{"title":"制造中人机协作中的人为错误识别与风险优先排序","authors":"Li Liu, Shixiong Sheng, Jiansi Li, Siu Shing Man","doi":"10.1002/hfm.70012","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Human error recognition and subsequent prioritization are the most important tasks in the human–robot reliability analysis. This study aims to address the issue of human error in human–robot collaboration (HRC) by developing a model for identifying and assessing risks. First, the key tasks performed by operators during HRC were identified using the hierarchical task analysis, and a cognitive model was built based on information processing theory. This model breaks down the collaboration process into stages and identifies potential human errors at each step. Next, failure modes and effects analysis and evidence reasoning were applied to quantify the risk levels of these errors. Finally, the risks associated with human errors were measured, ranked, and compared with existing studies, and recommendations were made. The findings showed that the leading causes of safety risks in HRC are fatigue, illegal operations, error operations, misjudgments, and misperception. The perception stage of the process was found to carry the highest risk level, which means operators are more likely to make errors during the perception stage than during decision or execution, largely due to factors such as fatigue, distraction, and misperception. These results provide important theoretical support for improving safety in HRC and offer practical suggestions for refining risk management strategies in HRC systems.</p>\n </div>","PeriodicalId":55048,"journal":{"name":"Human Factors and Ergonomics in Manufacturing & Service Industries","volume":"35 3","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Human Error Identification and Risk Prioritization in Human–Robot Collaboration in Manufacturing\",\"authors\":\"Li Liu, Shixiong Sheng, Jiansi Li, Siu Shing Man\",\"doi\":\"10.1002/hfm.70012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>Human error recognition and subsequent prioritization are the most important tasks in the human–robot reliability analysis. This study aims to address the issue of human error in human–robot collaboration (HRC) by developing a model for identifying and assessing risks. First, the key tasks performed by operators during HRC were identified using the hierarchical task analysis, and a cognitive model was built based on information processing theory. This model breaks down the collaboration process into stages and identifies potential human errors at each step. Next, failure modes and effects analysis and evidence reasoning were applied to quantify the risk levels of these errors. Finally, the risks associated with human errors were measured, ranked, and compared with existing studies, and recommendations were made. The findings showed that the leading causes of safety risks in HRC are fatigue, illegal operations, error operations, misjudgments, and misperception. The perception stage of the process was found to carry the highest risk level, which means operators are more likely to make errors during the perception stage than during decision or execution, largely due to factors such as fatigue, distraction, and misperception. These results provide important theoretical support for improving safety in HRC and offer practical suggestions for refining risk management strategies in HRC systems.</p>\\n </div>\",\"PeriodicalId\":55048,\"journal\":{\"name\":\"Human Factors and Ergonomics in Manufacturing & Service Industries\",\"volume\":\"35 3\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Factors and Ergonomics in Manufacturing & Service Industries\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/hfm.70012\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Factors and Ergonomics in Manufacturing & Service Industries","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hfm.70012","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Human Error Identification and Risk Prioritization in Human–Robot Collaboration in Manufacturing
Human error recognition and subsequent prioritization are the most important tasks in the human–robot reliability analysis. This study aims to address the issue of human error in human–robot collaboration (HRC) by developing a model for identifying and assessing risks. First, the key tasks performed by operators during HRC were identified using the hierarchical task analysis, and a cognitive model was built based on information processing theory. This model breaks down the collaboration process into stages and identifies potential human errors at each step. Next, failure modes and effects analysis and evidence reasoning were applied to quantify the risk levels of these errors. Finally, the risks associated with human errors were measured, ranked, and compared with existing studies, and recommendations were made. The findings showed that the leading causes of safety risks in HRC are fatigue, illegal operations, error operations, misjudgments, and misperception. The perception stage of the process was found to carry the highest risk level, which means operators are more likely to make errors during the perception stage than during decision or execution, largely due to factors such as fatigue, distraction, and misperception. These results provide important theoretical support for improving safety in HRC and offer practical suggestions for refining risk management strategies in HRC systems.
期刊介绍:
The purpose of Human Factors and Ergonomics in Manufacturing & Service Industries is to facilitate discovery, integration, and application of scientific knowledge about human aspects of manufacturing, and to provide a forum for worldwide dissemination of such knowledge for its application and benefit to manufacturing industries. The journal covers a broad spectrum of ergonomics and human factors issues with a focus on the design, operation and management of contemporary manufacturing systems, both in the shop floor and office environments, in the quest for manufacturing agility, i.e. enhancement and integration of human skills with hardware performance for improved market competitiveness, management of change, product and process quality, and human-system reliability. The inter- and cross-disciplinary nature of the journal allows for a wide scope of issues relevant to manufacturing system design and engineering, human resource management, social, organizational, safety, and health issues. Examples of specific subject areas of interest include: implementation of advanced manufacturing technology, human aspects of computer-aided design and engineering, work design, compensation and appraisal, selection training and education, labor-management relations, agile manufacturing and virtual companies, human factors in total quality management, prevention of work-related musculoskeletal disorders, ergonomics of workplace, equipment and tool design, ergonomics programs, guides and standards for industry, automation safety and robot systems, human skills development and knowledge enhancing technologies, reliability, and safety and worker health issues.