Download assessing the remaining service life of existing building components

ASSESSING THE REMAINING SERVICE LIFE OF EXISTING BUILDING
COMPONENTS FOR INSURANCE
Insurance of existing building components
P.D. MAYER
Technical Audit Unit, Housing Association Property Mutual, London, United
Kingdom
P. WORNELL
Building Performance Group, London, United Kingdom
Durability of Building Materials and Components 8. (1999) Edited by M.A. Lacasse
and D.J. Vanier. Institute for Research in Construction, Ottawa ON, K1A 0R6,
Canada, pp. 1447-1456.
 National Research Council Canada 1999
Abstract
Housing Association Property Mutual (HAPM) required a methodology to enable the
remaining service life of existing components to be assessed for a new insurance
product. A 35 year structural and non-structural defects cover is provided for existing
housing stock comprising low rise, medium rise and high rise types, of both traditional
and modern construction. A database structure was developed to allow systematic
identification and appraisal of building components. Various service life assessment
methods and models are considered to provide a framework to enhance site inspection
objectivity and quantify future service lives to allocate an insurance life: a) visual
condition assessment, b) modification of a reference service life using factors, c) scales
of component condition, d) rates of deterioration, e) failure patterns, f) probabilistic
models and g) service life forecasting guidance based on ISO/DIS 15686–1. Examples
illustrate how the HAPM service life assessment model works in practice and is
underpinned by theoretical analysis. The information gathering process and appraisal
of service lives using these approaches could benefit by application of an expert
computer system, incorporating fuzzy logic and rule induction software to assess
uncertainty by computer generated rules.
Keywords: component database, component insurance, failure patterns, expert
computer systems, prediction methods, remaining service life, Weibull distribution.
1
Introduction
Housing Association Property Mutual (HAPM) has nearly 10 years experience
insuring new buildings and existing buildings which have been rehabilitated against
the risks of major defects and premature component failure (Holmes and Wornell,
1994). A new insurance product — HAPM Dwellings — has been devised to cater for
large scale transfer of housing stock from Local Authorities to Housing Associations.
Such estate transfers required an insurance methodology which could provide 35 year
structural and non-structural defects cover to existing components.
A methodology for assessing new components and allocating insurance lives has
been established for HAPM’s new build insurance (Bourke, 1996). Construction
Audit Limited is a subsidiary of Building Performance Group (BPG) which provides
the HAPM Technical Audit Unit (TAU). Both BPG and TAU are involved in
component durability research. Their work comes together in publishing the
Component Life Manual (Wornell et al, 1992) where shorter life components are
distinguished and given a specific insurance life based on their predicted service life.
2
Component database structure
HAPM insures housing against inherent defects which result in damage. A claim
is made when a component is damaged i.e. fails. The component database is structured
for the insurance process. It is based on components which encompass components
(e.g. roof tiles), materials (e.g. insitu concrete floors) and assemblies (e.g. balustrades).
Structural and non–structural component distinctions and the consequences of
failure are considered separately within the audit process (Holmes and Wornell, 1994).
2.1
New build component database
The new build insurance system includes a component database modeled on the
Component Life Manual. Other component structures were considered such as the
‘Construction indexing manual’ (CI/SfB, 1991) but found to be inappropriate for the
insurance context. The process of identifying components is hierarchical:
•
•
•
•
Elements: e.g. foundations, flat roofs. In total there are 29 elements.
Component types: the principal components comprising an element. The element
flat roofs includes membrane coverings, decking and structural timbers.
Component sub–types: a division of component types based on materials. Flat
roof membranes include asphalt and double layer bitumen membranes.
Class category: components are ranked by durability. Best quality polymer
based double layer bitumen is allocated a 20 year insurance life, an average
quality glass–fibre based system is insured for 10 years.
2.2
Extension of the new build component database
The scope of the new build component database was found to be insufficient for
stock transfers which include low rise, medium rise and high rise housing types, built
in the 1900s to the present, using both traditional and modern construction methods.
The database was enlarged by addition of some eighty component types with
associated sub–types and classes. At the last count the component database covered
over 400 component types, 1600 component sub–types and 9000 component classes.
2.3
Relationship between predicted service lives and ‘insurance lives’
The insurance lives listed in the HAPM Component Life Manual are cautious
estimates of durability based on predicted service lives which are modified to reflect
the actuarial basis of premature failure. Durability is defined in terms of years a
component is expected to function before failure i.e. a predicted service life (Moss,
1995). Premature failure occurs where a component requires complete replacement or
extensive repairs within the HAPM insurance life i.e. before the predicted service life.
The research to enable precise adjustment of insured lives to provide estimates of
service lives remains to be carried out (Bourke, 1994). Nevertheless, insured lives are
typically targeted to reflect 80% of the predicted service life (Moss, 1995).
3
Auditing: component identification and insurance life allocation
Identification of components within the database requires ‘stepping down’ the
hierarchy of element, component type, component sub–type and component class.
3.1
‘Nominal’ insurance lives at sub–type level
Clearly not all existing components can be identified visually at the most
detailed level, i.e. by component class. An auditor may not be able to determine the
grade of chipboard used for a ground floor decking but should be able to distinguish at
sub–type level between plywood, orientated strand board and softwood boards.
The insurance audit system allows identification of existing components at sub–
type level. To facilitate allocation of an insurance life a ‘nominal’ insurance life is
associated with each component sub–type.
The ‘nominal’ insurance life concept is based on the insurance life of the most
likely class of component used in the type of construction commonly encountered.
3.2
Concealed components
Typically concealed components include foundations, lintels, sleeper walls and
wall ties. Concealed components may be critical when considering the longevity of a
building, hence it is important they are assessed for insurance life allocation.
The auditor may have access to as–built drawings. An estate transfer may
include a pilot scheme providing an opportunity to inspect concealed components.
Thorough inspection of the building should enable assessment of consequential
defects associated with concealed components, for example, cracking of horizontal
mortar courses may indicate wall tie corrosion. In which case further investigation
would be requested. The auditor may go beyond a visual inspection by conducting
wall–tie frequency detection tests at critical points such as gable verges. Detailed
examination with a boroscope of wall cavities or floor voids should provide pointers to
identify and assess the condition of components.
In the case of foundations there may be no circumstantial evidence to identify the
type of construction or material used, the auditor may use a generic sub–type
‘foundations’. Supposition is avoided, if an assumption is made about an existing
component this is recorded in the insurance report.
3.3
Insurance life allocation
New components are automatically allocated the full insurance life associated
with their component class by reference to the Component Life Manual.
Existing components are assigned a condition status based on site inspections.
Component condition guides the allocation of insurance lives (Table 1).
Table 1: Component condition and insurance life allocation
Condition
As new
Part worn
Needs replacement
Concealed
Insurance life
Full insurance life e.g. as component class or ‘nominal’ life.
Less than ‘nominal’ life, in five year bands to a minimum of
5 years.
No insurance life.
A ‘nominal’ life, in five year bands subject to confirmation
of there being no symptoms to indicate failure.
The condition of an existing component provides a guide to the rate of
deterioration previously experienced. The auditor makes an assessment of future
longevity based on: quality of material, design, workmanship, external/internal
environment and usage to assess future service life and then allocate an insurance life.
The process of allocating an insurance life for an existing component is
qualitative yet is based on quantitative models. Theoretical and quantitative models
are established in the literature, however, detailed guidance at component level for the
complete range of components HAPM encounters is not readily available.
4
Models to forecast the remaining service life of components
Seven service life forecasting models or approaches have been identified to
provide a working methodology for insurance purposes. They form a framework to
enhance site inspection objectivity and a strategy to quantify future service lives to
guide allocation of insurance lives.
4.1
Visual condition assessment
This is a qualitative approach; the remaining life of a building component is
assessed by reference to its existing condition. It is a method commonly used for
condition surveys. There are similarities between the processes used for insurance of
existing components and the assessment of components for condition surveys.
Components are considered within a definite time scale, 35 years or less. Time to
replacement, and insurance lives are commonly expressed in five year time bands.
The maintenance regime is defined and accepted as a constant. In the insurance
model a minimum maintenance regime is stipulated as a part of the life assignment.
The sampling strategy underlying condition surveys has application to auditing
large scale stock transfers. The aim is to reduce risk by optimizing the trade off
between sample frequency and accuracy (Mayer et al, 1994). In the insurance model a
representative sample of all the components is inspected. The percentage will depend
on the building type, construction and components encountered.
•
External components: 100% of the exterior of a single block of flats would be
assessed. A transfer of 50 similar two storey dwellings may have a two stage
approach to sampling; the first stage involving an overview to identify and
appraise typical or worst case dwellings, the second stage may involve a forensic
external survey of one or more properties provided they are representative of the
others.
•
•
Internal components: Public areas, shared services and high risk components
would generally have 100% assessment.
Internal components: Private areas and services would be assessed in a similar
manner as the two stage process for external components.
4.2
Modification of reference service life by factors
The factor method of estimating component service lives developed in Japan is
incorporated in ISO/DIS 15686–1 — ‘General principles of service life planning’
(Architectural Institute of Japan, 1993). Components are allocated a reference service
life which is adjusted positively or negatively by multiplication of factors which
represent, numerically, quality levels of: a) materials and components, b) design, c)
sitework/execution, d) indoor environment, e) outdoor environment, f) operating
characteristics and g) maintenance level.
This method would readily adapt itself to an insurance model by factoring the
reference service life to take into account the insurance risk. Knowledge of age and
condition of an existing component would provide a control check on the assumptions
of the factor model. The remaining service life could simply be calculated by
subtracting the age of the component from the estimated service life. The insurance
life would be a proportion of the remaining service life. While there are theoretical
worked examples of the factor approach there is little direct experience of using the
method. Consideration is also required of the effects of dosage variations and agents
in combination. Research is being carried out to quantify factors and evaluate the
mathematical relationships between factors (Hovde, 1998).
Nevertheless, the factor method provides a valuable framework within which to
assess principal agents of deterioration and to adjust remaining service lives positively
or negatively. In–house notes for auditors provide guidance on agents of deterioration,
key failure modes and durability issues. In the context of allocating insurance lives to
existing components the insurance life or ‘nominal’ life is increased or decreased in
five year steps related to positive or negative factors.
4.3
Scales of component condition
A series of reference pictures, photographs or sketches is compiled for each
component showing stages of deterioration, for differing modes of failure, from new to
failed.
4.3.1 Advantages of this approach include:
•
•
•
•
The actual condition can be compared to an objective standard.
Auditors’ assessments should be more consistent.
Position on the condition scale and associated mode of failure clarifies the
allocation of an insurance life.
Stochastic modeling techniques are being developed to provide performance
prediction taking into account uncertainty and variability associated with
component quality, deterioration agents, quality of design, workmanship and
maintenance regime (Lounis et al, 1998a).
4.3.2 Disadvantages:
•
•
Information is not readily available, although academic papers suggest research
has been carried out (Greer and Malek, 1998 and Brite-Euram 4213, 1996).
Condition assessments on site would necessitate auditors carrying a potentially
huge manual. Auditors could use photographs from site to compare with
condition scales in the office, however this looses directness of observation.
Assessment by reference to condition scales remains an attractive method.
Condition scales for commonly encountered components could be established and
expanded as and when new components were encountered. Differing components
constructed of the same material should follow similar failure patterns for given
conditions. A set of condition scales for say, internal timbers would cover a large
number of component sub–types (e.g. floor joists, wall plates, rafters and the like).
4.4
Rates of deterioration
The rate of component deterioration is a valuable piece of information to aid the
process of service life assessment. The condition of an existing component at the time
of inspection gives an indication of the rate of deterioration for a given set of
conditions.
Three patterns of deterioration are recognized a) constant rate of deterioration —
decomposition of timber, b) decreasing rate of deterioration — carbonation of concrete
and c) increasing rate of deterioration — freeze–thaw action on concrete (Matsufuji et
al, 1996). However, the pattern of deterioration is rarely sufficient in itself to complete
the assessment of future service life.
In the case of a timber joist, repairs may be carried out which arrest decay and
prevent further deterioration. The condition of the joist may not be as new but the
remaining service life could equivalent to that for a new joist.
The pattern of concrete carbonation is only a guide to estimate the future life of a
concrete structure The rate of carbonation, depth of reinforcement cover, quality of
reinforcement, exposure and degree of pollution are other factors which would be
considered. The carbonation process is influenced by three main variables: relative
humidity, cement content and ambient CO2 (Keršner et al, 1996). The implication for
assessment of future service life is to concentrate on the dominant factors which
influence the service life of a component within the framework of a particular pattern
of deterioration.
While the action of free–thaw cycles may lead to accelerated deterioration of
concrete, the frequency of freeze–thaw cycles as a climatic variable is critical in
assessing the future service life of exposed concrete. Notwithstanding considerations
of climatic change the general approach is to assume that future climatic conditions
broadly follow the pattern of the recent past. By establishing the historic rate of
deterioration the future rate and point of failure may be calculated.
To assess future service life a definition of component end–state or moment for
replacement is required. This is taken from BS 7543 as the point at which excessive
expenditure is required on operation, maintenance or repair. In insurance terms the
quantification of component end–state is linked with performance of function, threat of
damage as well as component deterioration.
4.5
Failure patterns
There are numerous statistical functions to model component failure; the Weibull
distribution describes a variety of failure patterns (Bartlett and Simpson, 1998). Where
possible results from published research are assessed to inform auditors judgement
about the future service life of components for the purposes of allocating an insurance
life. This section discusses three principal patterns of failure associated with
components to enhance the assessment of future service life. Failure pattern models
have been applied to the problem of maintenance optimisation (Moubray, 1997); the
principles can be adapted to service life assessment.
4.5.1 Burn–in failure
The Weibull shape parameter is less than 1. Failures of this pattern can be
discounted as we are dealing with existing buildings. Components which have failed
due to burn–in failure will have been repaired or replaced.
4.5.2 Random or constant failure
Where the Weibull shape parameter is 1. While it is not possible to predict when
any particular component will fail, the mean time between failures may be calculated.
For purposes of assessing the residual life of components the mean time to failure can
be treated as an average life. Components such as ventilation fans with bearings
follow this type of failure pattern. The insurance life associated with these
components takes into account the risk associated with random failure.
4.5.3 Age–related failure
This is the case when the Weibull shape parameter is greater than 1. Where the
Weibull shape parameter is between 1 and 2 a pattern showing increasing probability
of failure is described. Typically this pattern is associated with fatigue related failures,
for example, a pump working over capacity. The rate of failure may vary considerably
from weeks to decades. Where the rate of failure is very low this curve may
approximate to that of random failure, with similar consequences for the service life of
components.
A shape parameter of 3.2 or more tends towards a normal (bell–shaped)
distribution. An assessment of survey data for the estimated service life of over 30
components showed that a significant number of components such as softwood
windows displayed a normal distribution (Bourke, 1994). This information has been
applied to the quantification of insurance lives which represent a time before the
average service life.
In practice component failure patterns do not always conform to one of these
Weibull distributions. The deterioration of masonry can be described by a three
component composite model representing the cyclical mechanism of surface layer
delamination due to free–thaw weathering (Molina et al, 1996).
A combination of random followed by age–related failure may be a more
accurate description of the failure pattern experienced by external components such as
roof tiles. In which case the onset of the age–related failure part of the curve would
represent the service life.
Where failure patterns can be associated with components they provide a useful
framework in which to judge their remaining service life and allocate a nominal
insurance life.
4.6
Probabilistic models
The prediction of service lives has been considered as a probabilistic reliability
problem (Lounis et al, 1998b). Guidance on the values to input into the theoretical
equations would determine how these models could be applied in the context of
remaining service life assessment.
4.7
Service life forecasting guidance — based on ISO/DIS 15686–1
The international standard gives guidance on service life planning in the context
of imperfect knowledge. Two methods for forecasting the service life of buildings are
proposed. The factor method has been commented on earlier.
Use of test data is the second method for predicting service lives. Where
relevant test data is available the decision tree procedure as outlined in ISO/DIS
15686–1 and developed in ISO/CD 15686–2 is followed to provide an input to service
life forecasting.
The office has built up a large data base of published service life estimates which
is used in the evaluation of remaining service lives. In-house experience based on
defect investigation and insurance claims provides feedback from practice.
Table 2: The process of allocating an insurance life.
Allocation of insurance lives — process
Guidance
1. Preparation — As built drawings, information from
pilot schemes, condition surveys, specialist surveys or
reports. Documentation for any proposed works.
Published information on
defects/durability of
similar buildings.
2. Identification — Identify components, ideally the
manufacturer/product or by principal material as
defined by component sub-type categories.
Classification based on
the HAPM Component
Life Manual.
3. Determine condition — visual inspection, mechanical
probing/testing, opening up, boroscope investigation.
Specialist reports e.g. drainage or concrete corrosion.
In-house notes on
condition scales and
inspection procedures.
4. Construction — Consider design aspects which
influence durability. Check workmanship especially at
junctions between different components and materials.
Inspection is facilitated
with site visits during
construction work.
5. Agents of deterioration — Consider agents of
deterioration, modes of failure, rate of deterioration,
external environment, internal environment, anticipated
in-use conditions, effects of dosage variation and agents
in combination.
In-house notes on
principal agents and rates
of deterioration, modes
of failure and key
durability issues.
6. Remaining service life assessment — Evaluation of
likely remaining service life based on current condition
and age of component in the context of the overall
construction and agents of deterioration.
In–house notes on failure
patterns, service lives
based on published
sources and experience.
7. Insurance life allocation — Determine the insurance
life by reference to and comparison between the
remaining service life and the nominal life.
Nominal insurance life
dictates maximum
insurance life.
5
Methodology to assess remaining service lives of components for insurance
The methodology used by HAPM auditors to assess the remaining service lives
of components and the allocation of insurance lives is summarized in Table 2. At each
stage of the process rules are provided. In practice the methodology draws on each of
the service life assessment models described in this paper. The process is rarely linear
as suggested by the table. Experience to date suggests the process is iterative; as more
information becomes available and the work on site progresses a clearer picture of
component type, condition and construction is gained. Feedback from in-house
research and guidance about condition scales, failure patterns, rates of deterioration
enhance the objectivity of site visits and inform assessment of remaining service life.
The allocation of insurance lives is a function of the remaining service life.
Consistency is achieved by the insurance structure of maximum insurance lives
and the principle of allocating insurance lives in five year bands. This restricts the
range of choice so minor variations in the qualitative approach are limited. The office
environment encourages informal discussions between auditors to compare and norm
results. Formal meetings and joint site inspections are arranged to discuss particular
difficulties. The quality control system within the office ensures that each judgement
about insured lives is checked at each stage of the reporting process.
6
Expert computer systems
The use of knowledge–based expert systems for service life prediction has been
suggested (Frohnsdorff and Martin, 1996). The HAPM model could benefit from
application of expert systems. The condition of existing components and factors
which influence future service life vary on a continuum. Attaching a quantitative
value to continuous variables is problematic particularly where measures of condition
or climate require specialist equipment. The mathematics of fuzzy logic enables non–
specific variables to be modeled. The output expresses remaining service life as a
probability. The key to using fuzzy logic is in defining rules to underpin the model.
A complementary approach would be to input the known data into a ‘rule
induction’ or ‘neural software’ system to generate rules from patterns which may
emerge from the data. The information and rules generated from these systems may be
incorporated in a knowledge–based expert system which encapsulates the decision
making process for remaining service life assessment and insurance life allocation.
7
Conclusion
The HAPM methodology for assessing remaining service lives of components
for the purposes of allocating insurance lives is eclectic. It embraces aspects from each
of the service life assessment models outlined above. The decision making approach is
pragmatic — we do not have perfect knowledge but we are making the best judgement
we can, informed by up–to–date research, methodologies and guidance.
8
References
Architectural Institute of Japan. (1993) Principle guide for service life planning of
buildings, English edition.
Bartlett, E. V. and Simpson, S. (1998) “Durability and reliability, alternative
approaches to assessment of component performance over time”, in Proceedings
of CIB WBC, Gävle. pp 35 – 42.
BS 7543. (1992) British Standard guide to durability of buildings and building
elements, products and components. BSI, London.
Bourke, K.P. (1994) Estimating building component durability for the purpose of risk
management. Unpublished M Phil thesis, University of the West of England.
Bourke, K.P. (1996) Model for insuring durability of building components, in
Proceedings of Dbmc7 Stockholm, E & FN Spon, London, pp1223 – 1230.
Brite–Euram 4213. (1996) Condition assessment and maintenance strategies for
buildings and building components. Brite–Euram project 4213 for CEC.
Frohnsdorff, G.J. and Martin, J.W. (1996) Towards prediction of building service
life: the standards imperative, Proceedings of Dbmc7 Stockholm, pp1417 – 1428.
CI/SfB. (1991) Construction indexing manual. RIBA Publications, London.
Greer, W.C. Jr. and Malek, W. C. (1998) Information system for maintenance of
2500 buildings: a case history, in Proceedings of CIB WBC, Gävle. pp585 –592.
Holmes, R. and Wornell, P. (1994) Optimising defects control through design and
insurance, in Pro int. sym. dealing with defects in building, Varenna, pp553–562.
Hovde, P. J. (1998) Evaluation of the factor method to estimate the service life of
building components, in Proceedings of CIB WBC, Gävle, pp223 – 232.
ISO/DIS 15686–1. (1998), Buildings - service life planning. Part 1 : General
principles, ISO/TC 59/SC3/WG9, “Design life of buildings” BSI, London.
ISO/CD 15686–2. (1998), Buildings - service life planning. Part 2 : Service life
prediction, BSI, London.
Keršner, Z. et al. (1996) Service life prediction based on carbonation in Proceedings
of Dbmc7 Stockholm, E & FN Spon, London, pp13 – 20.
Lounis, Z. et al. (1998a) A discrete stochastic model for performance prediction of
roofing systems, in Proceedings of CIB WBC, Gävle, pp305 – 314.
Lounis, Z. et al. (1998b) Further steps towards a quantitative approach to durability
design, in Proceedings of CIB WBC, Gävle, pp315 – 324.
Matsufuji, Y. et al. (1996) Service life predictive method of building materials, in
Proceedings of Dbmc7 Stockholm, E & FN Spon, London, pp45 – 53.
Mayer, P. D. et al. (1994) Stock condition surveys: a basic guide for housing
associations, National Federation of Housing Associations, London.
Molina, C. et al. (1996) A service life prediction model for masonry based on
accelerated testing and Weibull interpreted testing results, in Proceedings of
Dbmc7 Stockholm, E & FN Spon, London, pp75 – 85.
Moss, G. (1995) Lifespans of building components, HAPM Technical Note number 6
– June 1995, HAPM, London.
Moubray, J. (1997) Reliability–centred maintenance, Butterworth Heinemann,
Oxford, United Kingdom.
Wornell, P. et al. (1992) HAPM Component Life Manual, E & FN Spon, London.