Proceedings of the 7th World Congress on Engineering Asset Management (WCEAM 2012)

The shift from the traditional to the modern operational risk assessment and management forms in modern complex sociotechnical systems reflects some transitions from a human-focused perspective to a systemic-focused perspective. A key feature, in the later, is that when a human error is found, it is taken as the starting point for wider analysis of a system and not as the conclusion as it so often is in the human-focused perspective. This paper contributes with a comprehensive review of scholarly work aiming at assessing and elaborating on theoretical foundations of the developments that have been taking place within high-risk industries. Some interesting distinctions could be found, mainly, between realist positions and constructivist epistemologies. Both developments show the relevance of taking into account the philosophical antecedents of applied research in explaining the modern trends and how this is valuable toward new paradigms to resolve risk assessment and management issues relating to complex systems, particularly when the dynamics of human, technological, and organizational issues take into perspective.

Many accident causation models/theories have been dominating the human factors literature from a range of viewpoints and in a variety of different industrial contexts. However, many of the theories/models have limited applications with respect to capturing the underlying accident causations in modern complex systems. As a result, we seem to be moving toward new incident potentials, particularly in high-risk industries. As observed, major accidents keep occurring that have similar systemic causes in different contexts. This creates serious doubts that the existing analysis methods are capable of discovering the underlying causality in new complex settings, and/or how do we transfer what we learn from past to new contexts. Many of the approaches to safety focus on enforcing ‘defenses,’ i.e., physical, human, and procedural barriers. This perspective has limited view of accident causality, as it ignores today’s changing factors in emerging complex work systems and their interactions that generate various potentially unintended situations and shape the work behavior. Understanding and addressing these causal factors is therefore necessary to develop effective accident prevention strategies. Thus, this paper reviews the popular theories/models, by focusing on the developments in modern industrial environments toward more complex systems and interactive or collaborative operations. Accident models founded on basic systems theory concepts, which endeavor to capture the underlying accident causality and complexity of modern socio-technical systems from a broad systemic view, are analyzed and new insights for future accident analysis efforts are identified.

Capital development of an oil and gas refinery involves the establishment of a large base of engineering assets. In developing countries, the question arises as to the capacity of local firms to supply the required technological capabilities while operating under regimes that vibrantly promote indigenization and empowerment legislations. By analyzing the capability of local vendors, this paper provides some insight into the perplexing challenges presented by the need to create and build local science, technology, and innovation (STI) capacity. Despite a vigorous empowerment regime, the local market more or less features agents, distributors, and vendors of sources of technological capabilities that are located well outside the sociopolitical environment of the refinery project.

Weather, well bore characteristics, tools and equipment failures, and other sources of risk aggregate into non-productive times (NPT) which, in turn, adversely impact on the efficiency and costs of drilling crude oil wells. The imperative is to increase efficiency and reduce the cost of drilling operations, especially for offshore locations where the high temperature and pressure conditions mean that the window between reservoir pore pressures and fracture gradients can be quite narrow. By analyzing data on drilling rigs from three operators, the paper provides insight into some of the prevalent reasons why NPT account for more than 30 % of the budget for oil well construction in the geographical area under study.

Profitable production demands continuously improved maintenance decision accuracy for reducing/avoiding failures and unplanned stoppages due to their consequences. More accurate decisions prolong life length of components, and consequently machines, and maintain the production running longer. When a condition-monitoring (CM) value exceeds a significant (warning) level, it demands a clear understanding of what happened and how it will develop in the next future to avoid failures. In addition to CM it demands reliable information concerning the probability of failure, residual lifetime, and when is the most profitable time of conducting maintenance. Companies strive to reduce production cost in order to increase the possibility of offering customers lower prices and generating additional competitive advantages. But applying new technologies for enhancing maintenance, production performances, and company competitiveness counters many problems in industry. In this paper, a new innovative e-maintenance decision support system (eMDSS) is introduced; the problems facing successful implementation of eMDSS based on a case study are introduced and discussed. Solutions to avoid the problems facing successful implementation of eMDSS are suggested and discussed. eMDSS offers a unique opportunity to achieve just in time dynamic and cost-effective maintenance by selecting the most profitable time for maintenance.

Public awareness of infrastructure projects, particularly roads, many of which are delivered through networked arrangements, is high for several reasons. Such projects often involve significant public investment; they may involve multiple and conflicting stakeholders and can potentially have major environmental impacts. To produce positive outcomes from infrastructure delivery, it is imperative that stakeholder “buy in” be obtained particularly about decisions relating to the scale and location of infrastructure. Given the likelihood that stakeholders will have different levels of interest and investment in project outcomes, failure to manage this dynamic could potentially jeopardize project delivery by delaying or halting the construction of essential infrastructure. Consequently, stakeholder engagement has come to constitute a critical activity in infrastructure development delivered through networks. To guide infrastructure governance networks in the undertaking stakeholder engagement, this paper proposes and tests a domain-based model of stakeholder engagement.

The popular discussion of sustainability, its importance, and the need for its systematic assessment opened up many research venues and has led to the development of a variety of methods to measure and improve sustainability performance. While there have been some genuine efforts on developing life cycle-based research regimes, most of these efforts and subsequent solutions have seemingly been limited to the products and processes within the firms’-specific physical or organizational boundaries. In this paper, the authors argue that concentration on firms’ boundaries to improve sustainability performance is ineffective. This paper, therefore, brings a network-based approach into perspective for a systemic and dedicated sustainability performance improvement that extends beyond the prevailing firm-based approach. Shortcomings of firm-based approaches are highlighted, and how they can be avoided in a network setting will be outlined.

There are a variety of existing frameworks that specify what to measure and how to improve on sustainability performance and there is constant discussion on indicators for performance assessment. Current practice mostly relates to firm-centric approaches, however and thereby neglects the realities of a networked manufacturing environment. In this paper, we argue for sustainability performance assessment that extends beyond firm boundaries and incorporates dyadic characteristics that affect internal performance levers. It thereby links performance outcome, internal performance levers, and network conditions through causal relationships. The framework takes into account existing interdependencies between different firms within a manufacturing network and thus provides the means for more realistic sustainability assessment.

The failure in rolling element bearings as an important part of rotary machine can lead to machine breakdown. Finding a good strategy for fault diagnosis can help to reduce maintenance cost and enhance reliability. The S-statistic based on the comparison of two reconstructed attractors (RA's) in the phase space was applied to diagnose different types of faults in bearings (inner, ball, and outer faults). To achieve the aim, measured signals of a normal bearing and several faulty bearings were decomposed to sub-signals by wavelet packet so that frequency of each defect is located in a unique packet. Comparing the result for normal and faulty sub-signals using the S-statistic indicate that the method can be applied for fault diagnosis.

With more than half of the world’s population living in urban areas and the rate of urbanization on the increase, there is a continuous and increasing demand for infrastructure and services in these areas. In addition to this growing demand, climate change adds a whole new dimension that compels a relook at our asset management procedures for the critical urban infrastructure. For a considerable time now, mitigation strategies have played an important role in various policy decisions. There is a recent trend in the scientific, geographic, institutional, and business domains that mitigation alone cannot be seen as an effective strategy to limit our vulnerability to the causes and consequences of climate change. Adaptation strategies must also form a part of our efforts, policies, discussions, and planning procedures. In this paper, we present a discussion on how an equal importance to adaptation strategies is being advocated, in conjunction with mitigation strategies, for infrastructure. We review some relevant literature that promotes both these strategies either individually or collectively in relation to infrastructure and services.

This paper reviews the extant literature about engineering asset management (EAM), which highlights that organizational and cultural change may be required to develop effective asset management practices. As such, this study uses the competing value framework (CVF) and professional theories to reposition the role of professional and organizational culture and support changes in the workplace practices of engineers working in asset management organizations. In particular, a process is proposed for assessing the current organizational culture of asset management firms to determine whether the environment is conducive for supporting improvements in the overall asset management performance. The methods suggested in this paper include interviews and the development of a survey instrument, comprising the OCAI and other relevant questions about EAM employees’ work practices. This tool is yet to be tested and applied to examine organizational culture within a professional asset management context. The evidence-based information from this study can be used by management to identify current and preferred work practices. In particular, the information is used to identify whether and what change is required to maximize employees’ performance. The study expects to identify new information about best work practices required to support the successful implementation of asset management practices. This information can be used as a platform to provide evidence-based strategies for realigning organizational goals with the goals of the individual employees to improve asset management capability.

Vibration-based condition monitoring and prognostic of rotating element bearings have been studied. Satisfactory methods on how identify bearing fault and lifetime prediction have been shown in literature. There are two characteristics of the investigated bearings in the literature: (1) The bearings were run in moderate and high rotating speed and (2) damage was artificially introduced, e.g., artificial crack and seeded fault. This paper deals with slewing bearing with very low rotational speed (1 and 4.5 rpm) with natural fault development. Two real vibration data are discussed, namely data obtained from laboratory slewing bearing test-rig and data from a sheet metal company. In this study, the result of EMD and EEMD applied in two real cases were shown superior compared to FFT method.

Pneumatic conveying is a process of transporting particulate material through pipelines using compressed gas. As material is conveyed through pipeline and bends, the pipeline especially after bends suffers severe wear due to particles’ interactions with the surfaces. Removal of material from solid surfaces by action of impinging particles is known as erosion. It is well known that particle velocity and impact angle play a major role in determining the material removal rate from the surface. In a recent study, it was demonstrated that materials’ response to deformation during impacts dictates how the material is removed from the surface. This paper presents the surface characteristics of ductile materials due to single-particle impacts as well as standard erosion using micro-sand blaster. Surface and subsurface damage characteristics with respect to the impact parameters as well as particles’ angularity have been presented. Aluminum and mild steel surfaces impacted by spherical zirconia and angular alumina particles have been analyzed using scanning electron microscope (SEM). Finally, the material removal mechanisms have been discussed with respect to the service life of pneumatic conveying pipelines.

Pneumatic conveying is a frequently used method of material transport particularly for in-plant transportation over relatively short distances. This is primarily to exploit the degree of flexibility it offers in terms of pipeline routing as well as dust minimization. Approximately 80 % of industrial systems are traditionally dilute phase system which uses relatively large amount of air to stay away from trouble, such as blocking the pipeline. Wear in pneumatic conveying is a very complex problem, and at present, there is limited understanding of the wear mechanisms responsible for the severe wear in certain areas of the pipeline. One of the recent studies [

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] showed that the surface modifications by conveying materials can alter surface characteristics which change the wear mechanisms of the pipeline. Better understanding of the surface modifications and their effects on wear mechanisms can play a significant role in developing predictive models for the service life of pneumatic conveying pipelines. In this paper, wear surfaces from fly ash conveying pipeline have been studied for a better understanding of the surface modification and its effects of wear mechanisms. Wear samples were analyzed using SEM Energy Dispersive X-ray Spectroscopy (SEM-EDS). Analysis of surface elements discovered high level of silicon (Si) and aluminum (Al) present in the modified surface areas which apparently responsible for brittle failure of the surface layer. Although the actual form of the chemical compounds has not been analyzed, it is evident that the surface modification by the constituents of the conveying material is one of the major contributors to the severity of wear in fly ash conveying pipelines.

Infrastructure is understood as a lifeline network for the society. As facilities are connected with each other, failure or poor performance of a facility in the network affects the rest of the network resulting in the overall performance deterioration. Social infrastructures such as roads, bridges, water supply, wastewater treatment, parks, and public buildings are all connected each other. Failure and or poor performance of an infrastructure would result the poor-performance infrastructure network. In order to keep the overall performance of the infrastructure network at certain level, the performance level of different facilities should be maintained in balance, i.e., performance leveling. Managing different facility in same level of performance is like comparing the qualities of oranges and apples. However, the facility managers must compare the performance of roads, bridges, water supplies, public buildings and parks in order to allocate appropriate budget to maintain those facilities at almost same level of performance. Authors have developed a method to normalize the level of service of infrastructure to compare different type of infrastructure performing at same level of service. First, levels of service indicators have been identified; then, they have been converted into normalized values, which are used as cross-asset management. Normalization factors were derived from surveying of users and statistically calibrated to remove the biases. This paper describes the development of level of service indicators and normalization methods for cross-asset management.

There is a wealth of asset information in the design environment that is necessary in the operational environment to effectively manage the asset. However, the asset design information model is typically a complex structure that requires in-depth knowledge of the model to access the necessary information. Currently, there are no well-defined methodologies to extract the relevant design information that is needed in the asset operational domain. In addition, there are no well-defined methods to define the relationships between the terms and definitions common to the design environment and the operational environment. In this paper, we will propose the use of an open technical dictionary and an information exchange approach based on ISO 18435 to organize the relevant information to achieve interoperability of applications in both design and operational environments.

Many researchers in the field of civil structural health monitoring (SHM) have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Fieldwork has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. Informed by a brief review of the literature, this paper documents the design and proposed test plan of a structurally complex laboratory bridge model that has been specifically designed for the purpose of SHM research. Preliminary results have been presented in the companion paper.

Many researchers in the field of civil structural health monitoring have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Field work has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. This paper presents some preliminary results of experimental modal testing and analysis of the bridge model presented in the companion paper, using the peak picking method, and compares these results with those of a simple numerical model of the structure. Three dominant modes of vibration were experimentally identified under 15 Hz. The mode shapes and order of the modes matched those of the numerical model; however, the frequencies did not match.

One of the fastest growing industries—aviation—faces serious and compounding challenges in maintaining healthy relationships with community stakeholders. One area in aviation-creating community conflict is noise pollution. However, current understandings of the factors that affect noise annoyance of the community are poorly conceptualized. More importantly, the way community needs and expectations could be incorporated in airport governance has been inadequately framed to address the issue of aircraft noise. This paper proposes the utility of adopting an integrated strategic asset management (ISAM) framework [

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] to explore the dynamic nature of relationships between and airport and its surrounding area. The case of the Gold Coast Airport (OOL) operator and community stakeholders is used. This paper begins with an overview of the ISAM framework in the context of airport governance and sustainable development—as a way to find a balance between economic opportunities and societal concerns through stakeholder engagement. Next, an exploratory case study is adopted as a method to explore the noise-related complaints, complainants, and possible causes. Following this, the paper reviews three approaches to community stakeholder engagement in Australia, Japan, and UK and discusses their implications in the context of OOL. The paper concludes with a contention that airport governance is likely to be much more effective with the adoption of ISAM framework than without it.

Companies are continuously striving for world-class performance by use of various performance management tools and techniques. One such popular technique, proving effective in achieving best-in-class results, is benchmarking. A case study of an oil and gas production company, aiming to drive business performance based on best practice-based learning rather than compliance, shows how benchmarking can be effectively implemented to maintain continuous improvement. Benchmarking practice is assessed across a variety of different departments affecting operations, giving an insight into the diversity and complexities of implementing the practice yet paying attention on learning opportunities, while maintaining focus on the ultimate goal of achieving world-class performance.

Contrary to traditional management style, where new managers would introduce immediate drastic changes in an attempt to create short-term impact, more contemporary performance management philosophies rely on embracing and further developing existing internal practices and operating cultures toward world class. Building on the vast knowledge and experience available within the performance management systems of one of the world’s largest oil and gas production companies, an Integrated Benchmarking model is developed combining internal and external best practices and continuous improvement tools.

Road asset managers are seeking analysis of the whole road network to supplement statistical analyses of small subsets of homogeneous roadway. This study outlines the use of data mining capable of analyzing the wide range of situations found on the network, with a focus on the role of skid resistance in the cause of crashes. Results from the analyses show that on non-crash-prone roads with low crash rates, skid resistance contributes only in a minor way, whereas on high-crash roadways, skid resistance often contributes significantly in the calculation of the crash rate. The results provide evidence supporting a causal relationship between skid resistance and crashes and highlight the importance of the role of skid resistance in decision making in road asset management.

Since late 80s and early 90s, the offshore oil and gas industry has seen a decline in the rate of large discoveries on the Norwegian Continental Shelf; moreover, a majority of fields on the NCS are mature. To cope with increasing risk and lower margins, integrated operations have become a modern solution that introduces novel business models innovations. This greatly opens up many opportunities for value creation, inclusive strong business-to-business relations, new organizational forms, and technological solutions that can improve decision making, operational effectiveness, safety, and production leading to increased recovery, lower operational costs, and extended field life. Collaborative operating environments are an important element of integrated operations, functioning as nodal points for data, people, decision, and work processes, and play an important role in bringing operators, service companies, and experts closer together in collaborative relationships. In this new operating environment, business-to-business relationships have a defining role in increasing value creating potential. This paper elaborates on the current performance gaps based on a project that aimed at identifying performance enhancement potential in B2B context, between operator and service companies in the oil and gas industry operating in collaborative operating environments.

Collaborative operating environments (COE) are a new concept for the offshore petroleum sector and have been introduced as a part of integrated operations as a solution to mitigate risks and to capitalize on value creating potentials. To some extent, military, aviation, and aerospace industries have used COE with encouraging success, yet still left with some notable challenges concerning modern developments in social, economical, technological, and political terms. To reflect on the developments in the Norwegian petroleum sector, the Norwegian Oil Industry Association (OLF) published a report in 2007 on the value potential for integrated operations, which concluded that a value of as much as 350 billion NOK could be realized by the offshore petroleum sector in Norway. However, realizing this value potential does not solely rely on pure technological innovations, but various other parameters that contribute to boost performance. This particularly involves relations and interactions between stakeholders of producing assets in COE—operational centers used in integrated operations. In a project conducted recently within the offshore petroleum sector, it was revealed that, regarding today’s implementation status of COE, there exist a number of performance gaps and challenges, particularly in the business relationships between operators and service companies. The findings from this project have been elaborated in another paper. As a continuing action, this paper tries to propose improvement solutions to capitalize on these performance gaps, create the right win–win scenario for all stakeholders, and present factors affecting performance in business-to-business (B2B) relationships.

Gartner suggested that 80 % of organizational data is unstructured and has not been made available to the users. As a result, most organizations have far more data than they possibly use, yet at the same time, they do not have the quality data they really need. With the participation of an Australian Power Utility Company, this research demonstrated the value of unstructured data found in the plant incident reports (which are Word documents stored in the public directory of the exchange server) by conducting text analysis with special in-house-developed software.

This paper addresses modeling of age-dependent failure tendency. The field data of an aircraft device record the follow-up start and end of the units and the failures in chronological order. The data are incomplete since they lack the exact age of the unit at some failures in a way that seems to be random. We construct a non-parametric point estimate of the nonlinear cumulative failure rate, and we model the failure point process behind. Firstly, we point out how effectively the quantiles of the distance to next failure capture and interpret the information in real data. Further, since the characteristics of the actual field data are recognizable enough, it is possible to generate artificial (bootstrap) data sets that imitate the field data set. Each simulated data set determines a nonparametric estimate of the cumulative failure rate, and these estimates together provide fully nonparametric bootstrap confidence bounds for the cumulative failure rate. For practical purposes, we carry out some computational demonstrations on how the data set size and the censoring rate affect the confidence bounds.

Engineering asset lifecycle management is information intensive. The variety of asset lifecycle processes generate, process, and analyze enormous amount of data on daily basis. Information systems utilized for asset management not only have to provide for the control of lifecycle management tasks, but also have to act as instruments for decision support. Asset lifecycle management can be viewed as a combination of decisions associated with strategic, planning, and operational levels of the organization. Information systems in asset management, in theory, thus facilitate data-enabled view of asset management. However, realization of such a view of asset lifecycle through information systems requires appropriate hardware and software applications; quality, standardized, and interoperable data; appropriate skill set of employees to process data; and the strategic fit between the asset lifecycle management processes data requirements and the information systems. This paper sketches out a framework for asset lifecycle management data governance, which highlights the rights and accountabilities related to asset data lifecycle management. The framework describes how common business data and metrics should be defined, propagated, owned, and enforced throughout the organization, thereby allowing for better quality and faster decision-making, business intelligence reporting, cost reductions, compliance, and better controls of business processes.

Information technologies (IT) implementation in asset managing organizations does not follow a linear path. It is primarily driven by cost concerns, rather than an approach that takes into account the existing technological infrastructure, business requirements, available skill base, social and cultural environment, and operational and strategic value of technology investment. This paper presents a case study of information technologies implementation in Australian asset managing organizations. It concludes that technology for asset management needs to be physically adopted, and socially and organizationally composed, to create consensus on what the technology is supposed to accomplish and how it is to be utilized.

This paper presents an experimental study on the vibration signal patterns associated with a simulated piston slap test of a four-cylinder diesel engine. It is found that a simulated worn-off piston results in an increase in vibration RMS peak amplitudes associated with the major mechanical events of the corresponding cylinder (i.e., inlet and exhaust valve closing and combustion of Cylinder 1). This then led to an increase of overall vibration amplitude of the time-domain statistical features such as RMS, crest factor, skewness, and kurtosis in all loading conditions. The simulated worn-off piston not only increased the impact amplitude of piston slap during the engine combustion, but it also produced a distinct impulse response during the air induction stroke of the cylinder attributing to an increase of lateral impact force as a result of piston reciprocating motion and the increased clearance between the worn-off piston and the cylinder. The unique signal patterns of piston slap disclosed in this paper can be utilized to assist in the development of condition-monitoring tools for automated diagnosis of similar diesel engine faults in practical applications.

An effective prognostics program will provide ample lead time for maintenance engineers to schedule a repair and to acquire replacement components before catastrophic failures occur. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique. For comparative study of the proposed model with the proportional hazard model (PHM), experimental bearing failure data from an accelerated bearing test rig were used. The result shows that the proposed prognostic model based on health state probability estimation can provide a more accurate prediction capability than the commonly used PHM in bearing failure case study.

Asset management supports long-term planning of physical assets and offers a structured approach for more sustainable manufacturing. Asset management aims to improve profitability of the production by supporting life cycle decision making by developing and applying optimal maintenance, capacity planning, and investment strategies. So far the impacts of networked business models and demands for sustainability have not been widely dealt with. The paper presents results from a road map exercise that aimed to identify future needs for sustainable manufacturing models, and focuses on the use of company networks for efficiency of physical assets. The main research questions addressed here are as follows: How does asset management contribute to the demands for more sustainable manufacturing and what implications the demand for more sustainable manufacturing has to asset management strategies?

The importance of materials management systems (MMS) is critical for an asset managing organization because of the role that these systems play in asset life cycle management. However, it is essential that these systems acquire, exchange, and process quality information. It is the quality of information held in MMS that eventually decides the credibility of the decision making regarding materials management, maintenance, and asset life cycle support. At the same time, asset management paradigm has moved toward mobile environment, where the demand of practitioners is that of real-time operation and availability of information. Information quality (IQ), however, has a number of technical, organizational, and people components. Each of these components affects the various IQ dimensions, such as accuracy, consistency, timeliness, and ease of operation. In order to improve IQ, it is important to know the relationship of these dimensions with the characteristics of the system. Therefore, this paper categorizes IQ dimensions according to the requirements associated with major functions of mobile MMS and identifies the types of IQ dimensions that are the most relevant in mobile environments.

Time-varying mesh stiffness is a periodic function caused by the change of the number of the contact tooth pairs and the contact positions of the gear teeth. In this study, we have derived the analytical equations of the time-varying mesh stiffness of a planetary gear set using the potential energy method. Three simulations are conducted with a common planetary gear set under fixed carrier, fixed ring gear, and fixed sun gear. The results indicate that the obtained time-varying mesh stiffness can reflect the stiffness variation, and the proposed approaches can be extended in the future to model the stiffness of a planetary gear set when faults are introduced.

This paper presents an experimental study on the vibration signal patterns associated with a simulated piston slap test of a four-cylinder diesel engine. It is found that a simulated worn-off piston results in an increase in vibration root-mean-square (RMS) peak amplitudes associated with the major mechanical events of the corresponding cylinder (i.e., inlet and exhaust valve closing and combustion of Cylinder 1). This then led to an increase of overall vibration amplitude of the time-domain statistical features such as RMS, crest factor, skewness, and kurtosis in all loading conditions. The simulated worn-off piston not only increased the impact amplitude of piston slap during the engine combustion, but also produced a distinct impulse response during the air induction stroke of the cylinder attributing to an increase of lateral impact force as a result of piston reciprocating motion and the increased clearance between the worn-off piston and the cylinder. The unique signal patterns of piston slap disclosed in this paper can be utilized to assist in the development of condition monitoring tools for automated diagnosis of similar diesel engine faults in practical applications.

Popular understanding today characterizes human as an asset of an organization. On the contrary, various industrial cases often conclude human error as a major cause for unwanted events and incidents. Subsequently, much focus over the years has been paid on the human reliability, human error etc. Under this conventional focus lies the hidden presumption that performances and behaviors can be controlled or regulated by various technical, operational, and managerial means. These imply that humans take up a dual role in the use and operation of industrial systems; an asset on certain occasions and/or a liability on the others. This paper takes a critical look at this dual role with respect to the developments that has taken place over thousands of years and the nature of industrial systems that have been developed as well as those that are emerging. It strongly argues that the very nature of the humans are not understood or incorporated in the design, deployment, and operationalization of industrial systems. With respect to the complexity and dynamics of emerging systems, this has very sensitive implications in terms of safety and security.

The ultimate goal of collaborative operating environments was value creation. All over the world, expert systems (ES) are being employed by various industrial sectors to foster this value creation process. Subsequently, under the umbrella of integrated operations (IO), this paper examines the current role and use of expert systems for value creation in the Norwegian offshore oil and gas (O&G) industry within the field of asset maintenance. Through comprehensive literature reviews, vendor surveys, and interactions with industry experts, the paper concludes that the Norwegian O&G industry closely mimics the global O&G industry in its adoption and use of expert systems technology. This study also reveals an apparent lack of widespread adoption of ES within maintenance is a contributory factor to the proliferation of preventive maintenance strategies on the Norwegian continental shelf.

Expert systems (ES) broaden the possibilities for solving complex practical challenges, providing quick decision support, particularly when operations become complicated and collaborative. Such systems can contribute to improve overall technical integrity of offshore asset, subsequently creating value for oil and gas (O&G) companies. Consequently, this paper summarizes the results of the data collected through multiple case studies to investigate how sophisticated tools and technologies, such as ES, can contribute to improve the technical integrity of assets and add value to the Norwegian continental shelf (NCS) under the new operating environment known as integrated operation (IO). The paper highlights the potential of ES to be effectively deployed for real-time decision-making, enhancing predictive/dynamic maintenance capabilities, improving equipment reliability and availability, and optimizing work planning and resource allocation. Given the practical complexities of IO, the paper also identifies potential challenges, obstacles, and factors in the use of such advanced applications.

This paper presents a study whereby a series of tests was undertaken using a naturally aspirated, 4-cylinder, 2.216 L, Perkins diesel engine fitted with a piston having an undersized skirt. This experimental simulation resulted in engine running conditions that included abnormally high levels of piston slap occurring in one of the cylinders. The detectability of the resultant diesel engine piston slap was investigated using acoustic emission signals. Data corresponding to both normal and piston slap engine running conditions were captured using acoustic emission transducers along with both in-cylinder pressure and top-dead centre reference signals. Using these signals, it was possible to demonstrate that the increased piston slap running conditions were distinguishable by monitoring the piston slap events occurring near the piston mid-stroke positions. However, when monitoring the piston slap events occurring near the TDC/BDC piston stroke positions, the normal and excessive piston slap engine running conditions were not clearly distinguishable.

Asset service organizations often recognize asset management as a core competence to deliver benefits to their business. But, how do organizations know whether their asset management processes are adequate? Asset management maturity models, which combine best practices and competencies, provide a useful approach to test the capacity of organizations to manage their assets. Asset management frameworks are required to meet the dynamic challenges of managing assets in contemporary society. Although existing models are subject to wide variations in their implementation and sophistication, they also display a distinct weakness in that they tend to focus primarily on the operational and technical level and neglect the levels of strategy, policy, and governance as well as the social and human resources—the people elements. Moreover, asset management maturity models have to respond to the external environmental factors, including climate change and sustainability, stakeholders, and community demand management. Drawing on five dimensions of effective asset management—spatial, temporal, organizational, statistical, and evaluation—as identified by Amadi-Echendu et al. [

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], this paper carries out a comprehensive comparative analysis of six existing maturity models to identify the gaps in key process areas. Results suggest incorporating these into an integrated approach to assess the maturity of asset-intensive organizations. It is contended that the adoption of an integrated asset management maturity model will enhance effective and efficient delivery of services.

The policies and regulations governing the practice of state asset management have emerged as an urgent question among many countries worldwide for there is heightened awareness of the complex and crucial role that state assets play in public service provision. Indonesia is an example of such country, introducing a ‘big bang’ reform in state asset management laws, policies, regulations, and technical guidelines. Indonesia exemplified its enthusiasm in reforming state asset management policies and practices through the establishment of the Directorate General of State Assets in 2006. The Directorate General of State Assets have stressed the new direction that it is taking state asset management laws and policies through the introduction of Republic of Indonesia Law Number 38 Year 2008, which is an amended regulation overruling Republic of Indonesia Law Number 6 Year 2006 on Central/Regional Government State Asset Management. Law number 38/2008 aims to further exemplify good governance principles and puts forward ‘the highest and best use of assets’ principle in state asset management. The purpose of this study is to explore and analyze specific contributing influences to state asset management practices, answering the question why innovative state asset management policy implementation is stagnant. The methodology of this study is that of qualitative case study approach, utilizing empirical data sample of four Indonesian regional governments. Through a thematic analytical approach, this study provides an in-depth analysis of each influencing factors to state asset management reform. Such analysis suggests the potential of an ‘excuse rhetoric’; whereby the influencing factors identified are a smoke-screen, or are myths that public policy makers and implementers believe in, as a means to explain stagnant implementation of innovative state asset management practice. Thus, this study offers deeper insights into the intricate Web that influences state asset management innovative policies to state asset management policy makers; to be taken into consideration in future policy writing.

Policy Delphi was first introduced in 1969, and it is a process that seeks to generate the strongest possible opposing views on the potential resolutions of a major policy issue, such as strategy and policy for infrastructure and engineering asset management within organizations. The objectives of the Policy Delphi are to: ensure that all possible options have been tabled for consideration; estimate the impact and consequences of any particular option; and examine and estimate the acceptability of all the individual options. There are six phases that include formulation of the issues, identifying options, determining initial positions on the issues, exploring and obtaining the reasons for disagreements, evaluation, and finally, reevaluation of options. The methodology relies on a two-round limit by utilizing the following procedures: (a) The monitor team devoting a considerable amount of time to carefully pre-formulate the obvious issues; (b) Seeding the list with an initial range of options but allowing for the respondents to add to the lists; and (c) Asking for positions on an item and establishing underlying assumptions in the first round. The research investigates what kind of asset management experts is needed to determine the scope of policy requirements for this process? The paper provides a case study of a Policy Delphi to elaborate the efficacy of this method for asset-intensive organizations to develop strategic policy.

Cavitation is one of the major problems associated with the operation of centrifugal pumps. Cavitation occurs when vapor bubbles that are formed due to a drop in pressure in the pipes upstream of the centrifugal pump implode under the added pressure within the volute of the pump. These implosions wear away the impeller, and sometimes the volute itself, which if left unchecked, would render the pump inoperable. Much research has been done in the detection of cavitation through: indicators in certain audible frequencies, drop in the net positive suction head (NPSHa), visual inspection using a transparent casing and a stroboscopic light, paint erosion inside the volute, and on the impeller, changes in pressure within the flow or volute, and vibration within certain frequency ranges. Vibration detection is deemed as one of the more difficult methods due to other structural and environmental factors that may influence which frequencies may be present during the onset of cavitation. Vibration measurement, however, is most easily measured and deployable in an automated condition monitoring scenario. It is proposed that an increasing trend in a set of statistical parameters, rather than a firm threshold of a single parameter, would provide a robust indication for the onset of cavitation. Trends in these statistical parameters were obtained from data collected on a pump forced to cavitate under several different operating conditions. A single cavitation indicator is outlined utilizing these statistical parameters that can quantify the level of cavitation in a centrifugal pump.

Steel markets are very competitive and demand greater gauge precision and higher production rates. These growing requirements result in tandem rolling mill, which is of substantial interest to the steel industry, in order to improve quality and productivity. In such an environment, it is important to construct appropriate condition monitoring, which can lead to achieving the highest economic efficiency and avoiding equipment damage. This paper proposes a comprehensive condition monitoring methodology based on statistical feature extraction technique to increase the efficiency of feature extraction from high-dimensional feature space. It is examined that one can explore easily the effective features by using three-dimensional feature space for the condition monitoring. The method has been applied on condition monitoring of the stationary rolling in steel industry.

This paper proposes an embedded system architecture for fault detection and prediction in electrical actuators used in pipelines for oil and gas transportation. The proposed system incorporates a signal processing flow that requires low complex mathematical operations using ANSI-C language. However, when described in the hardware description language (HDL), it can be implemented in dedicated field-programmable gate array (FPGA) or ASIC. To prove its functionalities, a test bench was developed, which aims to reproduce in a laboratory some common faults and degradation processes that may occur in real-world field applications. A data acquisition equipment was used to collect the sensors information from specific points of the actuator. The sensor data collected and simulation were used to validate the propose fault detection methodology.

The ability to detect and diagnose faults in rolling element bearings is crucial for modern maintenance schemes. Several techniques have been developed to improve the ability of fault detection in bearings using vibration monitoring, especially in those cases where the vibration signal is contaminated by background noise. Linear prediction (LP) and self-adaptive noise cancellation (SANC) are techniques which can substantially improve the signal to noise ratio of a signal, improving the visibility of the important signal components in the frequency spectrum. Spectral kurtosis (SK) has been shown to improve bearing defect identification by focusing on the frequency band with higher level of impulsiveness. In this paper, the ability of these three methods to detect a bearing fault is compared, using vibrational data from a specially designed test rig that allowed fast natural degradation of the bearing. The results obtained show that the SK was able to detect an incipient fault in the outer race of the bearing much earlier than any other technique.

There is an increasing awareness of sustainability and climate change and its impact on infrastructure and engineering asset management in design, construction, and operations. Sustainability rating tools have been proposed and/or developed that provide ratings of infrastructure projects in differing phases of their life cycle on sustainability. This paper provides an overview of decision support systems using sustainability rating framework that can be used to prioritize or select tasks and activities within projects to enhance levels of sustainability outcomes. These systems can also be used to prioritize projects within an organization to optimize sustainability outcomes within an allocated budget.

The expectation to integrate sustainability aspects (social, environmental, and economic success) into the design, delivery, and operation of infrastructure assets is growing rapidly and globally. There are now several tools and frameworks available to benchmark and measure sustainable performance of infrastructure projects and assets. This paper briefly describes the infrastructure sustainability (IS) rating tool developed by the Australian Green Infrastructure Council (AGIC) that was launched in February 2012. This tool evaluates sustainability initiatives and potential environmental, social, and economic impacts of infrastructure projects and assets. The rating tool provides the following benefits to industry: a common national language for sustainability; a vehicle for consistent application and evaluation of sustainability in tendering processes; assists in scoping whole-of-life sustainability risks, enabling smarter solutions that reduce risks and costs; fosters resource efficiency and waste reduction, reducing costs; fosters innovation and continuous improvement in sustainability outcomes; and builds an organization’s credentials and reputation in its approach to sustainability. The infrastructure types covered by this tool include transport, energy, water, and communication. The key themes of sustainability evaluation will be briefly presented in this paper, and they include management and governance; use of resources; emissions, pollution, and waste; ecology; people and place; and innovation.

The relationship between corporate and sustainability performance continues to be controversial and unclear, not withstanding numerous theoretical and empirical studies. Despite this, views on corporate responsibilities “meet where management can show how voluntary social and environmental management contributes to the competitiveness and economic success of the company.” This approach is fundamental to the business case for infrastructure sustainability. It suggests that beyond-compliance activities undertaken by companies are commercially justified if they can be shown to contribute to profitability and shareholder value. Potential public good benefits range across a wide spectrum of economic (for example employment, local purchasing, reduced demand for electricity generation), social (indigenous employment and development, equity of access), and environmental (lower greenhouse gas emission, reduced use of non-renewable resources and potable water, less waste, enhanced biodiversity). Some of these benefits have impacts that lie in more than one of the economic, social, and environmental areas of public goods. Using a sustainability rating schemes and potential business benefits from sustainability initiatives, this paper presents a brief summary of an online survey of industry that identifies how rating scheme themes and business benefits relate. This allows for a case to be built demonstrating which sustainability themes offer particular business benefits.

The nuclear power industry has historically been plagued with new plant deployment risks for engineering procurement and construction (EPC); project cost and schedule overruns present a risk to investors. These risks are anticipated to continue to hinder the growth of the nuclear industry, due to expected increased regulatory requirements due to the Fukushima Daiichi Nuclear Power Plant incident in March 2011. Although several risk management practices have been put in place, considerable cost and schedule excursions have continued to occur in the construction of recent nuclear power plant projects. We identify the limitations with current risk management practices by assessing the level of completeness of risk identification and accuracy of risk assessments on prior steam generator replacement (SGR) projects. SGR projects were chosen for this evaluation because their scope of work is characteristic of large nuclear power plant EPC projects.

Transformation of equipment manufacturers to become providers of industrial services is a trend that involves deep transformation of companies. Equipment manufacturers can potentially provide services significantly more efficiently and effectively by utilizing information about their installed base (IB). We aim to recognize decision support functionality and required information contents for a system that supports service business in the context of services like ‘full service’, lease of maintained equipment, extended warranties, and operations and maintenance. A further supported function is product and service development. Eight cases from Finnish machine-building and telecommunications industries provide a basis for our view of business needs in decision support of operational and tactical levels of service business management. We present a vision of a decision-making tool for service business of equipment manufacturers—the service business management environment (SBME)—and identify decision-making situations (‘use cases’) of SBME. SBME integrates ideas and information content from engineering asset management, condition-based maintenance, standards to represent and exchange life cycle, reliability and maintenance data, and e-maintenance. If successful, SBME can support transformation of equipment manufacturers to service business. This takes place by aggregating information from whole IB, which enables better accuracy in health assessment, prognostics, cost estimation, awareness of service contract status in terms of defined KPIs, and analysis of profitability of service offerings. Furthermore, SBME supports product development by providing information on field reliability, maintainability, recognition of epidemics, and other inputs.

Large-sized engineering assets, such as electrical transformers, are critical parts of the power supply chain. This research identifies the key parameters influencing transformer optimal operating conditions and asset life span management. Engineering asset research has developed few life span-forecasting methodologies for managing transformers in operation with respect to their maintenance, repair, and replacement policies. Using logistic regression (LR) models, this research develops an innovative transformer life span-forecasting approach and verifies the models with data from series of 161-kV transformers to improve the accuracy and efficiency for industrial applications. The transformer supplier and their stakeholders benefit from reliable and accurate asset life prediction, which enhances the reliability of decision making for engineering asset management.

In modern cities, natural gas is a major source of fuel that is needed in each resident’s daily life. Gas pipe risers are used to distribute natural gas to each household unit. They penetrate into each unit through concrete walls to connect the main outdoor gas pipe to the indoor residential gas pipes. After long periods of operation, part of the pipe riser embedded in concrete is prone to corrosion due to the combined effect of corrosive materials in concrete and humid environment. If the deterioration caused by the riser corrosion is ignored, pipe rupture and poisonous gas leaks are possible. In the worst-case scenario, catastrophic gas explosions can lead to human fatalities. Therefore, there is an urgent need for effective and reliable non-destructing testing methods that could enable the identification of corrosion in in-service through-wall riser so that the safety and proper maintenance of pipeline system in building can be guaranteed. This paper presents the application of advanced ultrasonic guided waves for this purpose. The problems and difficulties involved in the inspection including construction of transduction system and signal analysis of complex reflection wave signals will be identified and discussed. The experiments will be conducted to demonstrate the effectiveness of developed techniques. With the help of all of the achievements, the building is expected to become safer to live and hundreds of million dollars per year will be saved by avoiding potential gas explosions.

Public health data often consist of spatial information, which are correlated between cities. Some researchers point out that monitoring variability is often more critical and sensitive for health surveillance when focusing on the mutually correlated data. In this paper, we present a multivariate control chart, which is based on likelihood ratio tests, to detect the variance–covariance shift caused by a disease outbreak by extending the popular change-point detection scheme for monitoring the mean of the outbreak process. Two patterns of the variance–covariance matrix change frame, namely the ‘step change pattern’ and the ‘persistent change pattern,’ are explored in this study. When monitoring some disease data, the squared exponential function is used to calculate the variance–covariance matrix that describes the information given by the observed disease and the cities. Then, the maximum likelihood method is used to estimate the parameters of the variance–covariance matrix function. The effectiveness of the chart is proven by using two examples. During the study, we observe the performance of the extended model for monitoring the variance–covariance matrix. The results show that the extended chart can detect the variance–covariance shift. With the success in predicting the time that an outbreak of a disease could occur and its possible shift, the management teams of health department and hospitals can prepare all necessary remedy and proper action for such outbreak in advance.

For public and semipublic organizations, the use of risk assessment matrices is becoming a standard approach for asset management decisions. The risk matrix allows companies to assess the chance and effects of different risks with respect to proposed investment decisions. When the values in the risk matrix reflect the company values, the risk matrix allows for investment decisions to be made in line with these values and even for further strategic decision making. In this paper, we describe how a hierarchy of values can be used to uncover the core values of a company. These values are often shared by the people in a company and are institutionalized in core documents, such as the strategic vision or annual reports. We describe an approach in which we used value-focused thinking [

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] for the systematic elicitation of company values to determine the aggregation level of the values represented in the asset risk matrix of the Port Authority of Rotterdam (PoR).

Sewer systems are capital-intensive infrastructures, requiring appropriate asset management to safeguard serviceability. In the Netherlands, effective sewer asset management is described by De Leeuw’s control paradigm. Reliable data and information are key elements in decision making for rehabilitation and renewal of the assets. Rehabilitation is often based on limited asset condition information. Although various sources described procedures for guiding decision making for rehabilitation, it remains unclear which and how information sources are used in this process, and to what extent value trade-offs influence decisions. In order to improve current sewer asset management, this study assesses the availability and use of information in decision making for sewer system renewal in the Netherlands. Eighteen interviews were conducted at seven municipalities, combined with an analysis of their municipal sewerage plans. The interviewees described the decision making process and the information sources they use in this process. Decisions for sewer system renewal are often based on intuition in implicit risk analyses, where risk is defined as ‘feeling times consequence’. Sewer asset management is ineffective, because it relies mostly on intuition, hampering justification, accountability, and repetition of decisions and preventing evaluation. Evaluation procedures and a critical attitude toward relevancy and quality of information are recommended.

The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing, and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the KM field have showed that relational modes such as social capital is imperative for effective KM outcomes. In this paper, we argue that incorporating a relational approach to KM is more likely to contribute to the exchange of ideas and the development of creative responses necessary to improve decision making in asset management. This conceptual paper uses extant literature to explain KM antecedents and explore its outcomes in the context of asset management. KM is a component in the new integrated strategic asset management (ISAM) framework developed in conjunction with asset management industry associations (AAMCoG 2012) that improves asset management performance. In this paper, we use Nahapiet and Ghoshal’s [

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] model to explain antecedents of relational approach to KM. Further, we develop an argument that relational KM is likely to contribute to the improvement of the ISAM framework components, such as organizational strategic management, service planning, and delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.

In the Netherlands, the collection and processing of wastewater is executed by 415 municipalities (collection) and 25 water boards (processing). Those organizations have signed an agreement to reduce costs. Implementation of asset management is supposed to play a vital role in this cost reduction. In order to facilitate the implementation of asset management, the representative body of the industry [Stichting RIONED and STOWA (Dutch acronym for the Foundation for Applied Water Research)] envisioned an asset management guideline tailored to the specific needs of the wastewater industry. However, due to the diversity in size and scope of the asset managers to be and the assets in scope, it was not certain whether a single guideline would be possible nor if it would be cost-effective. To get a clearer view on those issues before committing large sums of money, the process of creating the guideline was split up in two phases. The first phase would result in a road map: design of the guideline, high-level planning of its realization, and the contours of a business case for implementation of asset management by means of the guideline. The second phase would then consist of actually realizing the guideline. In this paper, we describe the process we followed to arrive at the road map for the asset management guideline. The following can be concluded. Although the technical content of asset management for wastewater collection and wastewater treatment is very different, the process of management assets does not have to be different. By focusing on the asset management process, there was no need to distinguish wastewater treatment from wastewater collection. By making the guideline a collection of relative independent elements, it would do no harm to the concept of the guideline if in future elements would be added or removed.

A theoretically sound and accurate empirical hazard function may be used directly for analysis of lifetime distribution of the continuous-time failure data or can be used as a basis for further parametric modeling analysis in asset management. For the sake of bridging the gaps between probability theory and data analysis practice, this paper starts from clarifying the relationship between the concepts of hazard function and failure rate. Then, two often-used continuous-time data empirical hazard function formulas are derived directly from discrediting their theoretic definitions of the hazard function. The properties of these two different formulas are investigated, and their estimation performances against the true hazard function values are compared using simulation samples from exponential and Weibull distributions. Under the specified assumption conditions, both theoretic calculation and simulation results show that the formula that calculates the average failure rates (AFR) gives less biased estimation than the other one in all cases we have examined. We also showed that under practical situations, the relative difference of the calculated empirical hazards between these two formulas is less than 6 %. Based on the result of this study, we proposed a rule of thumb for applications of these two most often-used empirical hazard function formulas in data analysis practice.

Determining the condition as well as the remaining life of an insulation system is essential for the reliable operation of large oil-filled power transformers. Frequency-domain spectroscopy (FDS) is one of the diagnostic techniques used to identify the dielectric status of a transformer. Currently, this technique can only be implemented on a de-energized transformer. This paper presents an initial investigation into a novel online monitoring method based on FDS dielectric measurements for transformers. The proposed technique specifically aims to address the real operational constraints of online testing. This is achieved by designing an online testing model extending the basic “extended Debye” linear dielectric model and taking unique noise issues only experienced during online measurements into account via simulations. Approaches to signal denoising and potential problems expected to be encountered during online measurements will also be discussed. Using fixed-frequency sinusoidal excitation waveforms will result in a long measurement times. The use of alternatives such as a chirp has been investigated using simulations. The results presented in the paper predict that reliable measurements should be possible during online testing.