VAJIRA WICKRAMASINGHE
The requirement of predicting degradation came into light mainly to predict the maintenance cost of the Council buildings in Sri Lanka. This would result in more efficient and effective management of available budgets in the future. The most common current approach adopted is a reactive process where the assets are repaired or replaced when they degrade beyond the functional thresholds. However, this poses many risks to the asset managers as well as the community being serviced by the assets. Therefore, it is imperative to adhere to a well-structured, proven management system in order to make this transformation of asset management a reality.
The state-of-the-art CAMS-Mobile application was used as the data entry platform and the CAMS-Online back end system was used to populate and explore the data by capitalising the above necessity. Seven Local Councils from seven different provinces in Sri Lanka have been selected in order to collect the building condition data.
The CAMS system was used in three phases during the whole process as follows;
1] Preparation of Asset Inventories – CAMS-Mobile Application
2] Building Condition Survey – CAMS-Mobile Application
3] Evaluation of Shape of the data – preliminary study of the data at council level – CAMS-Online System
1] Preparation of Asset Inventories
As far as the local councils are concerned, requirement of maintaining asset inventories for each council has become a key necessity. The ‘Building’ assets have been identified as one of the primary tangible asset types that should reflect on their asset inventories.
In the first phase using CAMS-Mobile application, an up-to-date inventory for the building assets was developed, which included all types of building assets in each local council. The templates based on building and component hierarchy were prepared to allow for the collection of condition data at a latter stage of the process.
2] Building Condition Survey
Prior to commencing with the second phase or the building condition survey, a condition rating scale was established, in-order to benchmark the existing conditions of the building components. In which, the rating scales for building components were ranging from 1 to 5, where Condition 1 was considered as good as new and Condition 5 as fully damaged.
The Building condition data collection was carried out using CAMS-Mobile application, which was available on iPad devices
A group of undergraduates were trained to carry-out the data survey for each local council. The students were selected from the Engineering Faculties of University of Moratuwa and Peradeniya. A team of instructors conducted the training workshops for the selected students. The said group of students was divided into a few teams and were dispatched to pertinent sites to carry out the data surveys under the guidance of the specialist team.
The Condition data of building components were collected from each building included in the above inventories of each local council and all the available building components were captured in detail. Inspection of the building components were carried out following the strict guidelines developed, under deterioration, deficiency and defect rating criteria. The identified level of deterioration for each component, is a measure of physical deterioration that encapsulates the aging factor. Whereas, the deficiency levels identified reflect the maintenance criticality which would allow for future evaluation of the cost of repairs more effectively. The defect levels were only considered, if the deficiencies were existed within an area which is less than 10% of the total area considered only for the components that can be measured in terms of area. So that the particular area can be treated locally without treating the total area of the respective component.
Therefore, these ratings will enable to determine the required management strategy and investments by predicting future degradation and associated cost.
3] Shape of the data – A preliminary study of the data at council level
The collected snapshot data were uploaded to CAMS database and populated on the data platform, following the completion of condition survey. The new integrated CAMS-Online platform would enable the raw data to be represented as graphical representations and charts in different formats. This comes as a handy tool in presenting the surveyed condition data. So that the condition state of the Component Groups and individual Buildings at present, can be identified with respect to each Local Council. Thereby, the level of degradation in present context can be identified without any further analysis.
The use of CAMS System was crucial in terms of incorporating a substantial number of building components from each condition state, in order to achieve a wide spread and thus to create an improved statistical model for future predictions. Also, the replacement criteria can be established by recognising the Component Groups with similar deterioration patterns in-order to streamline the maintenance activities
These selected seven Local Councils will be benefited by this proposed system in the near future and will enhance their asset management capabilities mainly with regards to handling respective budgets by minimising the risk-costs.