
the factors that
determine the likelihood of error or effectiveness in human
performance. PIFs,
such as quality of procedures, level of time stress, and
effectiveness of training,
will vary on a range from the best practicable to the worst
possible (Center for
Chemical Process Safety, 1994). General failure type used in
kACMS has a
similarity to this method.
ii) MORT (management oversight and risk tree analysis): A
logic tree that assist
in providing analysts with a disciplined method for accident
investigation, use-

ful in safety program evaluation and applied to operational
readiness reviews.
MORT is a useful aid to the previously mentioned checklist type
of analysis
techniques that assists the analysts in visualizing the needed
hardware and
work procedures to match personnel capabilities at all levels of
the organiza-
tional hierarchy (Gertman and Blackman, 1994).
1026 H. Kwon et al.
iii) Contextual Level Classification: Many miscommunications
and pen taxo-
nomies are constructed at this level and include references to
contextual trigger-
ing features such as anticipation and preservations. Such
categorizations are
valued since they help in focusing attention on the complex
interaction between
local triggering factors and the underlying error tendencies
(Reason, 1998).
Formulation of General Failure Type
After years of experience in improving safety techniques and
process design, many
organizations discover that accident rates, processing plant
losses, and profitability
reache a plateau beyond which further improvement is
impossible to achieve (Center
for Chemical Process Safety, 1993b). Another discovery is that
even in organizations
with generally good safety records, occasional large-scale

disasters occur, which
invariably shake the public’s confidence in the chemical
processing industry.
The common factor in both discoveries is human error. Errors
are viewed as the
natural outgrowth of unfavorable combinations of people and
the working situa-
tions. Simply put, an error is a human output outside the
tolerances established
by the system requirements where the person operates (Process
Safety Institute,
2000).
Human errors represent a major target in prevention and are
becoming more
important (Center for Chemical Process Safety, 1995). A
rigorous analysis of human
errors shows that they might be relative to the human
management system (Stellman,
1984; Goh et al., 1998). So a more effective safety management
system has to be
applied to manage operators systematically and to identify
causes of human errors
efficiently. In order to get more insight into the controllable
parts of the accident
causation process, an understanding of the possible feedback
loop in a safety control
system is necessary. Figure 1 shows the component structure of
a safety control sys-
tem that can form the basis of managerial control of human
error.
The GFT (general failure type) of Gop Groeneweg’s accident
causation model
was used when we designed the safety control and risk

management systems that
concern human errors (International Labour Office, 1998).
kACMS can report the
weak points of the management of a company by collecting,
classifying, and analyz-
ing data based on GFT. GFT is defined as the factors that cause
substandard acts
and situations in the generating mechanism of an accident. GFT
was modified to
adapt it to petrochemical plants by including new classifications
of 11 fields by risk
causation, as shown in Table I (Yoon et al., 1999b). The 11 risk
causation fields
reported are major areas that may be greatly influenced by
human factors in terms
of implementing safety management. The 11 types of GFT
consist of hardware,
training, incompatible goals, and eight others. Each type of GFT
contains 20 related
questions and answers to investigate working conditions of
people involved. Refer to
Table II for GFT sample questions; the appendix also gives
examples of 20 related
questions for a single GFT sample question.
These questionnaire sheets are distributed to the employees to
let them diagnose
the status of their safety level. The final 20 questions were
prepared by processing
several steps in order to check the reliability of the questions.
In the Center for
Chemical Plant Safety of the Korean Occupational Safety and
Health Agency, 12
executive engineers are working towards the implementation of
the PSM (process
safety management system) in Korea. Each engineer, who has an

average of 15 years
experience in different backgrounds, such as plant design,
operation, instrumentation,
electronics, hazard analysis, fire fighting, piping, and material
selection, and also
possesses a professional engineer certificate in his own field,
proposed for the ideas
in preparation of the questions (20 questions�11 types).
When the engineers prepared the draft questions, their main
considerations were
the following classifications of human error:
. Errors due to a slip or a momentary lapse of attention: the
intention is correct but
the wrong action is taken.
. Errors due to poor training or instructions: someone does not
know the correct
procedures or worse, thinks he knows but does not. Some
analysts note these mis-
takes to emphasize that the intention was wrong.
. Errors due to a lack of physical or mental ability; thus, the
abilities of the person
and the situation match poorly.
. Errors due to a lack of motivation or a deliberate decision not
to follow instruc-
tions or expectations.

. Errors made by managers, often due to a lack of
comprehension of the part they
should play.
From a certain perspective, almost all accidents are due to
management errors. If the
management had ensured that the plant was better designed, the
training and
Figure 1. Flow of safety control system (Reason et al., 1998).
1028 H. Kwon et al.
instructions were better implemented, or previous violations
were addressed, most
likely the accident would not have occurred (Keltz, 1991).
Through several meetings, a tentative list of 220 of the most
appropriate ques-
tions were selected. After that the questionnaire sheets were
circulated to 20 chemical
companies to check the reliability of the questions. KOSHA
updated the list of ques-
tions by making amendments based on the comments from
industry. About 15% out
of the total questions were revised through this process. Then
the final questionnaire
sheets were distributed within the industry. We collected the
answer sheet and ana-
lyzed the data using a computer program. The program, which
uses Excel, is com-
posed of an input file, a table of correct answers, and a result
file. The table of
correct answers contains the predefined answer to each question

as Yes or No.
The answers from the industry were classified into a relative
risk level with scores
from 0 to 100, where 0 signifies highly dangerous and 100
means perfectly safe.
By analyzing the score of each person, each department, and
each GFT, the weak
areas of each plant can be identified and this result will be used
to guide safety
enhancements. The weak points in the company’s management
will be reported to
Table I. Definition of Korean GFT
Type of GFT Definition
Design (DE) Failures due to poor design of a whole plant as
well as individual items of equipment
Hardware (HW) Failures due to poor state or unavailability of
equipment and tools
Procedures (PR) Failures due to poor quality of the operating
procedures with respect to utility, availability,
and comprehensiveness
Error enforcing conditions (EC) Failures due to poor quality of
the working
environment, with respect to circumstances
that increase the probability of mistakes
Housekeeping (HK) Failures due to poor housekeeping
Training (TR) Failures due to poor or inadequate training
or insufficient experience
Incompatible goals (IG) Failure due to the poor way safety and

internal
welfare are defended against a variety of
other goals like time pressure and a
limited budget
Communication (CO) Failure due to poor quality or absence of
lines
of communication between the various
divisions, departments, or employees
Organization (OR) Failure due to the way the project is
managed
and the company is operated
Defenses (DF) Failures due to the poor quality of the
protection against hazardous situations
Maintenance management (MM) Failure due to poor quality of
the maintenance
procedures regarding quality, utility,
availability, and comprehensiveness
the managers to serve as a guideline for further actions to be
taken and new invest-
ments to make to eliminate safety hazards.
Case Study: Administration of GFT in a Company
After finalizing the question and answer sheets, we applied
them to a chemical com-
pany that has nine operating units such as styrene monomer, and

tere-phthalic acid
plants.
The surveying information is as follows:
. Period: September 1998–February 1999
. Surveying target: A large Korean chemical company
. Number of employees requested to answer: 62
. Number of employees who answered: 55 (percentage of reply:
88%)
. Number of items in the analysis: 12,100 items (55
employees�11 GFT�20
questions=GFT)
Table II. Examples of questions for each type of GFT
Type of GFT Sample questions for each type
Design (DE) Have you ever participated in risk assessment
of relevant equipment when modifying or
installing equipment?
Hardware (HW) Have you ever stop production work due to
mechanical problem during the past
four weeks?
Procedures (PR) Have you ever found anything wrong in
operation procedures?
Error enforcing conditions (EC) Have you ever not used PPE
that is provided
when you handle hazardous material

because of its discomfort?
Housekeeping (HK) Are drains or water pipes well maintained
in
the workplace?
Training (TR) Have you ever felt that your trainer is
incapable of training?
Incompatible goals (IG) Have you ever received any order from
your
manager to shorten your production time
that might cause your plant operation
unsafe?
Communication (CO) Has every result from a recent safety
meeting been reported to a manager in
your department?
Organization (OR) Do you know the reporting procedures when
any accident occurs?
Defenses (DF) Do you know your duty and action in
an emergency?
Maintenance management (MM) When you conduct maintenance
work do
you start your work after consulting a
permit-to-work sheet?
1030 H. Kwon et al.
The answers from nine operating units were classified into
relative risk levels as

scores of 0 to 100, where 0 signifies highly dangerous and 100
signifies no hazard
present, based on the probability of the answers. The analysis
results are shown in
Figures 2 and 3, and Tables III and IV. The abscissa of Figure 2
is the probability
Figure 2. Results of analysis on GFT (company level).
Figure 3. Result of analysis on accident causation model
(company level).
T
a
b
le
II
I.
A
n
a
ly
si
s
su
m

m
a
ry
o
f
a
cc
id
en
t
ca
u
sa
ti
o
n
m
o
d
el
(c
o
m
p

a
n
y
le
v
el
) G
F
T
P
ro
ce
ss
(D
ep
t.
)
D
E
H
W
P
R

E
C
H
K
T
R
IG
C
O
O
R
D
F
M
M
A
v
er
a
g
e
S
D
a

A
7
5
7
9
9
3
8
5
9
0
8
4
7
9
8
7
7
4
9
5
9
3
8

4
.9
1
2
.3
4
B
8
4
8
2
9
8
9
3
9
2
9
3
8
9
8
8
8

3
9
8
9
6
9
0
.5
5
1
.7
5
C
7
3
6
3
8
4
8
6
8
7
8

4
8
4
9
0
6
9
8
5
9
3
8
1
.6
4
2
.7
9
D
8
1
7
5
9

1
8
5
8
7
8
3
7
6
8
6
7
0
9
7
9
1
8
3
.8
2
2
.4
0

E
6
8
8
7
9
3
7
8
8
8
8
1
8
6
8
4
7
2
9
7
8
9
8

3
.9
1
2
.6
1
F
7
6
8
0
8
9
8
5
9
4
7
9
8
6
9
3
7

4
9
5
9
2
8
5
.7
3
2
.2
7
G
8
3
8
8
9
6
9
6
9
1
9

0
9
1
8
8
6
9
9
9
9
3
8
9
.4
5
2
.4
5
H
7
1
8
0
9

7
8
6
9
0
7
6
6
7
9
0
8
4
9
5
1
0
0
8
5
.0
9
3
.2

3
I
6
8
6
9
9
7
7
0
8
8
7
8
6
4
8
0
7
5
9
5
9
4

7
9
.8
2
3
.6
0
A
v
er
a
g
e
7
5
.4
4
7
8
.1
1
9
3
.1

1
8
4
.8
9
8
9
.6
7
8
3
.1
1
8
0
.2
2
8
7
.3
3
7
4
.4

4
9
5
.1
1
9
3
.4
4
S
D
a
2
.0
4
2
.6
9
1
.5
3
2
.5
4

0
.8
1
2
.2
1
3
.1
9
1
.2
9
1
.8
6
1
.3
6
1
.0
5
a
S
ta

n
d
a
rd
d
ev
ia
ti
o
n
.
T
a
b
le
IV
.
L
ev
el
s
o
f
re

sp
o
n
d
er
s
(P
ro
ce
ss
‘‘
I’
’)
R
es
p
o
n
d
er
em
p
lo
y

ee
P
a
W
Y
b
C
S
c
D
E
H
W
P
R
E
C
H
K
T
R
IG
C
O

O
R
D
F
M
M
E
m
p
l.
1
I
2
1
1
0
0
7
9
7
3
9
5
8

3
8
2
8
9
8
1
8
9
0
1
0
0
8
8
E
m
p
l.
2
I
4
1
1

0
0
5
0
6
7
9
3
6
2
1
0
0
6
7
6
0
7
8
5
0
1
0
0

1
0
0
E
m
p
l.
3
I
3
1
1
0
0
6
5
7
4
1
0
0
7
6
8

8
9
3
7
0
8
3
8
2
8
8
8
6
E
m
p
l.
4
I
8
1
1
0
0

6
5
7
1
9
4
4
1
6
9
6
0
5
0
7
8
6
7
9
5
9
2
E
m

p
l.
5
I
8
1
1
0
0
7
4
5
7
1
0
0
8
4
1
0
0
7
5
5

6
7
0
8
8
8
9
1
0
0
A
v
er
a
g
e
6
6
6
8
9
6
6
9

8
8
7
7
6
3
8
0
5
7
9
5
9
3
a
P
ro
ce
ss
.
b
W
o
rk

in
g
y
ea
rs
.
c
C
o
m
p
a
n
y
si
ze
.
1032
of the score and the ordinate is different types of processes such
as naptha craking
center (NCC), poly propylene (PP), linear density polyethylene
(LDPE), purified
tere-phthalic acid (PTA), etc. The process exposed to the most

incident conditions
was ‘‘I’’ with a score of 79.82, the safest process was ‘‘B’’
with a score of 90.55,
and the average score was 84.99. Table III represents the score
of 11 GFTs for each
process in abscissa, by which the safety manager can search and
analyze the weak
and strong points of each process from the management’s point
of view. ‘‘B’’ has
higher scores than average for all 11 types, but ‘‘I’’ has lower
scores than average
for almost every type. Figure 3 displays the same data in Table
III graphically in
order to help managers understand the trend of the GFT scores
more easily.
For the lowest scored processes, ‘‘I,’’ in Table III, it is
recommended that more
detailed analysis should follow and immediate remedial action
be requested.
Table IV represents the 11 GFT scores rated by each employee
for process ‘‘I.’’
As the score for design, hardware, error enforcing conditions,
incompatible goals,
and organization are found to be very low, being 66, 68, 69, 63,
and 57 respectively,
safety personnel should primarily concentrate their efforts on
these areas. The atten-
tion of special task management ought to be given for the
organization areas with a
57 GFT score. If data represented in Table IV are not sufficient,
the safety manager
must review the questionnaire records and find the root causes
that result in such low
scores.

Through the review of this analysis, the weak areas of each unit
were identified
and this result was used as a guide to safety enhancements. The
weak points in the
company’s management were reported to the managers to serve
as a guideline for
further actions to be taken and new investments to make to
eliminate safety hazards.
The risk level of each department and unit was also analyzed
based on 12,100
items (11 GFT�20 sub-items). kACMS managed the survey
efficiently and system-
atically using the new questions and classifications.
Table V gives the results of the two-way analysis, which
clarifies the score vari-
ation shown in Table III. The two-way analysis of variance was
performed to deter-
mine the effects of the chemical process and GFT, which are
two nonmetric
independent variables, on the score, which is a single-metric
dependent variable.
The analysis gave statistically significant results (F value ¼
12.0771, P ¼ 0.0001).
In the analysis of the primary effect of the independent
variables, the first inde-
pendent variable, process, showed a statistically significant
difference (F value ¼
4.7268, P ¼ 0.0001), indicating that the averages of the first
dependent variables
for the nine process groups were different. The second
independent variable, GFT,
also made a statistically significant difference (F value ¼
17.9573, P ¼ 0.0001),

Table V. Two-way analysis of score variance by chemical
process and GFT
Source of variation Sum of squares DFa Mean square F value
Prob. > F
Main effects 5840.1414 18 324.4523 12.0771 0.0001
Process 1015.8990 8 126.9874 4.7268 0.0001
GFT 4824.2424 10 482.4242 17.9573 0.0001
Error 2149.2121 80 26.8652 — —
Total 7989.3535 98 — — —
aDegree of freedom.
representing that the averages of the second dependent variables
for the 11 GFT
groups were diverse.
To conclude, the dependent variable, score, which is calculated
by each inde-
pendent variable, showed statistically significant differences.
Conclusion
Human error is probably the most significant contributor to loss
of life, personal
injury, and property damage in the chemical industry. We
developed a safety man-
agement system called kACMS by using a Korean GFT to
examine the role of

Case Study1. Review the information in your textbook ( Leveson,.docx

Case Study1. Review the information in your textbook ( Leveson,.docx

Recommended

Recommended

More Related Content

Similar to Case Study1. Review the information in your textbook ( Leveson,.docx

Similar to Case Study1. Review the information in your textbook ( Leveson,.docx (20)

More from wendolynhalbert

More from wendolynhalbert (20)

Recently uploaded

Recently uploaded (20)

Case Study1. Review the information in your textbook ( Leveson,.docx