Ankur Verma, Seog-Chan Oh, James W. Wells, J. Arinez, S. Kumara
{"title":"Conveyer-Less Matrix Assembly Layout Design to Maximize Labor Productivity and Footprint Usage","authors":"Ankur Verma, Seog-Chan Oh, James W. Wells, J. Arinez, S. Kumara","doi":"10.1115/imece2022-94628","DOIUrl":null,"url":null,"abstract":"\n The automotive industry has used in-line conveyor systems to move vehicles through the general assembly process since the early days of vehicle manufacturing in the 20th century. With products shifting to EVs (Electric Vehicle) and the emergence of AMRs (Autonomous Mobile Robot), there is an opportunity to transform the assembly process into a more flexible conveyor-less matrix-based system. One key development need is how to structure and optimize such an asynchronous system. This paper presents a new methodology for designing a conveyor-less matrix assembly layout to maximize labor productivity, workstation utilization, and footprint usage, while minimizing the system costs, and cycle times. Specifically, we develop an asynchronous assembly system for the automotive trim area. We aim to answer the question: How do we decide on an optimum number of workstations for the asynchronous assembly system, such that productivity and ROI are maximized? For this, we use cycle times, the number of operations per workstation, reference heights, and precedence graphs as input variables. Similarity matrices are used to quantify the similarity of tools, ergonomics, and human operations between workstations. Workstation utilization percentage and makespan are the metrics used to compare between alternative layouts. Finally, we perform a cost and makespan analysis to evaluate the ratio of trim area costs to total revenue, calculate makespan, and report the best layout found in the study. Quantifying subjective data, repeatability, less setup, and simulation time are the attributes that make this methodology valuable to any virtual commissioning software, an integral part of the smart manufacturing ecosystem.","PeriodicalId":113474,"journal":{"name":"Volume 2B: Advanced Manufacturing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 2B: Advanced Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2022-94628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The automotive industry has used in-line conveyor systems to move vehicles through the general assembly process since the early days of vehicle manufacturing in the 20th century. With products shifting to EVs (Electric Vehicle) and the emergence of AMRs (Autonomous Mobile Robot), there is an opportunity to transform the assembly process into a more flexible conveyor-less matrix-based system. One key development need is how to structure and optimize such an asynchronous system. This paper presents a new methodology for designing a conveyor-less matrix assembly layout to maximize labor productivity, workstation utilization, and footprint usage, while minimizing the system costs, and cycle times. Specifically, we develop an asynchronous assembly system for the automotive trim area. We aim to answer the question: How do we decide on an optimum number of workstations for the asynchronous assembly system, such that productivity and ROI are maximized? For this, we use cycle times, the number of operations per workstation, reference heights, and precedence graphs as input variables. Similarity matrices are used to quantify the similarity of tools, ergonomics, and human operations between workstations. Workstation utilization percentage and makespan are the metrics used to compare between alternative layouts. Finally, we perform a cost and makespan analysis to evaluate the ratio of trim area costs to total revenue, calculate makespan, and report the best layout found in the study. Quantifying subjective data, repeatability, less setup, and simulation time are the attributes that make this methodology valuable to any virtual commissioning software, an integral part of the smart manufacturing ecosystem.