Decision Support Tools

The most relevant DSTs identified in the literature, i.e. in this thesis only those DST that permit a building assessment to be made were considered, are summarised below. These reviews helped to shape the proposed decision support framework developed in this thesis.

EPIQR (Flourentzos et al. 2000) is a DST for domestic dwellings, but it is reviewed here because it influences other DSTs in the non-domestic sector (Strachan & Banfill 2012). This assessment of building conditions considered more than 50 elements where users needed to allocate a deterioration code. An Indoor Environmental Quality (IEQ) was also assessed via a questionnaire for occupants. Another DST, which is similar to the EPIQR assessment but is orientated to non-domestic buildings, is TOBUS DST (Flourentzou et al. 2002), which includes an extra assessment on lighting and day lighting evaluation. While both tools evaluate the building elements and occupants’ IEQ satisfaction, other aspects such as water, objective IEQ through acquired objective data, maintenance expenditure, and compliance issues are not included.

A slightly broader assessment of building performance is encountered in XENIOS (Dascalaki & Balaras 2004), a GA (Genetic Algorithm) DST (Juan et al. 2009) and Hybrid Decision Support System (Juan et al. 2010). XENIOS is intended for hotels; not only it assesses the condition of the facility elements, it also helps in an environmental impact evaluation. This includes estimating the levels of different air pollutants based on the energy consumed by the hotel. Water is also assessed. A GA based DST is intended for domestic buildings where it aims to improve the quality and performance of dwellings via six main aspects that are then divided into sub criterion. The main aspects evaluated are safety, usage, convenience, comfort, utility, and comfort. Then, an assessment score is obtained from evaluating the main aspects through a questionnaire, and if that score is lower than a suggested minimum threshold, refurbishment is then recommended. The refurbishment options are selected based on whether the users’ preference is a quality or budget priority. This hybrid DST (Juan et al. 2010) enables the sustainability levels of non-domestic property to be assessed via different criteria, i.e.

66 site, energy and water efficiency, materials and resources, and IEQ. The refurbishment strategy is provided based on a trade-off between the user’s selected budget and the quality of the refurbishment.

The DST that prioritised retrofits, also incorporated building energy management system (BEMS) data (Doukas et al. 2009). This system prioritises building upgrades based on a comparison between current building energy performance data acquired from the BEMS and a benchmark. This means that the operation with the highest difference from the benchmark is the first that needs to be addressed. While being an intelligent method, as in all of the aforementioned DSTs, its scope is restricted due not only because the building performance assessment is exclusively energy driven but also because subjective aspects coming from the decision maker are absent in this tool.

All the aforementioned DSTs were reviewed by Strachan and Banfill (2012). Essentially, the limitations commonly found in all those DSTs were:

 Not considering the occupant’s views in the whole process. That includes the whole process, from building assessment to the building post-refurbished.  The usefulness of the DSTs. A data update in the DST should be included with

new data recorded as per Doukas et al. (2009).

 Data quality. The sources of the data were not provided.

 Inclusion of externalities. External factors such as legislation or an organisation’s strategic views which might affect the suitability of some interventions were omitted.

Strachan and Banfill (2012) also developed their own DST that seems to be capable of taking more than one building into account. It also allows for a comprehensive energy performance building assessment that considers the occupant’s views. However, its scope is limited to energy efficiency and therefore the refurbishment only focussed on improving energy savings. Hence, in their current assessment of building condition only the energy performance and associated carbon emissions were considered. Finally their building assessment module, in the author of this thesis opinion, also has the two drawbacks described below:

 Despite stating that it can evaluate more than one building it appears to be unable to accomplish an energy assessment for a whole building portfolio. For instance, audits of all buildings must determine the internal heat gains, the efficiency of equipment, IT, and small lighting. These inspections are desirable

67 but will probably not occur, particularly in institutions such as universities where only a limited budget is available. Therefore, before requesting that all buildings be audited, the available data should have been investigated. Furthermore, the occupant’s views per building are being asked for, and while this perspective of the building is a crucial part of building assessment and refurbishment, it is extremely demanding of time and resources, so consulting the occupants’ in-situ while assessing a whole building portfolio was considered to be impractical. There are other tools that account for the occupants’ dissatisfaction and knowledge of the building without requiring a great deal of time.

 The reason for conducting the refurbishment is asked, but the reason for a refurbishment might not always be known beforehand. The data analysis might help in deciding which feature is underperforming.