Human Factors and Ergonomics in Manufacturing & Service Industries最新文献

Human factors analysis of coal mine gas accidents based on improved HFACS model 基于改进的 HFACS 模型的煤矿瓦斯事故人为因素分析

Human Factors and Ergonomics in Manufacturing & Service Industries Pub Date : 2024-02-14 DOI: 10.1002/hfm.21028

Mengjiao Zhang, Hongxia Li, Heqiong Xia, Qian Zhang, Yanlin Chen, Yuchen Liu, Haoran Xu

{"title":"Human factors analysis of coal mine gas accidents based on improved HFACS model","authors":"Mengjiao Zhang, Hongxia Li, Heqiong Xia, Qian Zhang, Yanlin Chen, Yuchen Liu, Haoran Xu","doi":"10.1002/hfm.21028","DOIUrl":"https://doi.org/10.1002/hfm.21028","url":null,"abstract":"Gas accidents represent a crucial domain of coal mine safety research, as they result in substantial property damage, environmental pollution, and even loss of life compared to other types of accidents. Particularly, human factors play a significant role in the majority of mining accidents. The objective of this paper is to enhance the quality of coal mine safety management, minimize the occurrence of adverse human factors in gas accidents, and analyze the factors influencing coal mine gas accidents using the Human Factors Analysis and Classification System (HFACS). To commence, this paper has devised a human factor influence index system based on the enhanced HFACS for coal mine gas accidents. Subsequently, the Decision‐making Trial and Evaluation Laboratory (DEMATEL) method has been employed to quantitatively delineate the causal relationships among these factors. Lastly, this paper utilized the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) comprehensive evaluation method to evaluate the importance of factors influencing coal mine gas accidents. The research findings indicate that through the utilization of the DEMATEL methodology for centrality and causal relationship calculations, the centrality and causality values associated with poor organizational management emerge as the foremost among all factors. This underscores the pivotal role that poor organizational management plays in the human factors influencing coal mine gas accidents. Furthermore, a meticulous examination using TOPSIS identified the top five indicators of influence capability: cognitive errors > habitual violations > operational management > management process > resource management. The analysis of human factors in coal mine gas accidents can provide enhanced theoretical support for the management of production safety in coal mines, as well as the prevention of gas accidents.","PeriodicalId":112194,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"41 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139779620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Characterization and classification of EEG signals evoked by different CAD models 不同 CAD 模型诱发的脑电信号的特征和分类

Human Factors and Ergonomics in Manufacturing & Service Industries Pub Date : 2024-02-13 DOI: 10.1002/hfm.21027

Hongwei Niu, Jia Hao, Zhiyuan Ming, Xiaonan Yang, Lu Wang

{"title":"Characterization and classification of EEG signals evoked by different CAD models","authors":"Hongwei Niu, Jia Hao, Zhiyuan Ming, Xiaonan Yang, Lu Wang","doi":"10.1002/hfm.21027","DOIUrl":"https://doi.org/10.1002/hfm.21027","url":null,"abstract":"The past two decades have witnessed dramatic advancement in computer‐aided design (CAD). However, development of human–computer interfaces (HCI) for CAD have not kept up with these advances. Windows, Icons, Menus, Pointer (WIMP) is still the mainly used interface for CAD applications which limits the naturalness and intuitiveness of the CAD modeling process. As a novel interface, Brain–computer interfaces (BCIs) have great potential in the application of CAD modeling. Utilizing BCIs, the user can create CAD models just by thinking about it in principle, because BCIs provide an end‐to‐end interaction channel between users and CAD models. However, current related studies are mainly limited to the existing BCIs paradigms, while ignoring the relationship between electroencephalogram (EEG) signals and CAD models, which largely increases the cognitive load on the users. In this study, we aimed to explore the potential of using BCI to create CAD models directly independent of the classical BCIs paradigms. For this purpose, EEG signals evoked by six basic CAD models (i.e., point, square, trapezoid, line, triangle, and circle) were collected from 28 participants. After preprocessing and sub‐trial principal components analysis (st‐PCA) of recorded data, the peak, mean and time‐frequency energy features were extracted from EEG signals. By applying the one‐way repeated measures analysis of variance, we demonstrated that there were significant differences among these EEG features evoked by different CAD models. These features from EEG electrode channels ranked by mutual information were then used to train a discriminant classifier of genetic algorithm‐based support vector machine. The empirical result showed that this classifier can discriminate the CAD models with an average accuracy of about 72%, which turns out that EEG based model generation is feasible, and provides the technical and theoretical basis for building a novel BCI for CAD modeling.","PeriodicalId":112194,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"59 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploration of multimodal alarms for civil aircraft flying task: A laboratory study 民用飞机飞行任务的多模式警报探索：实验室研究

Human Factors and Ergonomics in Manufacturing & Service Industries Pub Date : 2024-02-06 DOI: 10.1002/hfm.21026

Wenzhe Cun, Suihuai Yu, Jianjie Chu, Yanhao Chen, Jianhua Sun, Hao Fan

{"title":"Exploration of multimodal alarms for civil aircraft flying task: A laboratory study","authors":"Wenzhe Cun, Suihuai Yu, Jianjie Chu, Yanhao Chen, Jianhua Sun, Hao Fan","doi":"10.1002/hfm.21026","DOIUrl":"https://doi.org/10.1002/hfm.21026","url":null,"abstract":"Owing to the increasing amount of information presented in the cockpit, the visual and hearing channels are unable to adequately transmit information, which may increase the mental load on pilots. This study explores the benefits of multimodal alarms under high and low residual capacities during take‐off in civil aircrafts in a quasi‐experimental study. The performance of two modes of multimodal (visual and auditory [VA], and visual, auditory, and tactile [VAT]) alarms were tested. The results showed that the VAT alarms were superior to the VA alarms in terms of choice response times (CRTs) when the participants were exposed to low residual capacities of vision and hearing. However, this effect was not observed when the participants had high residual capacities for vision and hearing. Thus, we considered that an additional tactile alarm could play a significant role in the CRTs when VA resources were consumed. There was no significant difference in the number of response errors between the three multimodal alarm modes. This study provides a key comparison of the two modes of multimodal alarms, indicating that VAT alarms are ideal for use in alarm design strategies for next‐generation civil cockpits.","PeriodicalId":112194,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139800349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Use of cross‐training in human–robot collaborative rescue 在人机协作救援中使用交叉训练

Human Factors and Ergonomics in Manufacturing & Service Industries Pub Date : 2024-02-05 DOI: 10.1002/hfm.21025

Dan Pan, Di Zhao, Youchen Pu, Liang Wang, Yijing Zhang

{"title":"Use of cross‐training in human–robot collaborative rescue","authors":"Dan Pan, Di Zhao, Youchen Pu, Liang Wang, Yijing Zhang","doi":"10.1002/hfm.21025","DOIUrl":"https://doi.org/10.1002/hfm.21025","url":null,"abstract":"Human–robot collaboration has been widely used in postdisaster investigation and rescue. Human–robot team training is a good way to improve the team rescue efficiency and safety; two common training methods, namely, procedural training and cross‐training, are explored in this study. Currently, relatively few studies have explored the impact of cross‐training on human–robot collaboration in rescue tasks. Cross‐training will be novel to most rescuers and as such, an evaluation of cross‐training in comparison with more conventional procedural training is warranted. This study investigated the effects of these two training methods on rescue performance, situation awareness and workload. Forty‐two participants completed a path‐planning and a photo‐taking task in an unfamiliar simulated postdisaster environment. The rescue performance results showed that cross‐training method had significant advantages over procedural training for human–robot collaborative rescue tasks. During the training process, compared with procedural training, participants were more likely to achieve excellent photo‐taking performance after cross‐training; after training, the length of the route planned by the cross‐training group was significantly shorter than that of the procedural‐training group. In addition, procedural‐training marginal significantly increased the emotion demand, which proves that cross‐training can well control the emotions of the operators and make them more involved in the rescue task. The study also found that arousal level increased significantly after the first cross‐training session, and decreased to the same level as procedural training after multiple sessions. These results contribute to the application of cross‐training in human–robot collaborative rescue teams.","PeriodicalId":112194,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"11 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139805418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human Factors and Ergonomics in Manufacturing &amp; Service Industries最新文献

Human Factors and Ergonomics in Manufacturing & Service Industries最新文献