The contribution of enterprise systems to core capabilities: the case of asset lifecycle management in the utilities sector

The desire to obtain competitive advantage is a motivator for implementing Enterprise Resource Planning (ERP) Systems (Adam & O’Doherty, 2000). However, while it is accepted that Information Technology (IT) in general may contribute to the improvement of organisational performance (Melville, Kraemer, & Gurbaxani, 2004), the nature and extent of that contribution is poorly understood (Jacobs & Bendoly, 2003; Ravichandran & Lertwongsatien, 2005). Accordingly, Henderson and Venkatraman (1993) assert that it is the application of business and IT capabilities to develop and leverage a firm’s IT resources for organisational transformation, rather than the acquired technological functionality, that secures competitive advantage for firms. Application of the Resource Based View of the firm (Wernerfelt, 1984) and Dynamic Capabilities Theory (DCT) (Teece and Pisano (1998) in particular) may yield insights into whether or not the use of Enterprise Systems enhances organisations’ core capabilities and thereby obtains competitive advantage, sustainable or otherwise (Melville et al., 2004). An operational definition of Core Capabilities that is independent of the construct of Sustained Competitive Advantage is formulated. This Study proposes and utilises an applied Dynamic Capabilities framework to facilitate the investigation of the role of Enterprise Systems. The objective of this research study is to investigate the role of Enterprise Systems in the Core Dynamic Capabilities of Asset Lifecycle Management. The Study explores the activities of Asset Lifecycle Management, the Core Dynamic Capabilities inherent in Asset Lifecycle Management and the footprint of Enterprise Systems on those Dynamic Capabilities. Additionally, the study explains the mechanisms by which Enterprise Systems sustain the Exploitability and the Renewability of those Core Dynamic Capabilities. The study finds that Enterprise Systems contribute directly to the Value, Exploitability and Renewability of Core Dynamic Capabilities and indirectly to their Inimitability and Non-substitutability. The study concludes by presenting an applied Dynamic Capabilities framework, which integrates Alter (1992)’s definition of Information Systems with Teece and Pisano (1998)’s model of Dynamic Capabilities to provide a robust diagnostic for determining the sustained value generating contributions of Enterprise Systems. These frameworks are used in the conclusions to frame the findings of the study. The conclusions go on to assert that these frameworks are free - standing and analytically generalisable, per Siggelkow (2007) and Yin (2003).

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.

Energy harvesting for monitoring bridges over their operational life

The use of energy harvesting materials for large infrastructure is a promising and growing field. In this regard, the use of such harvesters for the purpose of structural health monitoring of bridges has been proposed in recent times as one of the feasible options since the deployment of them can remove the necessity of an external power source. This paper addresses the performance issue of such monitors over the life-cycle of a bridge as it deteriorates and the live load on the structure increases. In this regard, a Lead Zirconate Titanate (PZT) material is considered as the energy harvesting material and a comparison is carried out over the operational life of a reinforced concrete bridge. The evolution of annual average daily traffic (AADT) is taken into consideration, as is the degradation of the structure over time, due to the effects of corrosion. Evolution of such harvested energy is estimated over the life-cycle of the bridge and the sensitivity of harvested energy is investigated for varying rates of degradation and changes in AADT. The study allows for designing and understanding the potential of energy harvesters as a health monitor for bridges. This paper also illustrates how the natural growth of traffic on a bridge over time can accentuate the identification of damage, which is desirable for an ageing structure. The paper also assesses the impact and effects of deployment of harvesters in a bridge as a part of its design process, considering performance over the entire life-cycle versus a deployment at a certain age of the structure.