A review on degradation models in reliability analysis

With increasingly complex engineering assets and tight economic requirements, asset reliability becomes more crucial in Engineering Asset Management (EAM). Improving the reliability of systems has always been a major aim of EAM. Reliability assessment using degradation data has become a significant approach to evaluate the reliability and safety of critical systems. Degradation data often provide more information than failure time data for assessing reliability and predicting the remnant life of systems. In general, degradation is the reduction in performance, reliability, and life span of assets. Many failure mechanisms can be traced to an underlying degradation process. Degradation phenomenon is a kind of stochastic process; therefore, it could be modelled in several approaches. Degradation modelling techniques have generated a great amount of research in reliability field. While degradation models play a significant role in reliability analysis, there are few review papers on that. This paper presents a review of the existing literature on commonly used degradation models in reliability analysis. The current research and developments in degradation models are reviewed and summarised in this paper. This study synthesises these models and classifies them in certain groups. Additionally, it attempts to identify the merits, limitations, and applications of each model. It provides potential applications of these degradation models in asset health and reliability prediction.

A review on reliability models with covariates

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semi-parametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

The explicit hazard model – part 1: theoretical development

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

Atomistic numerical investigation of single-crystal copper nanowire with surface defects

Based on the embedded atom method (EAM), a molecular dynamics (MD) simulation is performed to study the single-crystal copper nanowire with surface defects through tension. The tension simulations for nanowire without defect are first carried out under different temperatures, strain rates and time steps and then surface defect effects for nanowire are investigated. The stress-strain curves obtained by the MD simulations of various strain rates show a rate below 1 x 10(9) s-1 will exert less effect on the yield strength and yield point, and the Young's modulus is independent of strain rate. a time step below 5 fs is recommend for the atomic model during the MD simulation. It is observed that high temperature leads to low Young's modulus, as well as the yield strength. The surface defects on nanowires are systematically studied in considering different defect orientations. It is found that the surface defect serves as a dislocation source, and the yield strength shows 34.20% decresse with 45 degree surface defect. Both yield strength and yield point are significantly influenced by the surface defects, except the Young's modulus.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

Molecular dynamics study of dynamic buckling properties of nanowires with defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, the deformation properties of Cu nanowires with different single defects under dynamic compression have been studied. The mechanical behaviours of the perfect nanowire are first studied, and the critical stress decreases with the increase of the nanowire’s length, which is well agreed with the modified Euler theory. We then consider the effects to the buckling phenomenon resulted from different defects. It is found that obvious decrease of the critical stress is resulted from different defects, and the largest decrease is found in nanowire with the surface vertical defect. Surface defects are found exerting larger influence than internal defects. The buckling duration is found shortened due to different defects except the nanowire with surface horizon defect, which is also found possessing the largest deflection. Different deflections are also observed for different defected nanowires. It is find that due to surface defects, only deflection in one direction is happened, but for internal defects, more complex deflection circumstances are observed.

Advanced numerical characterization of mono-crystalline copper with defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, the mono-crystalline copper with different defects is investigated through tension and nanoindentation simulation. The single-crystal copper nanowire with surface defects is firstly studied through tension. For validation, the tension simulations for nanowire without defect are carried out under different temperatures and strain rates. The defects on nanowires are then systematically studied in considering different defects orientation distribution. It is found that the Young’s modulus is insensitive of surface defects and centro-plane defects. However, the yield strength and yield point show a significant decrease due to the different defects. Specially, the 〖45〗^° defect in surface and in (200) plane exerts the biggest influence to the yield strength, about 34.20% and 51.45% decrease are observed, respectively. Different defects are observed to serve as a dislocation source and different necking positions of the nanowires during tension are found. During nanoindentation simulation, dislocation is found nucleating below the contact area, but no obvious dislocation is generated around the nano-cavity. Comparing with the perfect substrate during nanoindentation, the substrate with nano-cavities emerged less dislocations, it is supposed that the nano-cavity absorbed part of the indent energy, and less plastic deformation happened in the defected substrate.

Atomistic exploration of deformation properties of copper nanowires with pre-existing defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, in this paper, the tensile deformation properties of Cu nanowires (NWs) with different pre-existing defects, including single surface defects, surface bi-defects and single internal defects, are systematically studied. In-depth deformation mechanisms of NWs with pre-existing defects are also explored. It is found that Young's modulus is insensitive to different pre-existing defects, but yield strength shows an obvious decrease. Defects are observed influencing greatly on NWs' tensile deformation mechanisms, and playing a role of dislocation sources. Besides of the traditional deformation process dominated by the nucleation and propagation of partial dislocations, the generations of twins, grain boundaries, fivefold deformation twins, hexagonal close-packed (HCP) structure and phase transformation from face-centred cubic (FCC) structure to HCP structure have been triggered by pre-existing defects. It is found that surface defect intends to induce larger influence to yield strength than internal defect. Most importantly, the defect that lies on slip planes exerts larger influence than other defects. As expected, it is also found that the more or longer of the defect, the bigger influence will be induced.

Measuring the realization of benefits from enterprise architecture management

Enterprise architecture management (EAM) has become an intensively discussed approach to manage enterprise transformations. While many organizations employ EAM, a notable insecurity about the value of EAM remains. In this paper, we propose a model to measure the realization of benefits from EAM. We identify EAM success factors and EAM benefits through a comprehensive literature review and eleven explorative expert interviews. Based on our findings, we integrate the EAM success factors and benefits with the established DeLone & McLean IS success model resulting in a model that explains the realization of EAM benefits. This model aids organizations as a benchmark and framework for identifying and assessing the setup of their EAM initiatives and whether and how EAM benefits are materialized. We see our model also as a first step to gain insights in and start a discussion on the theory of EAM benefit realization.

An exploration of the professional competencies required in engineering asset management

Engineering asset management (EAM) is a rapidly growing and developing field. However, efforts to select and develop engineers in this area are complicated by our lack of understanding of the full range of competencies required to perform. This exploratory study sought to clarify and categorise the professional competencies required of individuals at different hierarchical levels within EAM. Data from 14 interviews and 61 on-line survey participants has informed the development of an initial Professional Competency Framework. The nine competency categories indicate that Engineers working in this field need to be able to collaborate and influence others, complete objectives within organizational guidelines and be able to manage themselves effectively. Limitations and potential uses in practice and research for this framework are discussed.

An exploration of the professional competencies required in engineering asset management

Engineering asset management (EAM) is a rapidly growing and developing field. However, efforts to select and develop engineers in this area are complicated by our lack of understanding of the full range of competencies required to perform. This exploratory study sought to clarify and categorise the professional competencies required of individuals at different hierarchical levels within EAM. Data from 14 field interviews, 61 online surveys, and 10 expert panel interviews were used to develop an initial professional competency framework. Overall, nine competency clusters were identified. These clusters indicate that engineers working in this field need to be able to collaborate and influence others, complete objectives within organisational guidelines, and be able to manage themselves effectively. Limitations and potential uses of this framework in engineering education and research are discussed.

An empirical analysis of the factors and measures of Enterprise Architecture Management success

Enterprise Architecture Management (EAM) is discussed in academia and industry as a vehicle to guide IT implementations, alignment, compliance assessment, or technology management. Still, a lack of knowledge prevails about how EAM can be successfully used, and how positive impact can be realized from EAM. To determine these factors, we identify EAM success factors and measures through literature reviews and exploratory interviews and propose a theoretical model that explains key factors and measures of EAM success. We test our model with data collected from a cross-sectional survey of 133 EAM practitioners. The results confirm the existence of an impact of four distinct EAM success factors, ‘EAM product quality’, ‘EAM infrastructure quality’, ‘EAM service delivery quality’, and ‘EAM organizational anchoring’, and two important EAM success measures, ‘intentions to use EAM’ and ‘Organizational and Project Benefits’ in a confirmatory analysis of the model. We found the construct ‘EAM organizational anchoring’ to be a core focal concept that mediated the effect of success factors such as ‘EAM infrastructure quality’ and ‘EAM service quality’ on the success measures. We also found that ‘EAM satisfaction’ was irrelevant to determining or measuring success. We discuss implications for theory and EAM practice.