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

{"title":"Individual and Organizational Resilience: Relationships, Antecedents, and Consequences","authors":"Claudia Cristina Alvares Beltrão de Medeiros,&nbsp;Tarcisio Abreu Saurin","doi":"10.1002/hfm.21063","DOIUrl":"https://doi.org/10.1002/hfm.21063","url":null,"abstract":"<div>\u0000 \u0000 <p>Resilience in socio-technical systems has a myriad of manifestations and outcomes that are often not made explicit in the literature. This drawback might be a source of misunderstandings and hinder the design of work systems supportive of desirable resilient performance. Two crucially distinctive manifestations refer to individual and organizational resilience. This study presents a model of how these two types relate to each other and how they relate to antecedents and consequences of resilience. To this end, we carried out a case study of freight road transport, emphasizing the truck drivers' perspectives. Data collection included 14 interviews with drivers and managers of logistics operations, in addition to non-participant observations of drivers' workplaces. Based on a thematic analysis, the model was developed consisting of seven themes: work constraints, investments, individual resilience practices, organizational resilience practices, operational efficiency, human costs, and overall costs. The first two themes are antecedents and the last three are consequences of resilience. The main relationships between the themes are presented as seven propositions for theory-testing. The model suggests three main approaches for a balanced distribution between individual and organizational resilience. These approaches consist of: tackling work constraints, especially production pressures; investing in organizational practices adopting a long-term view; and promoting individual practices that proactively support health and safety. The truck drivers' study offers examples of the applicability of these approaches.</p>\u0000 </div>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248406","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":"Combined Effects of Ambient Light and Color on Cognitive Performance and Sleepiness in a Simulated Working Environment","authors":"Reza Shahidi,&nbsp;Rostam Golmohammadi,&nbsp;Ebrahim Darvishi,&nbsp;Mohsen Aliabadi,&nbsp;Mohammad Babmiri,&nbsp;Javad Faradmal","doi":"10.1002/hfm.21061","DOIUrl":"https://doi.org/10.1002/hfm.21061","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigated the combined effect of correlated color temperature and wall color on subjective sleepiness and cognitive performance in a simulated workplace. Six combined conditions were designed by partitioning a room into three booths with the same dimensions in three colors of blue, red, and white and two cool and warm light: color temperatures of 6000 and 3000°K (Red × 3000, Red × 6000, Blue × 3000, Blue × 6000, White × 3000, and White × 6000) during the day. Thirty-three healthy males aged 21–35 were recruited. They were asked to conduct cognitive tests in three workload levels and finally estimate the subjective sleepiness level. The findings indicated that cool light had a more significant effect on reducing sleepiness when compared to warm light, particularly in white and blue colors. However, this effect was not observed in the case of red color. The rate of sleepiness was higher in the cool light and red color compared to warm light. The blue color slightly decreased sleepiness compared to the white and red colors. The mean correct responses of the cognitive tests in cool light and white color were more than in other conditions. Moreover, the effect of blue and red were higher in the correct response percentages, compared to white in warm and cool light. There were no significant differences in reaction time between two different lights in all colors. However, reaction time was better in blue than in two other colors. To conclude, designing a work environment with a combination of cool light and blue-colored walls may improve employee alertness and performance.</p>\u0000 </div>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121156","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":"Stakeholder Risk Perception About Heat: An Interview-Based Study Among Outdoor Workers in South India","authors":"Sneha Ragupathy,&nbsp;Shanmukh Pranavi Annadata,&nbsp;P. K. Latha,&nbsp;Sarada Satyamoorthy Garg,&nbsp;Vidhya Venugopal","doi":"10.1002/hfm.21062","DOIUrl":"https://doi.org/10.1002/hfm.21062","url":null,"abstract":"<div>\u0000 \u0000 <p>Heat waves in Southeast Asia are expected to intensify in the upcoming decades thereby raising the vulnerability of at-risk workers to heat-related illnesses (HRIs). Identifying and strengthening workers' self-protection knowledge is crucial to effective heat adaptation and management. The study aimed to investigate outdoor workers' perceptions of heat-related risks, changes in protective behavior during hotter seasons, knowledge and awareness of regional heat action plans (HAPs), and protection measures. It aimed to find effective means of communication and strategies for improving heat protection among these workers. We used a validated and structured mixed-method survey questionnaire and one-on-one interviews to assess 140 outdoor workers' heat-related risk perceptions, protective behavior changes during hot seasons, and knowledge of regional HAPs protective measures in April–July 2022. The estimated worker's seasonal average WBGT exposure using meteorological data was 34.4°C ± 0.02°C, which exceeded acceptable limits. Heat was a big concern for outdoor workers, the study revealed. Workers believed that knowing about heat hazards could help reduce individual risks. Many workers were aware of the heat's health risks but felt the nature of their jobs prevented them from taking precautions. Some workers assumed that business owners' concerns about productivity and cooling costs would prevent government measures to safeguard at-risk employees from succeeding. Workers responded more positively to business owners' HAP communications. Workers are more likely to use practical, simple sector-based warning HAPs. We urgently need management policy reforms to protect millions of workers in low- and middle-income countries (LMICs), and the implementation of cost-effective, practical, and sustainable heat protection infrastructure and behavioral change solutions through trusted channels is crucial.</p>\u0000 </div>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118418","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":"The Impact of Individual and Team-Level Variables on Burnout in Healthcare Providers","authors":"Logan M. Gisick,&nbsp;Jenna Korentsides,&nbsp;Joseph R. Keebler,&nbsp;Elizabeth H. Lazzara,&nbsp;Philip E. Greilich,&nbsp;Susan Matulevicius","doi":"10.1002/hfm.21060","DOIUrl":"https://doi.org/10.1002/hfm.21060","url":null,"abstract":"<div>\u0000 \u0000 <p>This study evaluates the relationships between individual and team-level factors in influencing burnout among clinical healthcare providers. Focusing on psychological safety, perceived autonomy, perceived team effectiveness, and emotional intelligence, the research aims to understand how these elements contribute to the prevalence and severity of burnout symptoms. Using electronic questionnaires analyzed through Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), the study sampled 180 healthcare providers from one large US medical center. The study results found that psychological safety significantly decreases levels of burnout, particularly emotional exhaustion. The results on team effectiveness suggest a complex relationship with burnout, with different dimensions having varied impacts. The study did not find support for the negative prediction of burnout by perceived autonomy and emotional intelligence, contrary to expectations based on prior research. These findings have practical implications for healthcare management, stressing the importance of psychological safety and effective team dynamics in reducing burnout. Overall, this study contributes significantly to understanding burnout in healthcare, emphasizing the critical role of team structures and individual emotional resilience in managing workplace well-being.</p>\u0000 </div>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708195","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":"Towards Holistic Functional Task Analysis","authors":"Vahid Salehi,&nbsp;Paul M. Salmon,&nbsp;Catherine Burns,&nbsp;Alexis McGill,&nbsp;Doug Smith,&nbsp;Brian Veitch","doi":"10.1002/hfm.21059","DOIUrl":"https://doi.org/10.1002/hfm.21059","url":null,"abstract":"<p>Task analysis (TA) can contribute to work systems design, accident investigation, risk assessment, human error identification, planning, and training. Despite the advantages of existing sequential and hierarchical methods, they decompose tasks into their structure and focus on the order in which tasks are accomplished. They do not trace all interactions among elements/subtasks/operations at different levels. As the complexity of tasks increases, not keeping track of all interactions may result in poor, unwanted outcomes. This research introduces a different approach to TA that decomposes tasks into their constituent functions, describes the functionality of the overall work system, traces (dynamic nonlinear) interactions among functions, and highlights the role of functional variability in forming emergent outcomes. This approach to TA is called functional task analysis (FTA). A case study on nursing work was used to demonstrate the suitability of the FTA approach. The findings of this study show that the FTA approach contributes to task modeling by building a nonsequential, nonhierarchical functional model of a complex task considering dynamic, nonlinear interactions among functions. The FTA also contributes to task description by explaining different ways a task can be accomplished. It also increases the understanding, interpretation, and analysis of how changes in work conditions shape good/acceptable and poor/unacceptable outcomes. The FTA can complement the TA by adding some aspects, including functionality, nonlinearity, dynamics, and emergence, that the TA does not normally consider. The findings highlight how the functional approach to TA can be deployed as an alternative (or complement) to other task analysis methods.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hfm.21059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641275","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}

{"title":"An expository analysis of biomechanical and subjective impacts induced by shoe inserts in asymptomatic subjects: A systematic review on functionality and mechanisms of action","authors":"Waseem Ahmad,&nbsp;Md Sarfaraz Alam","doi":"10.1002/hfm.21058","DOIUrl":"https://doi.org/10.1002/hfm.21058","url":null,"abstract":"<p>This systematic review explores the biomechanical and subjective effects of shoe inserts, including foot orthotics (FOs) and insoles, in asymptomatic subjects. Aimed at understanding their implications, the review poses two key research questions: (i) the influence of shoe inserts on lower extremity biomechanics and subjective perception and (ii) the effects of different design characteristics on these aspects. Following Preferred Reporting of Systematic Reviews and Meta-Analysis guidelines, a meticulous search of Scopus and PubMed from August 2022 to March 2023 yielded 34 articles, with 26 focusing on biomechanical effects and eight on comfort effects. The studies, conducted during static and dynamic activities, such as standing, walking, jogging, running, jumping, and cycling, reveal significant reductions in rearfoot eversion, knee joint forces, and lower extremity muscle forces through postings and wedging in FOs. Changes in stiffness impact rearfoot kinematics, plantar pressure distribution, and ankle–foot power distribution. Conversely, surface texture and arch variations demonstrate limited significance. FOs and shoe inserts, characterized by geometric, material, location, size, and fabrication features, effectively regulate forces and moments on the lower extremity. This control promotes uniform plantar pressure distribution and enhances comfort during various activities. These insights benefit manufacturers, clinicians, and stakeholders, providing a deeper understanding of the positive benefits of FOs and shoe inserts. However, further well-designed studies on clinical populations are necessary to validate these findings and establish their clinical efficacy, as the current focus remains on healthy subjects.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579784","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":"Evaluating human error probability in maintenance task: An integrated system dynamics and machine learning approach","authors":"Vahideh Bafandegan Emroozi,&nbsp;Mostafa Kazemi,&nbsp;Alireza Pooya,&nbsp;Mahdi Doostparast","doi":"10.1002/hfm.21057","DOIUrl":"https://doi.org/10.1002/hfm.21057","url":null,"abstract":"<p>Human error is often implicated in industrial accidents and is frequently found to be a symptom of broader issues within the sociotechnical system. Therefore, research exploring human error during maintenance activities is important. This article aims to assess the probability of human error in maintenance tasks at a cement factory using the Cognitive Reliability and Error Analysis Method and System Dynamics modeling. Given that human error probability (HEP) is influenced by various common performance conditions (CPCs) and their sub-factors, and changes dynamically in response to other variables, the SD method offers a practical approach for estimating and predicting human error behavior over time. This study identifies and quantifies the variables affecting HEP, explores their interactions and feedback in maintenance tasks, and assesses the associated costs. The machine learning technique is then used to estimate the relationship between HEP and these costs. The optimal value of the HEP function, 0.000772, is determined by identifying the minimum point of a cubic function, thereby minimizing associated costs and occupational accidents. Determining the optimal HEP is crucial for minimizing excessive costs and investing in improved ergonomics and CPCs for better performance. This addresses a significant gap in existing research where the impact of human error on maintenance tasks has not been estimated as a function. Furthermore, three scenarios are presented to help managers allocate the organization's budget more effectively.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579590","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":"Enhancing experiential learning through virtual reality: System design and a case study in additive manufacturing","authors":"Rafia Rahman Rafa,&nbsp;Taufiq Rahman,&nbsp;Md Humaun Kobir,&nbsp;Yiran Yang,&nbsp;Shuchisnigdha Deb","doi":"10.1002/hfm.21055","DOIUrl":"https://doi.org/10.1002/hfm.21055","url":null,"abstract":"<p>The recent advancement in additive manufacturing (AM) leads to an extensive need for an industrial workforce in the near future. Workforce training in AM requires expensive capital investment for installing and maintaining this technology and proper knowledge about potential safety hazards. Traditional classroom settings often fail to bridge the critical gap between textbook learning and practical applications. Virtual reality (VR) training can simulate real-world scenarios in a safe and controlled environment and improve student involvement to foster practical learning. In this paper, a virtual training platform for 3D printing has been developed and studied to improve AM education. The developed environment contains a selective laser sintering printer, a preparation station with necessary supplies, a control panel for process planning, and a post-processing station. This platform provides students with excellent learning opportunities to gain hands-on experiences and critical engineering skills on operating process parameters and safety measures. Undergraduate students majoring in industrial engineering were exposed to this learning approach to enhance their engagement and cognitive processing skills. Students' attentions were measured using eye metrics (fixation duration and preference index), and their exposure experiences were collected through the simulation sickness questionnaire, presence questionnaire, and system usability scale. Pre- and post-VR training questionnaires and performance metrics (task completion time and accuracy) evaluated students' learning outcomes. Results provide valuable insights into students' attention, performance, and satisfaction with virtual training environments. Users' gaze behavior and subjective responses revealed many challenges that will help future researchers develop assistive instructions within this virtual educational platform.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"34 6","pages":"649-666"},"PeriodicalIF":2.2,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435815","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":"Analysis on pulse rate variability for pilot workload assessment based on wearable sensor","authors":"Yunbiao Wang,&nbsp;Chenyang Zhang,&nbsp;Chenglin Liu,&nbsp;Kun Liu,&nbsp;Fang Xu,&nbsp;Jixue Yuan,&nbsp;Chaozhe Jiang,&nbsp;Chuang Liu,&nbsp;Weiwei Cao","doi":"10.1002/hfm.21053","DOIUrl":"https://doi.org/10.1002/hfm.21053","url":null,"abstract":"<p>The workload levels of pilots directly affect their flight performance and the safety of the whole flight. To explore the real-time workload of pilots in different flight phases (takeoff, cruise, and landing), this paper leveraged National Aeronautics and Space Administration Task Load Index (NASA-TLX), a subjective evaluation scale, and PhotoPlethysmoGraphy (PPG) signals of 21 participants using a flight simulator and a wearable sensor. First, the workloads of pilots under different phases were explored by the NASA-TLX scales; secondly, the pulse rate variability (PRV) features were selected by variance analysis and random forest importance evaluation; finally, the performances of the k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM) were compared for workload levels identification. It is shown that the workloads are ranked as follows: landing &gt; takeoff &gt; cruise. SDNN, CVCD, CVNNI, LF, TP, SD2, and SD2/SD1 were used as selected features with significant differences in different flight phases. In addition, machine learning models can effectively identify pilot workloads, and feature selection enhances the performance of both KNN and RF classifiers. The best identification of workload was achieved using the selected PRV features as inputs to the KNN classifier, with an average accuracy of 88.9%. Our results indicate that the KNN classifier and PRV features are suitable for identifying pilot workload. The pilot workload is highest during the landing phase, which provides a reference for flight safety management. The findings from this research could contribute to developing a robust pilot workload detection system and improve current flight operation safety regulations.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"34 6","pages":"635-648"},"PeriodicalIF":2.2,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435814","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 novel deep learning-based technique for driver drowsiness detection","authors":"Prithwijit Mukherjee,&nbsp;Anisha Halder Roy","doi":"10.1002/hfm.21056","DOIUrl":"https://doi.org/10.1002/hfm.21056","url":null,"abstract":"<p>Every year, many people lose their lives because of road accidents. It is evident from statistics that drowsiness is one of the main causes of a large number of car accidents. In our research, we wish to solve this major problem by measuring the drowsiness level of the human brain while driving. The study aims to develop a novel technique to detect different alertness levels (i.e., awake, moderately drowsy, and maximally drowsy) of a person while driving. A hybrid model using a stacked autoencoder and hyperbolic tangent Long Short-Term Memory (TLSTM) network with attention mechanism is designed for this purpose. The designed model uses different biopotential signals, such as electroencephalography (EEG), facial electromyography (EMG), and different biomarkers, such as pulse rate, respiration rate galvanic skin response, and head movement to detect a person's alertness level. Here, the stacked autoencoder model is used for automated feature extraction. TLSTM is used to predict a person's alertness level using stacked autoencoder network-extracted features. The proposed model can classify awake, moderately drowsy, and maximally drowsy states of a person with accuracies of 99%, 98.3%, and 98.6%, respectively. The novel contributions of the paper includes (i) incorporation of an attention mechanism into the TLSTM network of the proposed hybrid model to focus on the emphatic states to enhance classification accuracy, and (ii) utilization of EEG, facial EMG, pulse rate, respiration rate, galvanic skin reaction, and head movement pattern to assess a person's alertness level.</p>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"34 6","pages":"667-684"},"PeriodicalIF":2.2,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435816","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}