A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.

Life history of a native emydid turtle (Malaclemys terrapin centrata) on the remote oceanic islands of Bermuda

Diamondback terrapins (Malaclemys terrapin) are native to the remote oceanic islands of Bermuda and presently inhabit only four small brackish water ponds on a private golf course. The life history of this species is poorly understood on Bermuda and so the aim of this study was to fill these knowledge gaps, to compare the results with what is known from other areas in the North American range, and to inform the development of a local management plan. The results of a mark-recapture census revealed that ca. 100 individuals ≥81 mm straight carapace length live on Bermuda, of which nearly half (48.5%) were considered sexually mature. The population is dominated by females (sex ratio 2.9:1) and annual recruitment over the three year period was found to be extremely low (approximately two terrapins). Female diamondback terrapins in Bermuda nest almost exclusively within a limited number of sand bunkers on the golf course. Nesting commenced in late March or early April and ended in late August. Peak oviposition was observed in May and June. Clutch size averaged 5.1 eggs (range 0-10; SD 2.4) and the incubation period averaged 61.8 days (range 49-83; SD 10.5). Delayed emergence was documented, with 43.8% of the hatchlings remaining in their natal nests over the winter months. The mean annual hatching success rate was determined to be 19% (range 17.6-21; SD 1.9). Radio-telemetry was used to investigate the movements and survivorship of postemergent hatchling diamondback terrapins. The results indicated that mangrove swamps and grass-dominated marshes adjacent to the ponds are important developmental habitats for hatchlings. Yellow-crowned night herons (Nyctanassa violacea) were found to be significant predators of small terrapins during spring emergence. Small aquatic gastropods comprised 66.7% of the faecal samples analysed from the Bermudian population. Scavenged fish and vertebrate animal remains, terrestrial arthropods, polychaete worms and bivalves were consumed in lesser amounts. Sediment from the pond environment was found in 74% of the faecal samples analysed and is believed to have been incidentally ingested while foraging for the small benthic gastropods. Eco-toxicological analyses of the pond sediment, prey and terrapin eggs showed that the Bermudian diamondback terrapins live and feed in wetland habitats characterised by chronic, multifactorial contamination; principally total petroleum hydrocarbons, polycyclic aromatic hydrocarbons and a variety of heavy metals. This study found that some of those contaminants are accumulating in the gastropod prey as well as being transferred to terrapin eggs. This may be reducing the incidence of successful embryonic development for this species in Bermuda and may likely contribute to the observed low hatching rates. These collective findings indicate that the Bermudian population is very vulnerable to local extirpation.