{"title":"Quantifying and comparing the effects of human and organizational factors in electric maloperation accidents with HFACS–CatBoost and SHAP","authors":"Chuan Lin, Qifeng Xu, Yifan Huang","doi":"10.1002/hfm.20975","DOIUrl":"https://doi.org/10.1002/hfm.20975","url":null,"abstract":"<p>The proportion of electric maloperation accidents (EMAs) in substations caused by human and organizational factors (HOFs) has gradually increased. Although there has been some research into the factors affecting EMAs in substations, the available results are insufficient to support the interpretation of HOFs in EMAs. This article explores the relationships between the HOFs and EMAs using Human Factors Analysis and Classification System-gradient boosting with categorical features support (HFACS–CatBoost) and Shapley Additive exPlanation (SHAP) methods. First, the HFACS framework was introduced to identify 135 EMAs in the Southern Power Grid risk causation. CatBoost was used to construct an accident classification model to analyze the important relationship between accidents and HOFs and to compare and analyze with the extreme gradient boosting (XGBoost) and the binary logistic regression (BLR) to verify the superiority of CatBoost. Finally, to solve the problem of inadequate interpretation of the CatBoost black-box model, the SHAP value plot was applied to express the contribution degree relationship between accidents and HOFs. The results show that the above method can explore and explain the importance and contribution of HOFs in EMAs. And from this, it is concluded that poor psychological state, poor communication and coordination, inadequate supervision, and inadequate training and education are highly correlated with the occurrence of EMAs. The findings will help substation operations and maintenance staff to develop safety measures to address the confusion of HOFs in substations and prevent the occurrence of EMAs.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50154340","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}
Craig J. Foster, Katherine L. Plant, Neville A. Stanton
{"title":"Maladaptation in air traffic management: Development of a Human Factors methods framework","authors":"Craig J. Foster, Katherine L. Plant, Neville A. Stanton","doi":"10.1002/hfm.20974","DOIUrl":"https://doi.org/10.1002/hfm.20974","url":null,"abstract":"<p>Human Factors methods play a key role in challenging assumptions, analyzing interactions, and informing decision-making in complex sociotechnical systems and organizations that manage safety risks. Structured methodological approaches also have a role to play in better understanding properties of systems such as adaptation. Adaptation is increasingly recognized as being an important feature that supports the production of safety in complex sociotechnical systems. A safety management intervention, introduced to address a real risk in UK air traffic control but which resulted in unanticipated, maladaptive, and emergent effects, is analyzed using the Hierarchical Task Analysis, Systems Theoretic Accident Model and Processes, Functional Resonance Analysis Method, Human Factors Analysis and Classification System, Cognitive Work Analysis, Critical Decision Method, and Event Analysis of Systemic Teamwork Methods. The results from the application of each of the methods are presented and the different perspectives on adaptation that the methods provide are compared. A methodological framework is presented that has the potential to explore the factors of adaptation across the organizational hierarchy and assist safety practitioners in supporting decision makers in safety-related organizations.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50129266","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}
{"title":"A comfort evaluation method based on an intelligent car cockpit","authors":"Jian-Jun Yang, Yi-Meng Chen, Shan-Shan Xing, Rui-Zhi Qiu","doi":"10.1002/hfm.20973","DOIUrl":"https://doi.org/10.1002/hfm.20973","url":null,"abstract":"<p>With the rapid development of automobiles, car cockpits are becoming more and more intelligent and advanced, and the intelligent requirements of automobile cockpits are gradually increasing. However, the real value of intelligence can only be realized when it makes passengers in a cockpit feel comfortable. In this study, seven factors that affect passenger comfort in intelligent cockpits are defined. Under these factors, a total of 33 evaluation indicators were developed. The core of the method was to determine the dissatisfaction indicators and degree of dissatisfaction in the intelligent cockpit by analyzing the relationship between people's perceived performance and their expectations. This method was used to evaluate the Tesla Model 3, and it was found in the results that the higher the degree of dissatisfaction with the indicator, the more subjective feedback it had, which in turn proved the effectiveness of the model. According to the degree of dissatisfaction, the indicators affecting comfort were also divided into three levels. This hierarchical division helps clarify which indicators should be prioritized for improvement. Generally, this method has a certain feasibility, which is helpful for the development and redesign of an intelligent car cockpit, and provides some reference strategies for other transportation fields.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50122947","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}
{"title":"Accimap and crowd flow in urban infrastructure: Case study of Elphinstone road railway station tragedy, Mumbai, India","authors":"Vivek Kant, Aishwary Khobragade","doi":"10.1002/hfm.20972","DOIUrl":"https://doi.org/10.1002/hfm.20972","url":null,"abstract":"<p>The aim of this article is to show how Human Factors and Ergonomics (HFE) methods can be used to improve urban public infrastructure systems in densely populated countries, such as India. In this case, we use Accimap analysis with crowd flow approaches to inform safety and policy. We demonstrate the need for sociotechnical systemic safety by a case study of accident analysis of the <i>Elphinstone Road</i> railway station stampede. On September 29, 2017, the Elphinstone Road, Mumbai, India, railway platform bridge stampede killed at least 23 and injured 39 other commuters who traveled through the Mumbai Suburban railway. In this study, we understand the accident as it is presented in newspaper articles. We analyze the accident by a sociotechnical accident analysis method called the Accimap. The Accimap method helps by identification of various stakeholders and their interactions in the different levels of hierarchy in a sociotechnical system. This ensures moving away from individualistic and blame-based accounts of media reporting to a coherent sociotechnical account based on understanding the dynamics of the situation. The findings from the Accimap analysis identify the problem areas in the commuter transit system and provide recommendations. These recommendations range from commuter flow management to enforcement of rules for supporting pedestrian flow. The article concludes with an emphasis on the development of the sociotechnical dimension of public safety and infrastructure from a human factors perspective, above and beyond what is currently practiced in India.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50155980","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}
Brian D. Lowe, Marie Hayden, James Albers, Steven Naber
{"title":"Case studies of robots and automation as health/safety interventions in small manufacturing enterprises","authors":"Brian D. Lowe, Marie Hayden, James Albers, Steven Naber","doi":"10.1002/hfm.20971","DOIUrl":"10.1002/hfm.20971","url":null,"abstract":"<p>This article reviews the experiences of 63 case studies of small businesses (<250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (<i>n</i> = 17), computer numerical control (CNC) machining (<i>n</i> = 29), or other programmable automation systems (<i>n</i> = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated the acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: snack foods; photographic film, paper, plate, and chemical; machine shops; leather goods and allied products; plastic products; and iron and steel forging. This review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors, and improved process productivity in most cases.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10191138/pdf/nihms-1832571.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10292633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jisun Kim, Kirsten Revell, Pat Langdon, Mike Bradley, Ioannis Politis, Simon Thompson, Lee Skrypchuk, Jim O'Donoghue, Joy Richardson, Neville A. Stanton
{"title":"Partially automated driving has higher workload than manual driving: An on-road comparison of three contemporary vehicles with SAE Level 2 features","authors":"Jisun Kim, Kirsten Revell, Pat Langdon, Mike Bradley, Ioannis Politis, Simon Thompson, Lee Skrypchuk, Jim O'Donoghue, Joy Richardson, Neville A. Stanton","doi":"10.1002/hfm.20969","DOIUrl":"https://doi.org/10.1002/hfm.20969","url":null,"abstract":"<p>Vehicles with SAE Level 2 automated features are already in active use on the road, and vehicles with Level 3 or 4 will be with us soon. Although the vehicles provide support for longitudinal and lateral control, partially automated driving experience is sometimes more demanding than manual driving. However, the effects of automated driving on workload in naturalistic conditions have not been extensively investigated, as most studies have been undertaken in driving simulators. This study aims to extend the current understanding about workload in partially automated driving on public roads. Drivers' perceived workload was assessed after conducting manual and automated driving activities using a small sample (<i>N</i> = 8). They performed driving tasks in three contemporary vehicles with SAE Level 2 features, in highway and urban environments. The comparative findings revealed that drivers' perceived workload was higher in partially automated driving than manual driving. Furthermore, perceived workload was higher in urban environments than highway environments and in less experienced drivers than more experienced drivers. Although the findings may need to be interpreted with caution due to the small sample size, they provide a future research agenda that can be built upon.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50153213","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}
{"title":"Ecological interface design and emergent users: Designing for small-scale trucking ecology in India","authors":"Vivek Kant, Varun V. Karthikeyan, Nishant Sharma","doi":"10.1002/hfm.20970","DOIUrl":"https://doi.org/10.1002/hfm.20970","url":null,"abstract":"<p>Effective on-road safety requires proper maintenance of vehicles. In the trucking sector in India, there is a need for supporting predictive maintenance to decrease downtime and improve safety. Improving maintenance in this sector involves certain challenges. First, most trucks are owned by small-scale fleet owners (trucks < 5). Second, maintenance is often handled by small-scale mechanic workshops. The fault diagnosis is very often limited to recognition by the driver and later reassessed by the mechanic by relying on the feel or the sound of the vehicle. Third, a majority of stakeholders in this sector—drivers, mechanics, and owners—have low levels of education. Despite these challenges, with the increase in the rate of digitalization, in the future, it will be easier to monitor the health of the parts of a truck. In addition, there is a developing trend of mobile phone and internet penetration in India that has leapfrogged a majority of Indians into becoming “emergent users” of information technology. Therefore, this article shows that sociotechnical approaches such as ecological interface design can be used to develop mobile interfaces for supporting predictive maintenance through health and usage monitoring of trucks for small-scale fleet owners in India. To develop the interface, a field study was conducted at several sites in the state of Tamil Nadu, India. The insights were used to develop scenarios and the abstraction hierarchy, which were later used creatively to develop the interface design for emergent users.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50134128","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}
{"title":"A bi-objective ergonomic assembly line balancing model with conic scalarization method","authors":"Busra N. Yetkin, Emin Kahya","doi":"10.1002/hfm.20967","DOIUrl":"10.1002/hfm.20967","url":null,"abstract":"<p>The most important factor affecting efficiency and ergonomic risk levels in an assembly line design is the problem of assigning certain tasks to certain stations, namely the assembly line balancing problem. In the literature, assembly line balancing problem has often been studied, but studies that consider ergonomic risks are deficient. Recently, it has been one of the issues that have started to attract great attention with the realization of health problems caused by assembly lines. To this end, in this study, a bi-objective mathematical model is developed that considers balancing assembly line station time and ergonomic risk levels, simultaneously. It is aimed to minimize both station time and the total deviations of ergonomic risk scores for the stations. Weighted sum and conic scalarization methods are applied to solve the bi-objective model. To analyze the outcomes of the developed model, an application is proposed and tested on a real industrial case, at a home appliance assembly line. The deployment of the OMAX method is a contribution to the literature since it shows an analysis tool which evaluates the results of assembly line balancing. This method evaluates the performance of the stations based on different criteria such as station time and ergonomic risk. The number of high-risk stations is obtained as 13 in the single-objective model aiming to minimize the station time, while it is found to be nine in the bi-objective model solved with CSM, without an increase in the total number of stations.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79927230","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}
Elamara Marama de Araujo Vieira, Jonhatan Magno Norte da Silva, Luiz Bueno da Silva, João Agnaldo do Nascimento, Wilza Karla dos Santos Leite, Lucas Gomes Miranda Bispo
{"title":"How do thermal conditions in intensive care units affect the health and well-being of intensivists?","authors":"Elamara Marama de Araujo Vieira, Jonhatan Magno Norte da Silva, Luiz Bueno da Silva, João Agnaldo do Nascimento, Wilza Karla dos Santos Leite, Lucas Gomes Miranda Bispo","doi":"10.1002/hfm.20968","DOIUrl":"https://doi.org/10.1002/hfm.20968","url":null,"abstract":"<p>This study presents situational risk scenarios to predict the potential implications of predicted and perceived thermal configurations on the health and well-being of health care professionals in intensive care units (ICUs). Nine ICUs were selected, and thermal variables were collected; simultaneously, 128 health care professionals were interviewed to assess their perceptions, satisfaction, and health conditions related to their workplace environment. In scenarios with thermal comfort (either predicted or perceived), the risk of exposure to physical and psychological symptoms was reduced. This effect also extends to predictions and perceptions tending toward slightly cooler temperatures. In situations with a predicted mean vote below −1.5 and above 0.5, symptom complaints increased, even when the health care professionals perceived their environment as thermally comfortable, with the most extreme cases generating an increase of up to 27% in the baseline probability. Adjusting the workplace environment to be thermally comfortable can reduce symptom complaints.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50152369","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}
{"title":"An investigation of musculoskeletal discomforts among mining truck drivers with respect to human vibration and awkward body posture using random forest algorithm","authors":"Mohsen Aliabadi, Ebrahim Darvishi, Maryam Farhadian, Ramin Rahmani, Masoud Shafiee Motlagh, Neda Mahdavi","doi":"10.1002/hfm.20965","DOIUrl":"10.1002/hfm.20965","url":null,"abstract":"<p>Using Random Forest algorithms, this study aimed to investigate musculoskeletal discomforts among mining truck drivers considering human vibration and awkward body posture. The study was conducted on 65 professional male drivers of mining trucks. The Cornell questionnaire was used to determine musculoskeletal discomforts. Drivers' exposure to vibrations was measured using the Svanteck 106 A vibration meter. The body posture was analyzed using the quick exposure check (QEC). The main mechanical and individual risk factors were used as predictor variables of musculoskeletal discomforts model. The relative importance of each feature on the discomforts was determined based on Random Forest algorithm compared with multiple linear regression using R Statistics Packages. The equivalent acceleration of whole-body vibration (WBV) was higher than the exposure limit, however, the equivalent acceleration of hand-transmitted vibration (HTV) was lower than the exposure limit. The body posture of drivers was from moderate to high risk so that investigation and changes are required soon. The predictive error of Random Forest model for musculoskeletal discomfort scores was at an acceptable level with root mean square error (RMSE) = 5.29 for the blind case of drivers compared with regressions model with RMSE = 15.92. Random forest showed that the awkward body posture, vibration, and age, respectively, have the greatest relative importance on musculoskeletal discomforts. The findings provide empirical evidence on the relative importance of risk factors on musculoskeletal discomfort so that awkward body posture has a greater effect compared with whole-body vibration. Random forest provided better outputs and was more accurate compared with the regression method.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2022-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76069428","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}