{"title":"基于二次标化方法的双目标工效装配线平衡模型","authors":"Busra N. Yetkin, Emin Kahya","doi":"10.1002/hfm.20967","DOIUrl":null,"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":2.2000,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"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\":null,\"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\":2.2000,\"publicationDate\":\"2022-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"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.20967\",\"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.20967","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}
A bi-objective ergonomic assembly line balancing model with conic scalarization method
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.
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.