N. Swingle, A. Brasington, J. Halbritter, R. Harik
{"title":"Automated Fiber Placement Laminate Level Optimization for Mitigation of Through Thickness Defect Stacking","authors":"N. Swingle, A. Brasington, J. Halbritter, R. Harik","doi":"10.33599/sj.v59no6.03","DOIUrl":null,"url":null,"abstract":"Manufacturing composite structures with Automated Fiber Placement (AFP) requires detailed process planning that is rigorous and time consuming. To facilitate, accelerate and perpetuate process planning knowledge, the Computer Aided Process Planning (CAPP) tool was developed. CAPP assists process planners in identifying optimal layup strategies for each ply of a laminate. This paper expands the established framework for analyzing defect stack-up through thickness of a laminate. Four different combinatorial optimization algorithms are implemented and evaluated: genetic algorithm, differential evolution, particle swarm, and greedy search. The algorithms identify optimal combinations of ply-level layup strategies by analyzing defect stacking using two objective functions. These approaches are evaluated through a digital case study performed on a complex tool surface. The result is a streamlined methodology for comparing different laminate-level manufacturing strategies and minimizing the through thickness defect stack-up.","PeriodicalId":49577,"journal":{"name":"SAMPE Journal","volume":"55 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAMPE Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.33599/sj.v59no6.03","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Manufacturing composite structures with Automated Fiber Placement (AFP) requires detailed process planning that is rigorous and time consuming. To facilitate, accelerate and perpetuate process planning knowledge, the Computer Aided Process Planning (CAPP) tool was developed. CAPP assists process planners in identifying optimal layup strategies for each ply of a laminate. This paper expands the established framework for analyzing defect stack-up through thickness of a laminate. Four different combinatorial optimization algorithms are implemented and evaluated: genetic algorithm, differential evolution, particle swarm, and greedy search. The algorithms identify optimal combinations of ply-level layup strategies by analyzing defect stacking using two objective functions. These approaches are evaluated through a digital case study performed on a complex tool surface. The result is a streamlined methodology for comparing different laminate-level manufacturing strategies and minimizing the through thickness defect stack-up.
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