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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.