Quality and Reliability Engineering International最新文献_第10页

Springing loads analysis of large‐scale container ships in regular waves 大型集装箱船在规则波浪中的弹跳载荷分析

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-18 DOI: 10.1002/qre.3558

Qian‐Dong Feng, Liang‐Jun Wen, Cai‐Xia Jiang, Xue‐Liang Wang

引用次数: 0

An AK‐MCS‐based probabilistic fatigue life prediction framework for turbine disc with a mean stress correction model 基于 AK-MCS 的涡轮机盘概率疲劳寿命预测框架，含平均应力校正模型

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-12 DOI: 10.1002/qre.3556

Yun Wang, Yan‐Feng Li, Hong‐Zhong Huang, Song Bai

引用次数: 0

Optimal maintenance policy considering imperfect switching for a multi‐state warm standby system 考虑多状态热备用系统不完美切换的最佳维护策略

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-09 DOI: 10.1002/qre.3550

Fa‐Qun Qi, Yun‐Ke Wang, Hong‐Zhong Huang

引用次数: 0

Monitoring covariance in multivariate time series: Comparing machine learning and statistical approaches 监测多元时间序列中的协方差：比较机器学习和统计方法

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-09 DOI: 10.1002/qre.3551

Derek Weix, Tzahi Y. Cath, Amanda S. Hering

{"title":"Monitoring covariance in multivariate time series: Comparing machine learning and statistical approaches","authors":"Derek Weix, Tzahi Y. Cath, Amanda S. Hering","doi":"10.1002/qre.3551","DOIUrl":"https://doi.org/10.1002/qre.3551","url":null,"abstract":"In complex systems with multiple variables monitored at high‐frequency, variables are not only temporally autocorrelated, but they may also be nonlinearly related or exhibit nonstationarity as the inputs or operation changes. One approach to handling such variables is to detrend them prior to monitoring and then apply control charts that assume independence and stationarity to the residuals. Monitoring controlled systems is even more challenging because the control strategy seeks to maintain variables at prespecified mean levels, and to compensate, correlations among variables may change, making monitoring the covariance essential. In this paper, a vector autoregressive model (VAR) is compared with a multivariate random forest (MRF) and a neural network (NN) for detrending multivariate time series prior to monitoring the covariance of the residuals using a multivariate exponentially weighted moving average (MEWMA) control chart. Machine learning models have an advantage when the data's structure is unknown or may change. We design a novel simulation study with nonlinear, nonstationary, and autocorrelated data to compare the different detrending models and subsequent covariance monitoring. The machine learning models have superior performance for nonlinear and strongly autocorrelated data and similar performance for linear data. An illustration with data from a reverse osmosis process is given.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140565950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimum maintenance units in multi‐indenture systems 多诱饵系统中的最佳维护单元

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-09 DOI: 10.1002/qre.3549

Qian Qian Zhao, Jae Yoon Yoo, Tadashi Dohi, Won Young Yun

{"title":"Optimum maintenance units in multi‐indenture systems","authors":"Qian Qian Zhao, Jae Yoon Yoo, Tadashi Dohi, Won Young Yun","doi":"10.1002/qre.3549","DOIUrl":"https://doi.org/10.1002/qre.3549","url":null,"abstract":"This paper deals with an optimization problem of determining the maintenance units and age‐based inspection schemes to minimize the expected maintenance cost rate and satisfy a target system availability for multi‐indenture systems that have a modular structure with redundant units. Failures of primary components directly lead to system failures and can therefore be identified and maintained immediately, while failures of redundant components need to be identified by inspections. And the designated maintenance units need to be replaced during maintenance. By constructing the dual structure of the fault tree, we present a failure path enumeration method, based on which the system availability and expected maintenance cost rate models considering maintenance time are derived. For redundant units, two types of inspection policies are considered in our models: one is the corrective maintenance (CM)‐based inspection policy, and the other one is the age‐based inspection (PM) policy, inspections are performed at failures or age h, depending on which occurred earlier. A heuristic algorithm is proposed to find the reasonable maintenance units and inspection intervals simultaneously, and its performance is also compared and analyzed. Several numerical examples are studied to investigate the effect of parameters on optimal solutions.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140565953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new ordering method of basic events in dynamic fault tree for sequential binary decision diagram 用于顺序二元决策图的动态故障树中基本事件的新排序方法

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-08 DOI: 10.1002/qre.3555

Tudi Huang, Ying Zeng, Yan‐Feng Li, Jun Liu, Hong‐Zhong Huang

引用次数: 0

Efficient estimation of the reliability functions in a multicomponent stress‐strength set‐up for a generalized family of distributions under progressive type II censoring 在渐进式 II 型普查条件下，有效估算多成分应力-强度设置中广义分布族的可靠性函数

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-08 DOI: 10.1002/qre.3547

Taruna Kumari, Anupam Pathak

引用次数: 0

Cumulative sum control charts for monitoring zero‐inflated COM‐Poisson processes 用于监测零膨胀 COM-Poisson 过程的累积和控制图

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-04 DOI: 10.1002/qre.3554

Konstantinos A. Tasias, Vasileios Alevizakos

引用次数: 0

Presenting a new model for evaluating the factors affecting equipment reliability using system dynamics 介绍一种利用系统动力学评估影响设备可靠性因素的新模式

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-04 DOI: 10.1002/qre.3553

Azam Modares, Alireza Pooya, Vahideh Bafandegan Emroozi, Pardis Roozkhosh

{"title":"Presenting a new model for evaluating the factors affecting equipment reliability using system dynamics","authors":"Azam Modares, Alireza Pooya, Vahideh Bafandegan Emroozi, Pardis Roozkhosh","doi":"10.1002/qre.3553","DOIUrl":"https://doi.org/10.1002/qre.3553","url":null,"abstract":"This study examines reliability of equipment (RoE) through three approaches: equipment design reliability, human reliability (HR), and maintenance‐based reliability. HR plays a key role in minimizing human error (HE) and subsequently enhancing RoE. Given that equipment reliability is influenced by numerous factors, these technologies come with various constraints, multiple outputs, and inputs. Compared to mathematical programming and analytical models, simulation methods in the field of reliability are relatively limited. However, system dynamics (SD) modeling is well‐suited to capture dynamics and complexity of systems, making it a valuable tool for long‐term strategic decision‐making. In this study, a combination of SD and regression approaches has been employed to explore the relationship between reliability and key variables such as HE and profit. Initially, the variables influencing reliability are identified, and then SD is utilized to understand the processes and interactions among these variables. Furthermore, linear regression is employed to establish the relationship between affective variables, reliability, and HE. To validate the results obtained from the proposed method, a sensitivity analysis is conducted. The results demonstrate the effectiveness of the proposed model. Simulation results indicate that implementing policies such as employee training and preventive maintenance significantly enhances RoE, leading to increased sales and profits for the organization. Therefore, managers should prioritize these variables and allocate adequate attention and resources to them.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140565830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Risk assessment of man‐machine systems under safety‐critical multitasking situations 安全关键型多任务情况下的人机系统风险评估

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-04-03 DOI: 10.1002/qre.3552

Haiyang Che, Kehui Li, Shengkui Zeng, Changbo Yv, Jianbin Guo

{"title":"Risk assessment of man‐machine systems under safety‐critical multitasking situations","authors":"Haiyang Che, Kehui Li, Shengkui Zeng, Changbo Yv, Jianbin Guo","doi":"10.1002/qre.3552","DOIUrl":"https://doi.org/10.1002/qre.3552","url":null,"abstract":"Multitasking is increasingly common in highly complex and safety‐critical systems, especially under abnormal situations. Mental overload (MOL) may occur and result in forgetting/mistaking tasks uncertainly. Such probabilistic errors could have catastrophic consequences and contribute greatly to the multitasking risk of man‐machine systems. In this paper, to better identify the risks of safety‐critical multitasking situations, MOL mechanism is investigated and a risk analysis method considering MOL is proposed. MOL occurs when the demand for resources estimated by Multiple Resources Model exceeds an operator's ability. Then, the operator's performance degrades, and s/he tends to mistake or abandon parts of tasks. Based on the MOL mechanism, a MOL‐performance dependency (MOL‐PDEP) gate is proposed to incorporate MOL into risk analysis. Its inputs are concurrent tasks, and it triggers the related hazardous human behavior events with certain probabilities if MOL occurs. Through this gate, the dependence among these events and their nondeterministic cause relationships to MOL are added to traditional fault tree (FT), which presents a challenge issue to FT analysis. An implicit method is proposed to analyze the FT with MOL‐PDEP gate and calculate the accident probability. A case study on a helicopter crash accident demonstrates the effectiveness of the proposed method.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140566036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0