Search results

This position paper urges a drive towards clarity in the key definitions, terminologies and habits of speech associated with digital engineering and building information modelling (BIM). The ultimate goal of the paper is to facilitate the move towards arriving at an ideal definition for both concepts.

This paper takes the “explanation building” review approach in providing prescriptive guidelines to researchers and industry practitioners. The aim of the review is to draw upon existing studies to identify, describe and find application of principles in a real-world context.

The paper highlights the definitional challenges surrounding digital engineering and BIM in Australia, to evoke a debate on BIM and digital engineering boundaries, how and why these two concepts may be linked, and how they relate to emerging concepts.

This is the first scholarly attempt to clarify the definition of digital engineering and address the confusion between the concepts of BIM and digital engineering.

The purpose of this paper is to present a new disruptive maintenance model based on new technologies.

The approach is carrying out through the impact of the Industry 4.0, Internet of things, big data, virtual reality and additive manufacturing on maintenance.

The findings are that new technologies are an evolutionary challenge that is immediately affecting maintenance engineering. It presents a unique opportunity to make a disruptive evolution of maintenance.

The correct development of Maintenance 4.0 relates to the correct implementation of Industry 4.0.

Maintenance 4.0 will greatly improve the main operating indicators: safety, reliability, availability and cost.

Maintenance 4.0 will contribute to a circular and sustainable economy.

For the first time, a complete new Maintenance Engineering 4.0 model is proposed. The application of the new technologies appears in each specific maintenance process of the product life cycle.

The purpose of this paper is to provide an overview of research and development in the measurement of maintenance performance. It considers the problems of various measuring parameters and comments on the lack of structure in and references for the measurement of maintenance performance. The main focus is to determine how value can be created for organizations by measuring maintenance performance, examining such maintenance strategies as condition‐based maintenance, reliability‐centred maintenance, e‐maintenance, etc. In other words, the objectives are to find frameworks or models that can be used to evaluate different maintenance strategies and determine the value of these frameworks for an organization.

A state‐of‐the‐art literature review has been carried out to answer the following two research questions. First, what approaches and techniques are used for maintenance performance measurement (MPM) and which MPM techniques are optimal for evaluating maintenance strategies? Second, in general, how can MPM create value for organizations and, more specifically, which system of measurement is best for which maintenance strategy?

The body of knowledge on maintenance performance is both quantitatively and qualitatively based. Quantitative approaches include economic and technical ratios, value‐based and balanced scorecards, system audits, composite formulations, and statistical and partial maintenance productivity indices. Qualitative approaches include human factors, amongst other aspects. Qualitatively based approaches are adopted because of the inherent limitations of effectively measuring a complex function such as maintenance through quantitative models. Maintenance decision makers often come to the best conclusion using heuristics, backed up by qualitative assessment, supported by quantitative measures. Both maintenance performance perspectives are included in this overview.

A comprehensive review of maintenance performance metrics is offered, aiming to give, in a condensed form, an extensive introduction to MPM and a presentation of the state of the art in this field.

The following is an introductory profile of the fastest growing firms over the three-year period of the study listed by corporate reputation ranking order. The business activities in which the firms are engaged are outlined to provide background information for the reader.

The purpose of this paper is to explore certain resources, capabilities and competencies needed to improve the performance of physical asset management (PAM).

The analytic hierarchy process (AHP) is used to select and prioritize the most appropriate factors for improving performance. A multi-criteria approach is used to analyze and compare the importance of 6 main criteria and 18 subcriteria identified from a survey of relevant literature.

The study revealed that not all factors are viewed as having equal importance in improving PAM performance, as three of the main factors attained greater importance among the six factors.

This study explored the factors required for managing assets only within the third stage of asset lifecycle, that is, the utilization stage. It is recommended that future studies be conducted in such a way as to determine the importance of similar factors in the other stages of the asset lifecycle, or to identify new factors and add new criteria.

Knowledge of the differential impacts of the factors on the performance of PAM can impact asset managers and decision makers in their allocation of resources and focus their work on the highest-ranked rather than the lowest-ranked factors. Also, AHP used provides an effective mean for asset managers to identify priorities among decision criteria in their organization.

To date, no study has explored the impact of six combined factors on the performance of PAM. Previous studies have found that these factors each had equal importance. However, their relative ranking in practice and when they appear together have remained unrecognized.

Smart cities provide fully integrated and networked connectivity between virtual/digital assets and physical building/infrastructure assets to form digital economies. However, industrial espionage, cyber-crime and deplorable politically driven cyber-interventions threaten to disrupt and/or physically damage the critical infrastructure that supports national wealth generation and preserves the health, safety and welfare of the populous. The purpose of this paper is to present a comprehensive review of cyber-threats confronting critical infrastructure asset management reliant upon a common data environment to augment building information modelling (BIM) implementation.

An interpretivist, methodological approach to reviewing pertinent literature (that contained elements of positivism) was adopted. The ensuing mixed methods analysis: reports upon case studies of cyber-physical attacks; reveals distinct categories of hackers; identifies and reports upon the various motivations for the perpetrators/actors; and explains the varied reconnaissance techniques adopted.

The paper concludes with direction for future research work and a recommendation to utilize innovative block chain technology as a potential risk mitigation measure for digital built environment vulnerabilities.

While cyber security and digitization of the built environment have been widely covered within the extant literature in isolation, scant research has hitherto conducted an holistic review of the perceived threats, deterrence applications and future developments in a digitized Architecture, Engineering, Construction and Operations (AECO) sector. This review presents concise and lucid reference guidance that will intellectually challenge, and better inform, both practitioners and researchers in the AECO field of enquiry.

In recent years, many organisations responsible for economic infrastructure have developed asset management systems to improve the financial and service performance of their facilities. Asset management is an integrated approach to improving the ability of an irrigation system to deliver water at a defined level of service in the most cost‐effective manner. This paper describes how the analytic hierarchy process (AHP) is applied to identify priorities for asset renewals in the La Khe irrigation scheme in North Vietnam. The AHP methodology was coupled with the expected maximum utility (EMU) to evaluate renewal priorities of assets grouped by types and by location within the hydraulic system.

The purpose of this paper is to explore and compare the asset management policies and practices of six Australian states – New South Wales, Victoria, Queensland, South Australia, Western Australia and Tasmania – to improve understanding of the policy context to best shape policy focus and guidelines. Australian state-wide asset management policies and guidelines are an emergent policy domain, generating a substantial body of knowledge. However, these documents are spread across the layers of government and are therefore largely fragmented and lack coherency.

The comparative study is based on the thematic mapping technique using the Leximancer software.

Asset management policies and guidelines of New South Wales and Victoria have more interconnected themes as compared to other states in Australia. Moreover, based on the findings, New South Wales has covered most of the key concepts in relation to asset management; the remaining five states are yet to develop a comprehensive and integrated approach to asset management policies and guidelines.

This review and its findings have provided a number of directions on which government policies can now be better constructed and assessed. In doing so, the paper contributes to a coherent way forward to satisfy national emergent and ongoing asset management challenges. This paper outlines a rigorous analytical methodology to inform specific policy changes.

This paper provides a basis for further research focused on analyzing the context and processes of asset management guidelines and policies.

The authors analyze the equilibrium effects of non-tradable assets on optimal policy portfolios. They study how the existence of non-tradable assets impacts optimal asset allocation decisions of investors who own such assets and of investors who do not have access to non-tradable assets.

In this theoretical analysis, the authors analyze a model with tradable and non-tradable asset classes whose cash flows are jointly normally distributed. There are two types of investors, with and without access to non-tradable assets. All investors have constant absolute risk aversion preferences. The authors derive closed form solutions for optimal investor demand and equilibrium asset prices. They calibrated the model using US data for listed equity, bonds and private equity. Further, the authors illustrate the sensitivities of quantities and prices with respect to the main parameters.

The study finds that the existence of non-tradable assets has a large impact on optimal asset allocation. Investors with (without) access to non-tradable assets tilt their portfolios of tradable assets away from (toward) assets to which non-tradable assets exhibit positive betas.

The model provides important insights not only for investors holding non-tradable assets such as private equity but also for investors who do not have access to non-tradable assets. Investors who ignore the effect of non-tradable assets when reverse-engineering risk premia from asset covariances and market capitalizations might severely underestimate the equity risk premium.

The authors provide the first comprehensive analysis of the equilibrium effects of non-tradability of some assets on optimal policy portfolios. Thus, this paper goes beyond analyzing the effects of market imperfections on individual portfolio choices.

Railway transport maintenance plays an important role in delivering safe, reliable and competitive transport services. An appropriate maintenance strategy not only reduces the assets’ lifecycle cost, but also will ensure high standards of safety and comfort for rail passengers and workers. In recent years, the majority of studies have been focused on the application of risk-based tools and techniques to maintenance decision making of railway infrastructure assets (such as tracks, bridges, etc.). The purpose of this paper is to present a risk-based modeling approach for the inspection and maintenance optimization of railway rolling stock components.

All the “potential failure modes and root causes” related to rolling stock systems are identified from an extensive literature review followed by an expert’s panel assessment. The failure causes are categorized into six groups of electrical faults, structural damages, functional failures, degradation, human errors and natural (external) hazards. Stochastic models are then proposed to estimate the likelihood (probability) of occurrence of a failure in the rolling stock system. The consequences of failures are also modeled by an “inflated cost function” that involves safety-related costs, corrective maintenance and renewal (M&R) costs, the penalty charges due to train delays or service interruptions as well as the costs associated with loss of reputation (or loss of fares) in the case of trip cancellation. Lastly, a time-varying risk-cost function is formulated to determine the optimal frequency of preventive inspection and maintenance actions for rolling stock components.

For the purpose of clearly illustrating the proposed risk-based inspection and maintenance modeling methodology, a case study of the Class 380 train’s pantograph system from a Scottish train operating company is provided. The results indicate that the proposed model has a substantial potential to reduce the M&R costs while ensuring a higher level of safety and service quality compared to the currently used inspection methodologies.

The railway rolling stocks should be regularly inspected and maintained so as to ensure network availability and reliability, passenger safety and comfort, and operations efficiency. Despite the best efforts of the maintenance staff, it is reported that a considerable amount of maintenance resources (e.g. budget, time, manpower) is wasted due to insufficiency or inefficiency of current periodic M&R interventions. The model presented in this paper helps the maintenance engineers to assess the current maintenance practices and propose or initiate improvement actions when needed.

There are few studies investigating the application of risk-based tools and techniques to inspection and maintenance decision making of railway rolling stock components. This paper presents a modeling approach aimed at planning the preventive repair and maintenance interventions for rolling stock components based on risk measures. The author’s model is also capable of incorporating real measurement information gathered at each inspection epoch to update future inspection plans.