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Despite being poised as a standard for data exchange for operation and maintenance data, the database heritage of the MIMOSA OSA-EAI is clearly evident from using a relational model at its core. The XML schema (XSD) definitions, which are used for communication between asset management systems, are based on the MIMOSA common relational information schema (CRIS), a relational model, and consequently, many database concepts permeate the communications layer. The adoption of a relational model leads to several deficiencies, and overlooks advances in object-oriented approach for an upcoming version of the specification, and the common conceptual object model (CCOM) sees a transition to fully utilising object-oriented features for the standard. Unified modelling language (UML) is used as a medium for documentation as well as facilitating XSD code generation. This paper details some of the decisions faced in developing the CCOM and provides a glimpse into the future of asset management and data exchange models.

Linear (or continuous) assets are engineering infrastructure that usually spans long distances and can be divided into different segments, all of which perform the same function but may be subject to different loads and environmental factors. Typical linear assets include railway lines, roads, pipelines and cables. How and when to renew such assets are critical decisions for asset owners as they normally involves significant capital investment. Through investigating the characteristics of linear asset renewal decisions and identifying the critical requirements that are associated with renewal decisions, we present a multi-criteria decision support method to help optimise renewal decisions. A case study that concerns renewal of an economiser's tubing system is a coal-fired power station is adopted to demonstrate the application of this method. Although the paper concerns a particular linear asset decision type, the approach has broad applicability for linear asset management.

Over the last decade, system integration has grown in popularity as it allows organisations to streamline business processes. Traditionally, system integration has been conducted through point-to-point solutions – as a new integration scenario requirement arises, a custom solution is built between the relevant systems. Bus-based solutions are now preferred, whereby all systems communicate via an intermediary system such as an enterprise service bus, using a common data exchange model. This research investigates the use of a common data exchange model based on open standards, specifically MIMOSA OSA-EAI, for asset management system integration. A case study is conducted that involves the integration of processes between a SCADA, maintenance decision support and work management system. A diverse number of software platforms are employed in developing the final solution, all tied together through MIMOSA OSA-EAI-based XML web services. The lessons learned from the exercise are presented throughout the paper.

An asset registry arguably forms the core system that needs to be in place before other systems can operate or interoperate. Most systems have rudimentary asset registry functionality that store assets, relationships, or characteristics, and this leads to different asset management systems storing similar sets of data in multiple locations in an organisation. As organisations have been slowly moving their information architecture toward a service-oriented architecture, they have also been consolidating their multiple data stores, to form a “single point of truth”. As part of a strategy to integrate several asset management systems in an Australian railway organisation, a case study for developing a consolidated asset registry was conducted. A decision was made to use the MIMOSA OSA-EAI CRIS data model as well as the OSA-EAI Reference Data in building the platform due to the standard’s relative maturity and completeness. A pilot study of electrical traction equipment was selected, and the data sources feeding into the asset registry were primarily diagrammatic based. This paper presents the pitfalls encountered, approaches taken, and lessons learned during the development of the asset registry.

Data and information management systems have become a cornerstone for almost all operations of an organisation by providing quality, timely data for decision support. Information systems have progressed to cover a wide variety of asset management areas including asset registration, financial management, process scheduling and control, materials management, maintenance management, condition monitoring, risk management, reliability management, and safety management. Past studies into data management within asset management have focused on understanding why specific systems or specific data management processes are implemented in a firm. However, there has been little investigation into the broader picture of such asset management information systems and their overall data integration strategies. An exploratory, cross-sectional survey was conducted during 2007 and 2008 that explored a variety of data management issues in asset management across more than forty organisations. The survey research questions addressed practices in information system selection, data warehousing, integration, and data retention. Results show the significant adoption of information systems and data warehousing across different industries; the primary use of information systems to streamline business processes and enhance reporting; and the strong desire for improved system integration for next generation asset management information systems.

In an attempt to turn data management into a profitable enterprise, many businesses are seeking to integrate and centralise their data through data warehousing. A data warehouse then allows businesses to turn data into knowledge, and turn knowledge into tangible profits. One key success factor of a data warehouse lies in its ability to integrate data from multiple sources through a unified data model. Within asset management, several such integrated data models have been proposed, however these individually only cover a limited number of areas within asset management data and are not designed with data warehousing in mind. This paper presents the development process of a novel conceptual data warehousing data model that holistically integrates numerous asset management data areas. The comprehensive ethnographic modelling methodology involves a diverse set of inputs (including data model patterns, standards, information system data models, and business process models) that describes asset management data. The outputs of the process were verified by more than 20 experts in asset management and validated against four case studies.

Data are the lifeblood of an organisation, being employed by virtually all business functions within a firm. Data management, therefore, is a critical process in prolonging the life of a company and determining the success of each of an organisation’s business functions. The last decade and a half has seen data warehousing rising in priority within corporate data management as it provides an effective supporting platform for decision support tools. A cross-sectional survey conducted by this research showed that data warehousing is starting to be used within organisations for their engineering asset management, however the industry uptake is slow and has much room for development and improvement. This conclusion is also evidenced by the lack of systematic scholarly research within asset management data warehousing as compared to data warehousing for other business areas. This research is motivated by the lack of dedicated research into asset management data warehousing and attempts to provide original contributions to the area, focussing on data modelling. Integration is a fundamental characteristic of a data warehouse and facilitates the analysis of data from multiple sources. While several integration models exist for asset management, these only cover select areas of asset management. This research presents a novel conceptual data warehousing data model that integrates the numerous asset management data areas. The comprehensive ethnographic modelling methodology involved a diverse set of inputs (including data model patterns, standards, information system data models, and business process models) that described asset management data. Used as an integrated data source, the conceptual data model was verified by more than 20 experts in asset management and validated against four case studies. A large section of asset management data are stored in a relational format due to the maturity and pervasiveness of relational database management systems. Data warehousing offe

The amount of data that modern companies collect is ever increasing. With organisations that own a plethora of information systems, structured integration of data has become a pressing issue. Many companies have turned to data warehousing to bridge the gap of turning data into useful information and knowledge; however the data involved are typically from softer business domains rather than engineering-related domains. We investigate the area of engineering asset management data warehousing by examining the multidimensional modelling of asset management data. The multidimensional schemas are derived from the relational model in the MIMOSA OSA-EAI. The standards-based approach provides for platform neutrality, and as the OSA-EAI is a generic model, rules are given for company-specific implementations. From initial testing, query formation with multidimensional models is less complex than Third Normal Form models.

To integrate condition monitoring and reliability analysis with asset life-cycle management, a general-purpose asset health assessment system architecture is being developed. This system will assist management and maintenance staff to make decisions based on condition and reliability data, scientific analysis, and integrated information thereby reducing the asset management cost for enterprises. In this paper, a pattern-oriented software architecture design is presented. The functionality of the system is examined and some issues are identified. In particular, the paper elaborates on how design patterns are applied in the implementation of the different tiers in the system. It also presents a discussion detailing the system architecture that facilitates extensibility, flexibility, and robustness of the software system. To simplify the implementation of design patterns, various methodologies based on the in-built features of Microsoft .NET framework are applied.

Condition monitoring systems are prevalent in industries that contain critical assets. Their use allows the detection of potential failures at an early stage in order to minimise downtime and maintenance costs of a system. Many condition monitoring systems are commercially available, however these systems are limited in their support of diagnostic and prognostic models developed by external parties. An attempt to develop an extensible condition monitoring software lead to the creation of an ISO 13374/OSA-CBM based system named BUDS, which focuses on vibration condition monitoring. Research into condition monitoring data management strategies led our team to implement a database to support the data-driven application. A database based on the MIMOSA OSA-EAI database specification was used to store asset and sensor location, measurement event, raw sensor and processed signal data. This paper investigates the use of the MIMOSA OSA-EAI database for condition monitoring systems, and presents several issues encountered during the development process.

Timely decision making is critical in today’s competitive business world and in recent times, data warehousing has been employed by numerous companies to satisfy the needs of accurate and timely information. Data warehousing has traditionally been employed for financial and customer relationship analysis with current applications now moving to other domains, such as the medical and power industries. The asset management industry is one that has seen great strides in recent years due to improved technology, but data warehousing of asset management information has been lacking. A literature review was undertaken to determine data warehousing applications in the area of asset management, and with the lessons learned, a conceptual model of data warehousing for asset management is proposed. The water utility industry is chosen to provide a grounded example of an enterprise data warehouse model that integrates data from various local information systems. The particular issues faced in the asset management domain are highlighted, and several water utility applications are presented.

There have been several efforts made in the area of semi-automated techniques and tools for schema design. Most have focused on database schema design, and little work has been done on data warehouse schema design. This paper presents a new approach to data warehouse schema design based on case-based reasoning theory. Case-based reasoning is a problem solving paradigm that involves the development of a solution space to provide a basis for efficient reuse of proven pre-existing solutions. A detailed system design for the application of case-based reasoning to data warehouse schema design is examined in this paper. Two novel contributions of the paper include the matching of cases by data warehouse schema meta-data, and the use of a business context aware ontology to make intelligent suggestions on entities and attributes. These two approaches assist in improving the case matching and adaptation capability in the case-based reasoning system.

Asset management is playing an ever increasing role in sustaining the competitive capability of many businesses. Maintenance costs form a large proportion of asset management costs, and a reduction in these costs can represent significant savings to the business. Many software vendors provide various asset management solutions but lack complete horizontal and vertical integration; and with the sizeable number of systems come an equal number of software interfaces. With businesses that subscribe to different CMMS and condition monitoring systems from different vendors, system integration becomes a nightmare. By resolving the integration issue and considering holistic information, asset management can ascend to a new level through effective predictive maintenance. This paper outlines a proposal for integrating condition monitoring systems with a CMMS through the use of emerging technologies. The OSA-CBM framework will be implemented to monitor the condition of an asset for health assessment and predictive maintenance scheduling. Data will be stored in a MIMOSA-derived database, with communications between the OSA-CBM system and CMMS using the open standard MIMOSA OSA-EAI. The underlying foundation is a web services platform which will assist in turning asset condition data into real cost savings.