Search results

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

This research aims to develop an approach to assess the reliability of integrated construction supply chains via an integrated model of building information modelling (BIM) and the lean supply chain (LSC). It reflects the synergistic workflow between BIM and LSC as a novel approach to improve the reliability of construction projects.

This research evaluates the reliability of the BIM-LSC approach through a combination of entropy theory, set pair analysis (SPA), and Markov chains (EESM). An exploratory survey was conducted to collect data from 316 industry professionals experienced in BIM and LSC. Subsequently, multiple cycles of calculations were performed with indirect data inputs. Finally, a reliability evaluation index is established for the BIM-LSC approach and potential applications are identified.

The results show that the EESM model of BIM-LSC developed in this study can handle not only supply chain reliability evaluation at a given state but also the prediction of reliability in supply chain state transitions due to changing project conditions. This is particularly relevant to the current environment of the construction project, which is characterised by an increasing level of complexity in terms of labour, technology, and resource interactions.

Future research could consider the accuracy and validity of the proposed model in real-life scenarios with by considering both quantitative and qualitative data across the entire lifecycle of projects.

The research offers a model to evaluate the reliability of the BIM-LSC approach. The accuracy of BIM supply chain reliability analysis and prediction in an uncertain environment is improved.

The BIM-LSC reliability evaluation and prediction presented in this study provides a theoretical foundation to enhance understanding of the BIM-LSC in the construction project context.

This study aims to develop a hierarchical reliability framework to evaluate the service delivery performance of education public–private partnerships (PPPs) effectively and efficiently during long-term operations.

The research design included development and test phases. In the development phase, three performance layers, i.e. indicator, component and system, in the education service delivery system were identified. Then, service component reliability was computed through first order reliability method (FORM). Finally, the reliability of the service system was obtained using dynamic component weightings. A PPP school example in Australia was set up in the test phase, where performance indicators were collected from relevant contract documents and performance data were simulated under three assumptive scenarios.

The example in the test phase yielded good results for the developed framework in evaluating uncertainties of service delivery performance for education PPPs. Potentially underperforming services from the component to the system level at dynamic timepoints were identified, and effective preventative maintenance strategies were developed.

This research enriches reliability theory and performance evaluation research on education PPPs. First, a series of performance evaluation indicators are constructed for assessing the performance of the service delivery of the education PPP operations. Then, a reliability-based framework for service components and system is developed to predict service performance of the PPP school operations with consideration of a range of uncertainties during project delivery.

The developed framework was illustrated with a real-world case study. It demonstrates that the developed reliability-based framework could potentially provide the practitioners of the public sector with a basis for developing effective preventative maintenance strategies with the aim of prolonging the service life of the PPP schools.

Evaluating education PPPs is challenging as it involves long-term measurement of various service components under uncertainty. The developed reliability-based framework is a valuable tool to ensure that reliability is maintained throughout the service life of education PPPs in the presence of uncertainty.

Reliability assessment does require an effective structural modelling approach for systems, in general and manufacturing systems are no exception. This paper aims to develop it for large manufacturing systems using graph models, a systems approach.

Structural graph models for reliability at various hierarchical levels are developed by considering a CNC cam shaft grinding machine. The system reliability expression is obtained by converting the reliability graphs into equivalent matrices, which helps to evaluate and analyse system.

Using the obtained reliability expressions at various hierarchical levels of the system, it is possible not only to evaluate its reliability from structure point of view but also to identify weak structural elements from reliability point of view.

The approach can be extended to include the influence of other parameters, such as human, component and environment, etc., on the system reliability.

The approach helps to design and develop manufacturing systems from reliability consideration by assessing their possible alternatives among these.

The suggested methodology is useful for reliability evaluation of large and complex manufacturing systems.

The reliability of accounting internal control systems (AICS) is often viewed as a primary concern of auditors. Over the past three decades, several reliability models have been proposed for internal control. The main goal of these models is to provide an objective approach to evaluate the reliability of internal control systems. In addition, the models seek to assess the degree of audit reliance that can be placed on internal controls. This paper has a two‐fold objective: (1) to present an overview of the descriptive and prescriptive reliability models developed for the design and evaluation of internal control systems, and (2) to discuss the effects of various factors on the reliability assessment. Furthermore, two methods to estimate process reliabilities are presented and several numerical examples are provided to show the detailed calculations of the reliability and economic efficiency of accounting internal control systems.

This study constructs a three-stage evaluation model for interdisciplinary organizations to solve their ranking problems effectively.

A three-stage interdisciplinary organization evaluation model abounds the key problems of “who will evaluate the projects?” and “how to evaluate the projects?”. In the first stage, the authors build a consensus maximization model to identify the selected experts based on the interval grey number because of the uncertainty in assessment. In the second stage, considering the reliability of the experts, the authors calculate the reliability of the experts based on historical data. Meanwhile, considering the gradual changes of the experts, the dynamic weighting method is obtained based on the clustering method. In the third stage, considering decision-makers regret psychological behavior, the authors construct a cross-organizational performance evaluation model based on consensus expectations.

First, for selecting the experts responsible for assessing interdisciplinary organizations, the consensus-reaching method can effectively avoid cognitive bias. Second, during the assessment, the authors obtained more reasonable results by considering the psychological changes of experts based on regret theory. Third, based on the results, the cross-organization of colleges focused on the achievements of talent training, cross effects, and system construction.

Our study could help organizations establish a suitable assessment mechanism and promote interdisciplinary development.

First, considering the importance of selecting the experts, the authors use the consensus-reaching process for expert selection. This method could guarantee most experts' preferences. Then, the authors propose a two-stage dynamic weighting method, including a pre-determined and adjusted process. The dynamic method can better perform the preferences of experts. Third, the authors studied the assessment in interdiscipline. In addition, based on the framework and considering the features of the interdiscipline, the authors use the grey number to perform the uncertain preferences of the experts using regret theory.

The purpose of this paper is to explore new ways and lay a solid foundation to solve the problem of reliability growth analysis of major aerospace equipment with various uncertainty data through propose new concepts of general uncertainty data (GUD) and general uncertainty variable (GUV) and build the operation system of GUVs.

The characteristics of reliability growth data of major aerospace equipment and the limitations of current reliability growth models have been analyzed at first. The most commonly used uncertainty system analysis methods of probability statistics, fuzzy mathematics, grey system theory and rough set theory have been introduced. The concepts of GUD and GUV for reliability growth data analysis of major aerospace equipment are proposed. The simplified form of GUV based on the “kernel” and the degree of uncertainty of GUV is defined. Then an operation system of GUVs is built.

(1) The concept of GUD; (2) the concept of GUV; (3) The novel operation rules of GUVs with simplified form.

The method exposed in this paper can be used to integrate complex reliability growth data of major aerospace equipment. The reliability growth models based on GUV can be built for reliability growth evaluation and forecasting of major aerospace equipment in practice. The reliability evaluation example of a solid rocket motor shows that the concept and idea proposed in this paper are feasible. The research of this paper opens up a new way for the analysis of complex uncertainty data of reliability growth of major aerospace equipment. Moreover, the operation of GUVs could be extended to the case of algebraic equation, differential equation and matrix which including GUVs.

The new concepts of GUD and GUV are given for the first time. The novel operation rules of GUVs with simplified form were constructed.

This paper seeks to introduce a set of key practices that can be used to assess whether an organization has the ability to design, develop and manufacture reliable electronic products.

The ability to design, develop and manufacture reliable electronic products is defined in the paper in terms of a reliability capability maturity model, which is a measure of the practices within an organization that contribute to the reliability of the final product, and the effectiveness of these practices in meeting the reliability requirements of customers.

The paper presents a procedure for evaluating and benchmarking reliability capability. Criteria for assigning different capability maturity levels are presented. The paper also presents a case study corresponding to reliability capability benchmarking of an electronics company.

The paper provides a set of practices for evaluating and benchmarking reliability capability.

Servitization of manufacturing is characterized by very complex decision processes within strongly unstable and uncertain decision contexts. Decision-makers are face situations of lack of internal and external information. The purpose of this paper is to develop a decision aid approach to support the management of servitization decision-making processes.

The scientific orientation of this research consists in working at improving the efficiency of the servitization decision-making process, by identifying factors of non-reliability, in order to propose remediation actions for the whole process. Improving the final decisions taken by the managers is considered as a consequence of the improvement of the decision-making process reliability. The method, based on modeling and evaluation, requires the specification of a decision process model for servitization, used as a basis to assess decision process reliability and diagnose the enterprise’s servitization decision system. Improving the final decisions made by the managers is considered as a consequence of the improvement of the decision-making process reliability.

Key added values: first, to formalize a servitization decision-making reference model; second, to specify a reliability assessment applied to the decision system; and third, to define a decision process reliability diagnosis procedure for servitization, illustrated in a case study.

A direct perspective is to complete the focus on procedural reliability, by taking into consideration the subjective rationality of decision-makers in the reliability assessment procedure. Additionally, this reliability assessment method and diagnosis could become the basis of a larger risk management approach for servitization.

The diagnosis procedure proposed in the paper is dedicated to generating practical results for enterprise decision-makers, consisting in recommendations for decision process improvements, in the context of servitization. The approach is illustrated through an industrial SME case study. The practical implications are highly contextualized.

The key originality of this research is to tackle servitization complexity with a decision system modeling and diagnosis orientation, including the formalization of the notion of “decision process reliability,” and the specification and implementation of a quantitative assessment procedure.

Patient experience (PE) evaluation can identify critical issues in healthcare quality. Various methods are used for PE evaluation in the healthcare system in Ontario; however, evidence suggests that PE evaluation is not systematically performed and has not received substantial buy-in from healthcare providers. This study explores the perspectives of healthcare providers, managers and policymakers in Ontario on PE evaluation methods, barriers, utility and reliability.

The study used a qualitative descriptive design. Twenty-one semistructured interviews were conducted with healthcare providers, managers and policymakers in Ontario between April 2018 and May 2019. The authors used thematic analysis to analyze the data. The Consolidated Criteria for Reporting Qualitative Research quality criteria were used.

Barriers to PE evaluation include evaluation cost and the time and effort required to collect and analyze the data. Several factors affect the reliability of the evaluation, resulting in an unrealistically high level of patient satisfaction. These include the inclusivity of evaluation, the subjective nature of patient feedback, patients' concerns about health service continuity and the anonymity of evaluation. Participants were skeptical about the meaningfulness of evaluation because it may only yield general information that cannot be acted upon by healthcare providers, managers and policymakers for quality improvement.

This paper reveals that many healthcare providers, managers and policymakers do not see a tangible value in PE evaluation, regardless of Ontario's patient-centeredness and “patient first” rhetoric. An improvement in evaluation methods and a cultural change in the healthcare system regarding the value of PE are required to foster a better appreciation of the benefits of PE evaluation.