Decision Making for Predictive Maintenance in Asset Information Management

Abstract

Asset management is a process of identification, design, construction, operation, and maintenance of physical assets (Wenzler, 2005). An asset-centric approach is vital for the success of an asset intensive organisation as the effective management of assets is a major determinant of organisational success. One key issue in asset information management is the availability of information at the right time, in the right format, before the right person, against the right query, and at the right level. This paper provides a comprehensive and in-depth critical analysis from literature which fulfils an identified need of fusing asset information for predictive maintenance so that decision making can be improved. The critical literature review included also highlights the need for an expert system which integrates reliable information with effective decision-support, under the umbrella of Asset Management. Various elements of asset management were critically reviewed, highlighting the need for more robust Predictive maintenance management for assets. We argue that this is best achieved by a system that, in particular, incorporates Expert System to enhance the quality of predictive maintenance through accurate decision analysis. In addition, it should have fuzzy logic reasoning ability that assists in the decision-making process. Our analysis leads us to propose that Expert System when combined with fuzzy logic provides a better way of decision making in predictive maintenance management of assets.

Real-time predictive maintenance for wind turbines using Big Data frameworks

“…Each status pattern corresponded to a specific class. In Tables I, II and III, the model's number represents the time-stamp of the predictive models that went from t+10 to t+60 (1)(2)(3)(4)(5)(6). The percentages that appear within the number of the classes are the percentages of the instances for each class within the dataset.…”

Information asset analysis: credit scoring and credit suggestion

“…Both the rules and the knowledge can be updated and it may happen in real time as a continuous analysis. Case-based reasoning is also considered (Faiz and Edirisinghe, 2009;Simic and Simic, 2007) for the process of decision making. This approach uses a set of problems and answers in a Case Archive.…”

“…These techniques provide the ability to monitor assets in real time dealing with the unknown and unpredictable where the goal may be to reduce asset maintenance expenses, improve utilisation and product quality. Artificial intelligence use, according to Faiz and Edirisinghe (2009), neural networks, expert systems and fuzzy logic. A neural network is a system that simulates the operation of the human brain and performs tasks such as data-mining, pattern recognition, classification and process modelling.…”

The Need for a Whole Life Framework in Electrical Power System Asset Management and the Problems with Individual Silo like Asset Management System Contributions

“…That is that the combination of hypothesised model, as expressed as a holistic framework created by the author and tested through a case study offers a well attuned mechanism to research the holistic asset management picture in light of the real world context [33][34][35][36]. Although the research method shown above is very much applicable for the purpose of power companies operating in capital investment only activities, it is not inclusive enough to ensure whole-life-cycle optimisation of power systems, assets and or power companies throughout the entire life cycle.…”

“…That is the lack of a corresponding holistic framework to utilise or apply. Some have attempted to morph a specific industrial concept to loosely fit elements of the power industry as demonstrated in report [35] yet again nothing specifically applied for power system assets.…”