Loganthan et al. (2002) suggested that deterioration is a critical infrastructure problem contributing to increased replacement and repair costs which necessitates the need for prioritisation of pipe replacement. Park (2004) stated that when a failure event occurs, the structural integrity of the pipe has been lost due to environmental and operational stresses exerted on it over its service life. Research has shown that several factors influence pipe failure and that the quality, quantity and availability of failure data is critical for effective management of pipe infrastructure (Wood and Lence, 2006; Clair and Sinha, 2013).
Fletcher (2005) stated that the analysis of risk requires the examination and identification of the possible sources of an issue, including the impact and likelihood associated with the actual occurrence of an identified issue. Similarly, Simonsen and Perry (1999) provided the following three guiding questions for risk assessments:
· What can happen?
· How likely is it that it can happen?
· What are the consequences if it does happen?
Risk assessments are generally categorised as (i) qualitative, (ii) semi-quantitative and (iii) quantitative. Berg (2010) noted that all three techniques mentioned are acceptable analysis techniques, depending on the goal of the analysis, the information and type of data available and the manner in which risk is calculated or assigned. Table 2-10 provides a brief description of each of the risk assessment categories stated above.
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Table 2-10: Summary of risk assessment categories
Risk assessment
category Description
Qualitative
Comprises of the categorisation of risk with textual descriptions (high, medium, low). The use of a risk matrix for decision making is most common. Allows for use of operational staff with risk identification.
Semi-quantitative
Textual descriptions are replaced with numerical value assignments to describe relative risk scale. Risk matrices are also used, but individual elements can be compared based on ranked indices. The objective is to develop a hierarchy of risks which reveals the order that should be reviewed and no real relationship between them.
Quantitative
Quantification of risk with numerical modelling and probabilities and requires mathematical and statistical expertise. Suitable assessment technique with sufficient data and appropriate mathematical models to quantify specific risks.
Iacob (2014) stated that qualitative assessments are descriptive and do not imply an exact quantification and often provide support for further investigation and use of more quantitative approaches. Radu (2009) indicated that a qualitative risk assessment is most appropriate when numerical data are inadequate and limited expertise is available. Pollard and MacGillivray (2008) noted the importance of stakeholder engagement and the benefit of more qualitative approaches to include non-specialists part of the operational staff to provide useful insights.
Aven (2008) stated that risk analysis simply provides decision support and not the decision itself and qualitative or semi-quantitative analysis could present a more comprehensive risk picture, taking underlying factors that influence risk into account, when compared to a quantitative analysis, for which the calculations are tedious and could include a strong element of randomness. Swartz et al. (2010) concluded that risk estimation with risk matrices is a useful and efficient tool as it is easy to understand and present data.
FAO (2009) stated that a semi-quantitative risk assessment is most useful in providing a structured way to rank risks and is achieved through a predefined scoring system. Holmgren and Thedéen (2009) noted that the advantage of quantitative risk analysis is that it yields precise risk measures, but concede that such approaches should be avoided when the data quality is poor and the data sources are questionable. FAO (2009) mentioned that at least part of the assessment team should have rigorous mathematical training when quantitative risk assessments are considered.
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Research shows that a semi-quantitative risk approach is preferable when there is limited or questionable data and provides adaptability in including additional risk factors as it provides an intermediary level between the textual descriptions qualitative assessments and numerically modelled risk measures from quantitative assessments (FAO, 2009). In general, semi-quantitative risk analysis offers a more consistent approach for comparing risks than qualitative risk analysis and does not require the same level of mathematical skill or data requirements of quantitative risk analysis.
The risk-based prioritisation model used as part of this research has been developed as a practical method to account for factors that influence pipe failure, consequence of failure and management strategies (e.g. preference to replace asbestos-cement pipes due to possible health risks, regardless of remaining useful life). A final risk value is calculated from the likelihood and consequence of failure, which is based on scores and weights assigned to individual factors. The pipes are then ranked and prioritised according to the resultant risk value, with highest risk value receiving the highest priority. The risk model employed is therefore considered to fall within the semi- quantitative assessment category.
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3 Description of the once-off risk prioritisation approach
In this research, the risk-based prioritisation approach as explained in Sinske et al. (2009; 2011) and Sinske and Streicher (2013) and discussed by Scruton (2012) is used, as it has been widely implemented in South Africa in addition to the case study. Risk is calculated by multiplying factors that describe likelihood of failure (LF) and consequence of failure (CF). The factors are determined using several variables and their respective assigned scores and weights. A higher assigned score (and weight) will have a greater impact on the final risk calculation.