Search results

The purpose of this paper is to explore the main ontologies related to eMaintenance solutions and to study their application area. The advantages of using these ontologies to improve and control data quality will be investigated.

A literature study has been done to explore the eMaintenance ontologies in the different areas. These ontologies are mainly related to content structure and communication interface. Then, ontologies will be linked to each step of the data production process in maintenance.

The findings suggest that eMaintenance ontologies can help to produce a high-quality data in maintenance. The suggested maintenance data production process may help to control data quality. Using these ontologies in every step of the process may help to provide management tools to provide high-quality data.

Based on this study, it can be concluded that further research could broaden the investigation to identify more eMaintenance ontologies. Moreover, studying these ontologies in more technical details may help to increase the understandability and the use of these standards.

It has been concluded in this study that applying eMaintenance ontologies by companies needs additional cost and time. Also the lack or the ineffective use of eMaintenance tools in many enterprises is one of the limitations for using these ontologies.

Investigating eMaintenance ontologies and connecting them to maintenance data production is important to control and manage the data quality in maintenance.

The purpose of this paper is to investigate how performance of linear assets can be analysed and displayed, considering both the technical asset and the user context, to simplify cognitive tasks of planning and decision making.

Linear, or continuous assets, such as roads, railways, electrical grids and pipelines, are large, geographically spread out technical systems. Linear assets are comprised of system, subsystem and component levels. Thus, asset managers are involved with each level of the linear asset; asset management has strategic, tactical and operational levels. A methodology is developed to link together the technical and organisational levels and to measure asset performance considering their spatial extension. Geographical location and time are used as independent variables.

For performance measurement of linear assets, it is found that the spatial extension is an equally generic dimension as time is for technical assets in general. Furthermore, as linear assets actually are combinations of linear and point assets; separate analysis of these assets is a prerequisite. Asset performance has been studied in a case study in terms failures and cost; the results indicate that the methodology visualise poor, as well as good, performance in an easy to interpret manner. Besides, the results indicate that other parameters related to dependability can be presented in a similar way.

This study highlights the importance of including the spatial or geographical extension of linear assets in infrastructure managers’ performance measurement. It is believed that the methodology can make planning and decision making more effective by pointing out improvement areas in technical assets, in a way that is appealing to both technicians and managers.

As infrastructure managers are improving their analysis and visualisation of performance, the public's interest of following the information increases, which in turn contributes to the connection between infrastructure managers and the public.

The presented methodology and case study analysed performance in function of both the technical and organisational levels, including the spatial component. It is believed that the methodology for analysing and visualising performance of linear assets is distinctive.