Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability最新文献

{"title":"Optimal condition based maintenance using attribute Bayesian control chart","authors":"H. Rasay, Seyed Mohammad Hadian, F. Naderkhani, Fariba Azizi","doi":"10.1177/1748006x231174960","DOIUrl":"https://doi.org/10.1177/1748006x231174960","url":null,"abstract":"Condition-based maintenance (CBM) has been emerged as a relatively new trend in maintenance management. Instead of conducting preventive maintenance actions in specified time intervals, the CBM program collects information through condition monitoring, then recommends maintenance actions based on the observed data. On the other hand, Bayesian control charts use the posterior probability of being the system in an unhealthy state as the chart statistic. An attribute Bayesian control chart is employed in this study to monitor a deteriorating system and plan CBM actions based on a continuous-time homogeneous Markov chain. The system consists of three states: healthy, unhealthy, and failure states. A partially observable Markov decision process (POMDP) is developed, which optimally determines the sample size, sampling interval, and warning limit to minimize the long-term expected cost per time unit. Numerical examples and sensitivity analyses are conducted to clarify the performance of the proposed attribute control chart. To the best of the authors’ knowledge, this is the first study of the applications of attribute Bayesian control charts in condition-based maintenance.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"30 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79815343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A virtual reality instrument to raise drivers’ awareness on safer driving through road tunnels","authors":"K. Kirytopoulos, Andreas Mourelatos, G. Chatzistelios, Panagiotis Ntzeremes, M. Konstantinidou","doi":"10.1177/1748006x231175719","DOIUrl":"https://doi.org/10.1177/1748006x231175719","url":null,"abstract":"Studies reveal that drivers’ behavior is the most significant factor in road accidents worldwide. Regarding tunnels, which are the most critical element of road infrastructure, despite the significant efforts that have been conducted toward the enhancement of drivers’ education all these years, studies illustrate that there are still serious deficiencies need to be tackled. To address this issue, this research endeavor develops a virtual reality tool based on the serious game idea in order to inform and educate potential users about the specific rules and behavioral patterns that should govern their safe driving when passing through tunnels. To do so, the appropriate behavioral patterns are determined using applicable norms and guidelines while the specific educational requirements are identified. Following that, the novel tool for training users is developed. The tool consists of a virtual reality gaming environment based on the notion of serious games that simulates driving through a tunnel from a first-person perspective. Various scenarios are developed within this environment based on the knowledge gaps identified in the literature, with the aim of assessing users’ knowledge as well as educating them when required. The developed tool was tried by more than 50 drivers, professional and non-professional during tool’s launch activities. In particular, drivers who had recently obtained a driver’s license confirmed that such a tool would be especially useful in the context of their training. The ultimate goal of this study is to provide an efficient tool in order to support both practitioners and authorities to significantly improve the safety level of road tunnels by emphasizing on the driving behavior, since this is considered the most crucial component of each tunnel system.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"24 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80060156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A modelling approach to studying variations in newborn life support procedure","authors":"Alfian Tan, R. Remenyte-Prescott, M. Valstar, D. Sharkey","doi":"10.1177/1748006x231173595","DOIUrl":"https://doi.org/10.1177/1748006x231173595","url":null,"abstract":"Variations in clinical practice are common. However, some variations may cause undesired consequences. Careful consideration of their causes and effects is necessary to assure the quality of healthcare delivery. A modelling approach that could capture these aspects would help to achieve this goal. In this paper, a Newborn Life Support procedure is modelled. This activity is considered prone to error with reduced outcomes for the patient. Hence, it is necessary to understand the nature of the activity and its variations. A Coloured Petri Net (CPN) approach and a simulation technique are used for this purpose. The CPN colours are used to represent the characteristics of babies and to control the flow of tokens representing the resuscitation procedure. Probabilistic modelling aspects include the duration of individual tasks, the choice of treatment and the condition of the baby. The model outputs consist of the percentage of babies with an unsatisfactory outcome, the percentage of babies who need full resuscitation, and the duration of the procedure until a satisfactory condition is achieved. The modelling approach is demonstrated using a number of scenarios on some common NLS variations, relating to the maximum number of ventilation and the probability of errors in the inflation procedure.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"37 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88601433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Maintenance Modelling for Industrial Systems","authors":"R. Remenyte-Prescott, P. Do, J. Andrews","doi":"10.1177/1748006X221149608","DOIUrl":"https://doi.org/10.1177/1748006X221149608","url":null,"abstract":"Maintenance has an important role in modern economies and industries. Effective maintenance can improve system safety and reliability and reduce whole-life cycle costs of complex engineered systems. With the emergence of new technology and opportunities to collect system performance and condition data, it has become necessary to develop advanced methods for modelling maintenance of complex systems. Maintenance modelling allows balancing the cost of performing maintenance for a system against the losses incurred due to its performance loss. It provides decision makers with the knowledge and tools to enable them to reduce costs or/and keep system performance at a desired and safe level. Over the years, research in maintenance modelling has attracted considerable attention from both academy and industry and it is the main focus of this special issue, which contains a number of articles that are focussed on recent advancements in modelling maintenance for complex and industrial systems. The first paper by Tamssaouet et al. reviews literature in the areas of system-level prognostics and RUL estimation for multicomponent systems. Prognostics and Health Management approaches integrate fault detection, failure diagnostics, prognostics and maintenance decision support processes, and their effective usage can make large savings in asset management costs. Many studies focus on component-level prognostics, but their practical use can be enhanced only if system operators and maintenance managers can base their decisions on system-level parameters of complex system performance. Future challenges in this relatively recent research area conclude the paper. The second paper by Corset et al. proposes a stochastic model for imperfect condition-based maintenance. The degradation is modelled by a gamma process, and the condition-based maintenance policy with perfect corrective and imperfect preventive actions is proposed. The statistical inference of the model parameters is carried out, considering degradation data with imperfect maintenance. Finally, a sensitivity analysis shows how the whole lifecycle maintenance cost depends on the degradation and maintenance model parameters, and such information can support asset management decision-making processes. Ulansky and Raza in the third paper focus on imperfect inspections while modelling condition-based and preventive maintenance. The authors develop probabilistic indicators of imperfect inspections that can be used to describe correct and incorrect decisions. The effectiveness indicators of such maintenance are expressed in terms of operating costs, total error probability and a posterior probability of failure-free operation. The paper concludes with emphasising the importance of including time-dependency in the obtained probabilities of correct and incorrect decisions. A mathematical model of a hybrid maintenance policy is proposed in the fourth paper by Melo et al. Such a policy consists of combining periodic insp","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"6 1","pages":"523 - 523"},"PeriodicalIF":2.1,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75715023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel approach based on fault tree analysis and Bayesian network for multi-state reliability analysis of complex equipment systems","authors":"Xiaofang Luo, Yushan Li, Xutao Bai, Rongkeng Tang, Hui Jin","doi":"10.1177/1748006x231171449","DOIUrl":"https://doi.org/10.1177/1748006x231171449","url":null,"abstract":"Due to the complex structure of multi-state complex systems and the lack of data, information, and knowledge, the uncertainty of the logical relationship between the failure states of systems and components and the uncertainty of related failure data become the key issues in the reliability analysis of multi-state complex systems. In this paper, combined with multi-state fault tree (MSFT), a multi-state reliability assessment framework for complex systems considering uncertainty based on multi-source information fusion and multi-state Bayesian network (MSBN) is proposed. The multi-source information fusion method combines historical data and experts’ opinions to solve the uncertainty problem of multi-state failure data in complex equipment systems effectively. Based on the multi-source information fusion method, the calculation method of multi-state prior probability and the construction method of conditional probability are given. By constructing the conditional probability table (CPT), the uncertain logic relationship between the multi-state nodes is effectively expressed, which effectively improves the efficiency of CPT acquisition for MSBN and reduces the workload of experts scoring. Finally, a mud circulating system is taken as an example to prove the proposed method, and the specific calculation process, evaluation results, and some discussions are given. The results show that the proposed method is an effective multi-state reliability analysis method for complex uncertain multi-state systems.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"17 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80196564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mission abort strategy for generalized k-out-of-n: F systems considering competing failure criteria","authors":"Shuai Cao, Xiaoyue Wang","doi":"10.1177/1748006x231170909","DOIUrl":"https://doi.org/10.1177/1748006x231170909","url":null,"abstract":"For safety-critical systems such as submarines and solar lighting system, mission abort is an effective way to enhance system survivability when a certain malfunction condition is met. This paper contributes by presenting a bivariate mission abort policy for generalized k-out-of- n: F systems that fail if there are at least m non-overlapping kc consecutive failed components or at least kt failed components. When the number of non-overlapping kc consecutive failed components reaches a preset level or the total number of failed components exceeds a predetermined value, the mission is aborted, and then a rescue procedure is initiated. Mission reliability and system survivability are derived by employing a two-step finite Markov chain imbedding approach. The optimization models are formulated with the purpose of maximizing the mission reliability, and minimizing the expected total cost of mission failure and system failure, respectively. A numerical example based on a solar lighting system is presented to illustrate the applicability of the proposed policies.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"31 9","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72412960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantification of risk dilution induced by correlation parameters in dynamic probabilistic risk assessment of nuclear power plants","authors":"K. Kubo, Yoichi Tanaka, J. Ishikawa","doi":"10.1177/1748006x231167201","DOIUrl":"https://doi.org/10.1177/1748006x231167201","url":null,"abstract":"Nuclear power plants are critical infrastructures that produce electricity. However, accidents in nuclear power plants can cause considerable consequences such as the release of radioactive materials. Therefore, appropriately managing their risk is necessary. Various nuclear regulatory agencies employ probabilistic risk assessment (PRA) to effectively evaluate risks in nuclear power plants. Dynamic PRA has gained popularity because it allows for more realistic assessment by reducing the assumptions and engineering judgments related to time-dependent failure probability and/or human-action reliability in the conventional PRA methodology. However, removing all assumptions and engineering judgments is difficult; thus, the risk analyst, for example, the regulator, must understand their effects on the assessment results. This study focuses on “risk dilution,” which emerges from the assumptions about uncertainty. Dynamic PRA of a station blackout sequence in a boiling-water reactor was performed using the dynamic PRA tool, namely, Risk Assessment with Plant Interactive Dynamics (RAPID) and the severe-accident code Thermal–Hydraulic Analysis of Loss of Coolant, Emergency Core Cooling, and Severe Core Damage version 2 (THALES2), which altered the correlation parameters among the uncertainties of the events that occurred in sequence. The results demonstrated that the conditional core-damage probability and mean value of the core-damage time varied from 0.27 to 0.47 and from 7.1 to 8.7 h, respectively. When the dynamic PRA results are used for risk-informed decision making, the decision maker should adequately consider the effect of risk dilution.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72992572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Petri nets-based method for operational risk analysis in supply chains based on timeliness and recovery time","authors":"J. Skorupski, A. Tubis, S. Werbińska-Wojciechowska, Adam Wróblewski","doi":"10.1177/1748006x231168957","DOIUrl":"https://doi.org/10.1177/1748006x231168957","url":null,"abstract":"Recently, supply chain risk management has been attracting growing attention. Therefore, various methods, tools, and practices have been developed in this area. However, they usually are focused on the direct consequences of disruptions occurring in supply chains. Thus, the purpose of this article is to present an operational risk analysis method for supply chains, in which consequences of an adverse event occurrence are assessed based on two measures: (1) the direct consequences (disruption) of supply processes to customers, and (2) recovery time for a supply system. Based on research findings, we introduced a Petri nets model for mapping material flows along a supply chain. We implement the proposed analysis method in a selected company from the automotive industry. The performed final discussion confirmed the relevance of distinguishing the direct and indirect consequences of the risk assessment. It was also suggested that the results’ interpretation could be two-fold, which may be necessary for appropriate risk management tool selection.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"23 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86830306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating condition-based monitoring with process sensors information for operation and maintenance in a functional modeling framework","authors":"Jing Wu, Xinxin Zhang","doi":"10.1177/1748006x231167457","DOIUrl":"https://doi.org/10.1177/1748006x231167457","url":null,"abstract":"Safe operations and adequate maintenance are two main means to achieve reliable production and reduce downtime of a plant. While the tasks of operations and maintenance are carried out by two different groups of staff, as a result, the close relationship between the two tasks is split. In this paper, this challenge is handled by a proposed integrated functional modeling framework. In this framework, the Multilevel Flow Modeling (MFM) method with its cause-consequence reasoning rules is used. Condition-based monitoring is a well-accepted strategy for predictive maintenance and fault detection based on measurements is a well-developed technology for operation support. Information fusion including monitoring conditions of assets and process sensors information for both operation and maintenance in the same modeling framework is desired. The qualitative relationship distribution between operations and maintenance can be established based on the function states of the system. In addition, these relationships are visible for both groups of staff. As a result, the detected information in the early stage of the development of the unpleasant scenarios is used to improve their situation awareness, so that the undesired emergency shutdown from both perspectives of operation and maintenance is prevented. Consequently, it can reduce production loss. A case study of operations and maintenance of a seawater injection system is carried out and shows the industrial applicability of the proposed framework. The case study strongly reveals that there is a highly close relation between operation and maintenance for ensuring the system working properly. It demonstrates that the proposed integrated framework is not only able to support operational tasks but also for the maintenance tasks by including relevant maintenance information of the system. The results show that it can potentially help with decreasing downtime of the system.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"53 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84533726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatigue reliability assessment method for wind power gear system based on multidimensional finite element method","authors":"Ming Li, Yuan Luo, L. Xie, Cao Tong, Chuan Chen","doi":"10.1177/1748006x231164723","DOIUrl":"https://doi.org/10.1177/1748006x231164723","url":null,"abstract":"As a core strategic technology industry, the wind power plays an important role in protecting national energy reserves. The large gear component is one of the core foundation parts in wind turbines, and its quality indexes greatly affect the service performance of the wind turbine drive chain and even the wind turbine as a whole. This paper calculates the fatigue load history of the wind power large gear system under the coupling mechanism of elastic behavior based on a multidimensional finite element method, and obtains the probabilistic fatigue strength of gear teeth through the gear low circumference fatigue test and life distribution transformation method, and deeply explores the inherent characteristics of the wind power gear system in functional implementation and then establishes a system fatigue reliability evaluation model. Finally, a mapping path from the global structural elements of the wind power gearbox to the reliability indexes of the gear system is constructed with significant simulation and test cost advantages. It can provide structural optimization guidance in the development and design of large wind power gear systems, and significantly reduce the cost of achieving reliability indexes in the design iterations of such large high-end equipment. At the same time, it can provide cost-effective training data for intelligent optimization algorithms such as the deep reinforcement learning, which will eventually achieve multi-objective optimal stiffness matching for wind power gearboxes under reliability index constraints.","PeriodicalId":51266,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part O-Journal of Risk and Reliability","volume":"92 2 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83453628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}