4. Describe a condition index (CI) for an infrastructure system you would create
ID: 419533 • Letter: 4
Question
4. Describe a condition index (CI) for an infrastructure system you would create. You will need to note a series of factors that are related to level of service, condition, how well the asset functions, etc. Explain how your CI works, and why it accurately represents the condition of the asset. You may need to create weights for same as appropriate. Then apply it to 10 different assets, of different types. You will need to acquire photos etc. for the same. Project data is preferred. Try actually applying the CI to the chosen assets. Feel free to include more than 10. Does your CI concept work? (10 points)
Explanation / Answer
Recent requirements in component management of building systems have focused on the requirement for improving methods and metric tools to support component condition assessment and appropriate decisions for infrastructure owned facilities. Although engineers and researchers have focused on developing methodologies for component assessment in recent years but there is not enough attention dedicate to facilities and components that have been constructed. This paper is a literature study of scientific papers within the topic of component condition index system (CCIS) in the period 1976 to 2009. Infrastructure component condition index had existed for some 40 years. The purpose of this paper is to provide an overview of CCIS to identify the suitable method for component condition assessment during its service life. This paper finds that the focus of CCIS, surveyed in several aspects during the 40 years that have been investigated, from technology to measurement and from assessment function to component maintenance as an integrated part of the infrastructure component management. This study offers help to researchers in understanding the selection of an appropriate method for component condition assessment in building and non-building systems.
The CCAS infrastructure system is a procedure of a systematic measurement
of an organization’s found assets that includes project repair, replacement, or renewal
required which protects their capability to support the task or activities that they are
allocated to function (Rugless 1993). CCAS infrastructure system is the most
important work in the inventory management process as this method is the base or the
first step for other tasks such as the decisions to time of repair or replacement. This
paper reviews much of the literature on CCAS infrastructure systems. The literature
is collected from major books, journals, technical reports and conference
proceedings, the period covered is from 1975 to 2009. This paper shows a
comprehensive review of various areas that are related to the condition assessment
system, comprising evaluation mechanisms and comparison in selecting the suitable
method for assessing component, and condition index analysis.
IMPORTANCE OF THE STUDY
The CCAS infrastructure systems have been used in western countries (USA,
Canada et al.) some 35 years and are today a natural tool for many components
assessment activities. In what way has component condition assessment system
(CCAS) made advances during the 35 years of existence? This question will be
investigated using literature as a basis. After reviewing literature about CCAS several
times the author has not yet found a literature study describing the development of
CCAS. To fill this gap, this paper presents a literature review over the topic of CCAS
focusing on the development of the concept specifically, and in comparison with the
development of corporate CI in general. CCAS provides to measure the overall health
of the components and facilities and correlate to maintenance and repair requirements
and needed budget levels (Shahin et al. 1977). This procedure and prediction of the
component future is costly and currently is lack of support and systematic techniques.
Existing systems do not provide sufficient guidance for the execution of accurate
assessment for component condition. To meet the challenge of the maintenance needs
of a building component; installation engineers and facilities managers will need to
know the suitable method of building component assessment.
OVERVIEW
The literature pertaining to CCAS infrastructure system is classified into three
sections namely: (1) Historical perspective of CCAS; (2) Assessment of CCAS
methods; and (3) Analysis, results, and suggestion for CCAS.
Historical perspective of CCAS
In any system, the values of the condition scales support the methods of
comparing the condition of different components. The condition index scale for
building components is commonly from 0 to 100 and A to D where 0 or D represents
a critical (failure) condition and 100 or A presents a new condition or excellent. A
condition scale presentation can be obtained from the numeric or lexical values.
The concept of the condition of building component using an index
correlation condition rating is based on rating scale theory (Uzarski and Burley
1997). These indices provide a suitable assessment for showing present condition,
survey of rates of deterioration, comparing condition between different
subcomponents, components, systems, and buildings, and condition prediction about
each of components. CCAS presents a method for measuring rates of deterioration
and prediction of condition for each component or material. The condition index is
used to historically map the component condition over time to determine the rates of
degradation.
Since the 1980, condition assessment methods of infrastructure systems have
been developed solely for individual kinds of infrastructure system assets. For
instance, the association of Higher Education Facilities Officer (Kaiser 1993),
PAVER was developed for pavement management (Shahin 1992), BRIDGER for
bridges (Lee 1997, Thompson and Harrison 1993) DAMMER for dams (Greimann et
al. 1997), BUILDER for building management (Uzarski and Burley 1997, Elhakeem
2005, ADOE 1997) ROADER for highway and road management (WSDOT 2000),
TOBUS (2002), NCES (2003) and DfES (2003) are supplement recently developed
condition assessment tools for school buildings. Other researchers have done in this
field include the roofing membrane condition index (MCI), and the roofing flashing
condition index (FCI) (Shahin et al. 1987), condition indices for clay brick masonry
walls (Weightman 1994), and concrete masonry walls (Wittleder 1994). Also in the
past few years, USACERL has developed a number of condition indices for various
types of components and facilities include the roof condition index (RCI) for built-up
roofs (Shahin et al. 1987), the corrosion status index (CSI) of certain piping systems
(Kumar et al. 1986), and railroad track Structure condition index (Uzarski 1993). In
additional, this research institute developed a family of condition index for various
kinds of civil tasks structures (Koehn and Kao 1986).
Assessment of CCAS methods
This section focuses on the condition assessment methods, and provides a
discussion on the specific rating scale used in the component condition development.
USACERL (1990) has been developed by the U.S. Army crops engineers at the
engineering research and development center. Construction Engineering Research
Laboratories (CERL) in plain. USACERL condition index method is condition-based
with functions which comprise an asset of major building components; condition
indices; condition prediction skill; and comprehensive condition description for each
CI value (BUILDER 2008). USACERL (1990) was designed to support a purpose
and quantitative means for component condition assessment while supporting a
common language and explanation among estimators and assessors. The scale used in
all of the USACERL indices ranges from 0 to 100 and is divided into seven condition
categories. USACERL’s condition category includes (0-10)=failed, (10-25)=very
poor, (25-40)=poor, (40-55)=fair, (55-70)=good, (70-85)=very good, and (85-
100)=excellent (Uzarski 1990, Grussing 2009). PONTIS has developed a method for
assessing bridge facilities. This model provides the degree and state of physical
degradation and the action necessary for components in field bridges. The PONTIS’s
method was designed to support component condition assessment by assessors for
accurate identification of component condition during service life. This method is
divided into five condition categories from 1 to 5. This classification is based on
deterioration process. PONTIS’s condition category includes 1=protected,
2=exposed, 3=vulnerable, 4=attacked, and 5=damaged (Thompson and Harrison
1993). Lee (1997) have developed a condition scale for facilities of bridges. Lee’s
condition scale was designed to provide component condition assessment with a
common language among users. This condition scale includes condition indices and
condition prediction capabilities. The scale is used in all of the components and
facilities of bridges ranges from 1to 4 and is divided into four condition categories.
Lee’s condition category includes 1=no, 2=slight, 3=moderate, and 4=severe.
Greimann (1997) has developed a condition scale for assessing infrastructure system
components including locks and dams. Its condition assessment provides the degree
and extent of physical deterioration and the action that is essential to renew dams and
locks facilities. The Greimann condition scale was designed to provide an accurate
assessment of facilities condition in field dams and locks. The scale has been divided
into three condition categories. These ranges are from 0 to 100. The condition scale
has been designed based on maintenance needs. Greimann’s condition category
includes (0-39)=only after further investigation, (40-69)=only if economically
feasible, and (70-100)=no action is required. ADOE (1997) has developed a condition
scale method for assessing education facilities condition. This department (Alaska
Department of Education) supports engineers, assessors, and component managers
with a tool that supports decisions related to when, and where for best to maintain
schools buildings and their key components. ADOE condition indices were designed
to provide a purpose for component condition assessment with common language.
The scale used in all of ADOE index scales from 1 to 4 and is divided into four
condition categories. ADOE’s condition category includes 1=good, 2=fair, 3=poor,
and 4=unsatisfactory. WSDOT (2000) has been developed by Washington State
Department of Transportation. This department is responsible in constructing,
maintaining, and performing the state highway system. WSDOT condition scale has
been developed to support data collection and presentation for assessing component
condition within road, railroads, and airports. The WSDOT condition scales were
designed based on three condition categories from 1 to 4. WSDOT’s condition
category includes 1-2=meets current standards, 3-4=adequate, 4-5=poor. TOBUS
(2002) is the most recent framework developed by the European Commission in the
JOULE II program. Its condition assessment provides the scale and extent of physical
deterioration and the action essential to renew office buildings (Brandt and
Rasmussen 2002). The TOBUS condition indices were divided into four condition
categories from A to D. TOBUS’s condition category includes A=good, B=some,
C=Mean, and D=repair immediate (Caccavelli and Gugerli 2002). DFES (2003) has
developed condition index model for survey building condition. DFES (Department
for Education Schools) performs building condition assessment in schools and other
local authority buildings. This institute has a good practice guide for local authority
assessment management plan condition assessments. The DFES condition indices
were designed based on condition category for assessing component condition related
to schools. The condition scales were divided into four condition categories from (A-
D). DFES’s condition category includes grade A=good, grade B=satisfactory, grade
C=poor, and grade d=bad. NCES (2003) was developed by National Center for
Education Statistics – facilities information management. This institute is the primary
federal entity for gathering, analyzing, and presenting data related to education
facilities in the United States and nations. NCES is assessment-based with functions
that include assets of major building components and condition index. It has been
used widely for school boards. The NCES condition scales were designed based on
condition category. These categories include eight condition categories form 1 to 8.
NCES’s condition category includes 1=excellent, 2=good, 3=adequate, 4=fair,
5=poor, 6=non operable, 7=urgent building condition, 8=emergency condition.
Elhakeem and Hegazy (2005) have developed a condition scale guide for assessing
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school components. Elhakeem’s condition scale has been divided into five condition
categories from 0 to 100. This scale is used for different facilities and component in
field school buildings. Elhakeem’s condition category includes (0-20)=no, (20-
40)=slight, (40-60)=moderate, (60-80)=severe, and (80-100)=critical.
Analysis, results, and suggestion for CCAS
The use of numeric rating has been used by TOBS (2002), DFES (2003),
PONTIS (1993), Greimann (1997), ADOE (1997), WSDOT (2000), Elhakeem
(2005), Lee (1997), and NCES (2003) for assessing various infrastructure condition
systems with regards to mission readiness. These ratings embody subjective opinion.
Since they represent broad condition of the category ranges, minor or moderate
change in condition cannot be ascertained. Therefore, these methods are wholly
inadequate for building component assessment and these indices are not applicable or
useful for accurate prediction of component condition.
Most important issue for component condition assessment is an integrated
system and a comprehensive guide for users (engineers, assessors, inspectors, etc).
Users can estimate, assess, or predict component condition based on existing indices
and condition description related to each scale. Also, a condition scale should have
extendable indices for assessing components with high lifespan such as pipe or roof.
Thus, those indicators are standard where their scales have amplitude in each value.
For instance, methods of USACERL (1990), Greimann (1997), and Elhakeem (2005)
have scales with amplitude in each value ((0-20), (20-40), …, etc) but other methods
don’t have this amplitude in each index value. This system is used for more accurate
assessment of component condition and more obvious simulation results.
The condition index (CI) should provide a way of communicating the
suitability of the component to provide requirement service in support of its specific
task (Grussing et al. 2009). The condition category should provide a general
classification of facility functional deficiencies. However, the conditions within each
category must provide the depth and detail needed to suitability and objectively
evaluation functionality loss. Each condition uniquely exhibits a facility-related
problem that can be addressed by an actionable corrective process. Each condition
category has a specific definition and visual or technical criteria that must exist. This
definition and criteria provide a facility technician or a professional estimating the
facility functionality with a set of instructions for measuring whether a particular
condition is affecting the building facility. According to ADA (Americans and
Disabilities Act), the assessor evaluates a building facility through a simple checklist
and comprehensive guidance. The condition measurement process is a consistent and
repeatable procedure through standardized list of facility condition and the explicitly
stated criteria for each condition (Grussing et al. 2009).
Grussing et al. (2009) invoked a number of assumptions for identification of
the appropriate CI method: (i) CI is a measurable attribute; (ii) assessors are capable
of making quantitative judgment about facility condition (comprehensive condition
description); (iii) the judgment of each assessor can be expressed directly on an
interval scale (amplitude in each index value); and (iv) Each assessor is equally
capable of making the required judgment of condition.
USACERL (1990) has terms required for assessing building component
system. This method has a comprehensive condition description for assessing and
predicting the future of component condition and maintenance time based on
inspectors’ and assessors’ experiences in field component maintenance time during
its service life. USACERL (1976 to 2009) has been used in more than 20 projects for
building and non building projects such as railroad, roof, building exterior, etc. This
method includes seven condition indices categories from 0 to 100 for accurate
prediction of component condition with respect to the guidance table and assessors’
experiences. Also, this condition scale is extendable into more details for component
with high lifespan (more than 30 years). When condition index is divided into more
index amplitude (among 0 to 100) results, it is more obvious and more attractive in
the prediction process of component condition and more accurate simulation of the
component condition prediction. Table 1 shows the analysis and comparison of
various component assessment methods.
CONCLUSION
This paper summarized that the focus of CCAS surveyed in several aspects
during the 40 years that have been investigated; from technology to measurement and
from assessment function to component maintenance as an integrated part of the
infrastructure component management. Advancements in CCAS have in general
followed the development of the future prediction of component and facilities in
infrastructure systems.
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