Engineering Asset Research Articles

IT Enabled Engineering Asset Management: A Governance Perspective

Engineering asset lifecycle management requires a variety of information as well as operational technologies to keep their asset base in running condition In theory these technologies are used in collection, storage, and analysis of information spanning asset lifecycle processes; providing decision support capabilities through analytic conclusions arrived at from analysis of data; and in providing an integrated view of asset management through processing and communication of information that also allows for the basis of asset management functional integration. In doing so, these technologies not only provide for the control of asset lifecycle tasks, but also contribute to the overall advise on effective asset management though the critical role that they have in decision making. However, even though operational technologies depend a lot on information technologies for their smooth functioning, yet due to their specialized nature these operational technologies are not considered as part of the overall organizational information technology infrastructure. Consequently, when it comes to governance of information technologies, operational technologies are not accounted for. This paper provides a framework for governance of information technologies utilized for asset lifecycle management. It concludes that information technologies should not be taken as technical constructs, these are at the core of strategic alignment, value delivery, resource management, and risk management. Governance of information technology, therefore, calls for understanding and accounting for the whole information technology base and enabling infrastructure of the organization.

Strategic asset management modelling of infrastructure assets

Network Rail owns tens of thousands of civil engineering assets in the UK which include more than 40 000 bridges, 15 000 km of earthworks and 200 km of sea defences. In order to manage this diverse and ageing infrastructure a model was required to forecast the level of expenditure needed to meet defined levels of service that recognises the variation in types of asset, individual condition and the intensity of use of each asset. The model allowed Network Rail to plan its programme of maintenance work on civil engineering assets to achieve long-term objectives and provided essential information in preparation for periodic submissions for funding to the Office of Rail Regulation. Recognising that each asset could be managed in a number of ways, Mouchel provided modelling support to forecast the expenditure and performance implications for a range of policies. By selecting the policies to be applied to different groups of structures, Network Rail was able to investigate the implications of applying different combinations of policies to groups of assets, or assets on specific railway routes. This enabled Network Rail to identify a preferred maintenance approach according to funding levels and immediate performance requirements with full recognition of the long-term implications. The models utilised Bayesian statistical methods to deal with the large number of assets and optimising routines to ensure that structures were managed efficiently over the long term.

Testing a tri-partite contingent model of engineering cultures: A pilot study

For some time there has been a growing awareness of organizational culture and its impact on the functioning of engineering and maintenance departments. Those wishing to implement contemporary maintenance regimes (e.g. condition based maintenance) are often encouraged to develop “appropriate cultures” to support a new method’s introduction. Unfortunately these same publications often fail to specifically articulate the cultural values required to support those efforts. In the broader literature, only a limited number of case examples document the cultural values held by engineering asset intensive firms and how they contribute to their success (or failure). Consequently a gap exists in our knowledge of what engineering cultures currently might look like, or what might constitute a best practice engineering asset culture. The findings of a pilot study investigating the perceived ideal characteristics of engineering asset cultures are reported. Engineering managers, consultants and academics ( n=47), were surveyed as to what they saw were essential attributes of both engineering cultures and engineering asset personnel. Valued cultural elements included those orientated around continuous improvement, safety and quality. Valued individual attributes included openness to change, interpersonal skills and conscientiousness. The paper concludes with a discussion regarding the development of a best practice cultural framework for practitioners and engineering managers.

A Tutorial on Nonlinear Time‐Series Data Mining in Engineering Asset Health and Reliability Prediction: Concepts, Models, and Algorithms

The primary objective of engineering asset management is to optimize assets service delivery potential and to minimize the related risks and costs over their entire life through the development and application of asset health and usage management in which the health and reliability prediction plays an important role. In real‐life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset is generally described as monitored nonlinear time‐series data and subject to high levels of uncertainty and unpredictability. It has been proved that application of data mining techniques is very useful for extracting relevant features which can be used as parameters for assets diagnosis and prognosis. In this paper, a tutorial on nonlinear time‐series data mining in engineering asset health and reliability prediction is given. Besides that an overview on health and reliability prediction techniques for engineering assets is covered, this tutorial will focus on concepts, models, algorithms, and applications of hidden Markov models (HMMs) and hidden semi‐Markov models (HSMMs) in engineering asset health prognosis, which are representatives of recent engineering asset health prediction techniques.

Mobile solutions for engineering asset and maintenance management

PurposeThis paper seeks to present an overview of current trends in employing wireless solutions to engineering asset and maintenance management.Design/methodology/approachThe paper reviews literature and technological advances in wireless technologies and their applications in engineering asset and maintenance management from the viewpoint of assessing their potential impact, use and penetration in industrial practice. Rather than attempting a literature survey, the paper highlights emerging opportunities, benefits and potential hurdles in the adoption of mobile application solutions for industrial assets.FindingsDespite the fact that the use of advanced application solutions in manufacturing, production or process facilities takes place at a different scale, the emerging trend has already shown that mobile technologies have a great potential to redefine and re‐engineer the conventional setting for industrial asset and maintenance management. They have already begun to form the basis for offering advanced and smart solutions to remotely manage complex, high‐risk, and capital‐intensive assets, regardless of the geographical location, building agile information and knowledge networks. The key characteristics of the emerging environment include: 24/7 connectivity for active data management, enhanced web‐based interactivity, ready access to knowledge and information, and growth of use of advanced communication networks.Research limitations/implicationsThe paper focuses on analysing current trends and concludes by highlighting promising research directions in employing wireless and mobile solutions for engineering and maintenance asset management.Practical implicationsManagerial and engineering personnel, as well as practitioners, can examine on a case‐by‐case basis the specific benefits that can be offered by the introduction of mobile technologies for engineering asset and maintenance management.Originality/valueThe recent penetration of mobile technologies in industrial practice highlights the need to assess the benefits of the technology in maintenance engineering. Much of the literature focuses on the contribution of ICT in maintenance, without analysing the impact of mobile technologies. The paper goes some way towards examining and analysing the current practice and prospects of implementing mobile application solutions in maintenance.

Agent-Based Integrated and Collaborative Engineering Asset Management

Engineering assets are fundamentally important to enterprises. Thus, making the best use of engineering assets attracts equipment and system engineers’ attention. The state-of-the-art researches contribute to asset condition monitoring, asset symptom diagnosis, asset health prognosis, and the integration of above knowledge. However, they still lack the combination with enterprise resources to determine the best maintenance/renewal time for the optimization of total enterprise benefits. Consequently, this paper proposes the integrated architectural framework, activity and process models of a multi-agent system called agent-based integrated engineering asset management (AIEAM) based on agent techniques to build collaborative environment for asset manager, diagnosis expert, prognosis expert and enterprise resource manager. An engineering asset management case (for repair and maintenance of automatic parking tower) applying the proposed architecture and models is depicted in the paper.

A data quality framework for engineering asset management

Data Quality (DQ) is a critical issue for effective engineering asset management (AM). DQ problems can result in severe negative consequences for an organisation. Several research studies have indicated that most organisations have DQ problems. This research aims to explore DQ issues associated with asset management in engineering organisations. The study first develops an AM specific DQ framework, and then tests it in a preliminary case study of two large Australian engineering organisations. The empirical findings of the DQ issues from the research are used to validate the proposed AM DQ framework. This study provides a better understanding of DQ issues for engineering asset management. This in turn will assist in providing useful advice for improving DQ in this area, leading to activities which will help ensure DQ. The research suggests that the importance of DQ issues for engineering asset management is often overlooked; thus, there is a need for more scrutinised studies in order to raise general awareness.

A risk management toolkit for integrated engineering asset maintenance

This paper presents the design of a risk management toolkit that facilitates maintenance of integrated engineering assets over a distributed operational environment. Key aspects of the tool includes impact profiling (ie, the impact of loss of a particular system or sub-system), parametric modelling of the system-as-a-whole and business case generation. A variance based model has been developed for risk assessment. The system provides number of other features including, but not limited to, report generation, alert and flash messaging, testing/testability considerations and other such records. The system also offers a limited degree of visualisation capabilities in order to view risks at various layers and types.

Similitude: Fatigue cracking in steels

The ability to understand and predict fatigue crack growth is central to both the design and the continued operational safety of aircraft, rail, offshore structures, nuclear power plants, and many other engineering assets. However, most current crack growth models are based on the concept of similitude. This paper examines cracking in a range of steels and reveals that the similitude hypothesis is invalid in Region I, where the crack growth rate is low.

E-Prognostics: A Step towards E-Maintenance of Engineering Assets

Reliability of manufacturing or production processes is heavily dependent upon the flawless operation of asset plant and equipment utilised in the processes. Nevertheless, continuous and seamless flow of information, aimed at real time access to process stakeholders provides the foundation for effective management of these assets. An essential requirement in this regard is the continuous availability of the condition monitoring information and its analyses in order to predict failure conditions as soon as the asset starts deviating away from its standard operational behaviour. This paper presents an integrated approach for prognostics based on radio frequency identification (RFID) technology. It presents an architecture aimed at introducing information processing capabilities at the asset level, thereby equipping the asset to be proactive in identifying its maintenance requirements wirelessly rather than relying on human interaction to examine the asset for irregularities.

The Role of Ontologies in Reusing Domain and Enterprise Engineering Assets

The main purpose of the paper is to compare ontology-based reuse techniques in domain engineering and enterprise engineering. It discusses attempts to combine classical domain engineering technique...

The Role of Ontologies in Reusing Domain and Enterprise Engineering Assets

The main purpose of the paper is to compare ontology-based reuse techniques in domain engineering and enterprise engineering. It discusses attempts to combine classical domain engineering techniques with ontology-based techniques as well as the attempts to incorporate ontologies in enterprise engineering process and demonstrates that, on the one hand, both approaches still are not mature enough to solve practical reuse problems and, on the other hand, both propose ideas that can be used to develop more mature approach. The main contribution of the paper is the detail description of the problems of ontology-based reuse of enterprise engineering assets.