CivilEng, Volume 1, Issue 1 (June 2020) – 4 articles

Selecting a suitable sewer network plan for a city is a complex and challenging task that requires discussion among a group of experts and the consideration of multiple conflicting criteria with different measurement units. A number of multi-criteria decision-making (MCDM) methods have been proposed for analyzing sewer network selection problems, each having their own distinct advantages and limitations. Although many decision-making techniques are available, decision-makers are confronted with the difficult task of selecting the appropriate MCDM method, as each method can lead to different results when applied to an identical problem. This paper evaluates four different multi-criteria decision-making methods, which are the Analytic Hierarchy Process (AHP), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Elimination Et Choix Traduisant la REalité (ELECTRE III) and the Preference Ranking Organization METHods for Enrichment Evaluations II (PROMETHEE II), for one sewer network group decision problem in the early stage of sewer water infrastructure asset management. Moreover, during the implementation of different MCDM methods, the Delphi technique is introduced to organize and structure the discussions among all the decision-makers. The results of the study are examined based on each method’s ability to provide accurate representations of the decision-makers’ preferences and their experience implementing each method. As a conclusion, decision-makers identify PROMETHEE II as their favorite method, AHP is more time and energy consuming and results in a number of inconsistencies, while TOPSIS loses information during vector normalization for multi-dimension criteria, and ELECTRE III’s results are inconclusive. Full article

Decision support tools (DSTs) are increasingly being used to assist with asset acquisition and management decisions. Whether these tools are “fit for purpose” will have both economic and non-economic implications. Despite this, the on-going governance of DST performance receives only limited attention within both the academic and industry literature. This work addresses that research gap. Within this paper a conceptual process for managing the operational performance of decision support tools is presented. The novelty of the approach is that it aligns with the ISO 5500x:2014 Asset Management Standard, therefore introducing consistency in the governance of DSTs with physical engineered assets. A case study of the UK’s National Grid Electricity Transmission (NGET) is used to inform the approach design. The evaluation demonstrates it to be both logical and useable within the context of NGET and they have expressed an intention to implement the approach within their business. A key finding of the research was that DSTs transcend functions and organisations. This is significant and can lead to a situation whereby performance and criticality are interpreted and measured differently. The introduction of a common approach for managing DST performance works towards improving consistency and creating a shared understanding. Full article

Insurance is a growing economic activity within the construction sector. Homes and buildings are perhaps the most important investment an individual makes in his/her lifetime. Nevertheless, the market for insurance coverage policies applied to the building envelope is in an embryonic stage, mainly due to the lack of knowledge in terms of risk and costs associated to the failure of these elements. This study provides an innovative and methodological approach to the development of an insurance product that targets the obsolescence of building components. In defining a structured approach to the design of insurance policies for buildings, the use of the service life prediction models proposed in this study allows establishing different types of insurance policies with different risk premiums and evaluating different losses and risks accepted by the owners, thus promoting the increase of the patrimonial value of the asset and reducing the risk of premature failure and the uncertainty of the costs of maintenance during its life cycle. Full article