From physical degradation condition ratings of building elements to lost value ratio bands

Purpose Defining degradation in terms of physical deficiency-based condition descriptors, combined with Markov chain modelling, has been shown to provide improved predictions of degradation. However, unless these physical conditions are converted to lost value ratios (LVRs), maintenance managers would not be able to grasp the cost implications of degradation. Hence the purpose of this research is to convert the predicted deficiency-based condition ratings to lost value ratio bands. Design/methodology/approach Rectification costs were found using a Building Schedule of Rates to arrive at LVRs for each of the physical degradation conditions for the 12 building elements studied (ranging from concrete elements through finishes and ceilings to doors and windows). These LVRs were allocated into five bands with LVR interval limits of 0.00, 0.10, 0.25, 0.50, 0.75 and 1.00, with the five intervening ranges corresponding to LVR Bands A to E. These computations were compared with those arrived at independently by industry professionals. Findings Elements such as doors, widows and ceilings reached the maximum LVR Band E at the worst physical Condition 5 defined. However, Condition 5 for other elements only corresponded to LVR Bands A to D. Some 83% of the LVR bands assigned to the physical conditions were in agreement with those arrived at by the professionals, or differed by only one band. Originality/value The conversion of deficiency-based conditions to LVR bands yielded a completely new maintenance-oriented perspective on degradation. The banding was done using a novel ranking and clustering process that identified regions of high variation in LVRs as thresholds of the bands.

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Publication Details

Journal
Built Environment Project and Asset Management
Published
2024-09-26
DOI
https://doi.org/10.1108/bepam-12-2023-0218
Citations
2
Primary Topic
Life Cycle Costing Analysis
Type
article
Field-Weighted Citation Impact
1.89
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article

From physical degradation condition ratings of building elements to lost value ratio bands

Priyan Dias, Dilan Robert, Sujeeva Setunge, Vajira Wickramasinghe
2 citations
Built Environment Project and Asset Management
Life Cycle Costing Analysis
1.89
article

From physical degradation condition ratings of building elements to lost value ratio bands

Priyan Dias, Dilan Robert, Sujeeva Setunge, Vajira Wickramasinghe
article en
2 citations

Abstract

Purpose Defining degradation in terms of physical deficiency-based condition descriptors, combined with Markov chain modelling, has been shown to provide improved predictions of degradation. However, unless these physical conditions are converted to lost value ratios (LVRs), maintenance managers would not be able to grasp the cost implications of degradation. Hence the purpose of this research is to convert the predicted deficiency-based condition ratings to lost value ratio bands. Design/methodology/approach Rectification costs were found using a Building Schedule of Rates to arrive at LVRs for each of the physical degradation conditions for the 12 building elements studied (ranging from concrete elements through finishes and ceilings to doors and windows). These LVRs were allocated into five bands with LVR interval limits of 0.00, 0.10, 0.25, 0.50, 0.75 and 1.00, with the five intervening ranges corresponding to LVR Bands A to E. These computations were compared with those arrived at independently by industry professionals. Findings Elements such as doors, widows and ceilings reached the maximum LVR Band E at the worst physical Condition 5 defined. However, Condition 5 for other elements only corresponded to LVR Bands A to D. Some 83% of the LVR bands assigned to the physical conditions were in agreement with those arrived at by the professionals, or differed by only one band. Originality/value The conversion of deficiency-based conditions to LVR bands yielded a completely new maintenance-oriented perspective on degradation. The banding was done using a novel ranking and clustering process that identified regions of high variation in LVRs as thresholds of the bands.

Built Environment Project and Asset ManagementVol. 14(6)
Sri Lanka Institute of Information Technology (LK), University of Moratuwa (LK), RMIT University (AU)
Openalex Percentile: Top 12%
Life Cycle Costing Analysis
1.89
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