Matheus Herman Bernardim Andrade, Anderson Luis Szejka, Fernando Mas
{"title":"制造模型(MfM)方法在航空航天钣金件制造中的应用","authors":"Matheus Herman Bernardim Andrade, Anderson Luis Szejka, Fernando Mas","doi":"10.4028/p-p5b5ar","DOIUrl":null,"url":null,"abstract":"With the advancement of globalization and the growth of Industry 4.0, it is necessary to apply new concepts and methods for manufacturing to increase the productive capacity and efficiency of processes. These concepts allow the application of intelligent manufacturing within the Aerospace industry, responsible for transforming manufacturing processes using software technologies based on artificial intelligence, to automate the Sheet Metal Parts modeling process and get more accurate data. Therefore, it applies to Models for Manufacturing (MfM) in product projects, a recent methodology that presents an organization for formally defined information and knowledge. However, MfM does not consider information tracing and inconsistency analysis in the modeling phases. Based on this paradigm, a solution is proposed by developing and adopting methods, processes, and tools of Ontology-Based Engineering based on the MfM model to obtain data. In addition, Semantic Technologies are used for data processing through an OWL structure, also formalizing the information through semantic rules in SWRL. This research aims to: (I) Obtain data extracted from Sheet Metal Parts and structure them from ontology; (II) Formalize information about this data using semantic rules; (III) Validate information between product and manufacturing projects to identify and address inconsistencies in advance.","PeriodicalId":46357,"journal":{"name":"Advances in Science and Technology-Research Journal","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Models for Manufacturing (MfM) Methodology to Aerospace Sheet Metal Parts Manufacturing\",\"authors\":\"Matheus Herman Bernardim Andrade, Anderson Luis Szejka, Fernando Mas\",\"doi\":\"10.4028/p-p5b5ar\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the advancement of globalization and the growth of Industry 4.0, it is necessary to apply new concepts and methods for manufacturing to increase the productive capacity and efficiency of processes. These concepts allow the application of intelligent manufacturing within the Aerospace industry, responsible for transforming manufacturing processes using software technologies based on artificial intelligence, to automate the Sheet Metal Parts modeling process and get more accurate data. Therefore, it applies to Models for Manufacturing (MfM) in product projects, a recent methodology that presents an organization for formally defined information and knowledge. However, MfM does not consider information tracing and inconsistency analysis in the modeling phases. Based on this paradigm, a solution is proposed by developing and adopting methods, processes, and tools of Ontology-Based Engineering based on the MfM model to obtain data. In addition, Semantic Technologies are used for data processing through an OWL structure, also formalizing the information through semantic rules in SWRL. This research aims to: (I) Obtain data extracted from Sheet Metal Parts and structure them from ontology; (II) Formalize information about this data using semantic rules; (III) Validate information between product and manufacturing projects to identify and address inconsistencies in advance.\",\"PeriodicalId\":46357,\"journal\":{\"name\":\"Advances in Science and Technology-Research Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Science and Technology-Research Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4028/p-p5b5ar\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Science and Technology-Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4028/p-p5b5ar","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Application of Models for Manufacturing (MfM) Methodology to Aerospace Sheet Metal Parts Manufacturing
With the advancement of globalization and the growth of Industry 4.0, it is necessary to apply new concepts and methods for manufacturing to increase the productive capacity and efficiency of processes. These concepts allow the application of intelligent manufacturing within the Aerospace industry, responsible for transforming manufacturing processes using software technologies based on artificial intelligence, to automate the Sheet Metal Parts modeling process and get more accurate data. Therefore, it applies to Models for Manufacturing (MfM) in product projects, a recent methodology that presents an organization for formally defined information and knowledge. However, MfM does not consider information tracing and inconsistency analysis in the modeling phases. Based on this paradigm, a solution is proposed by developing and adopting methods, processes, and tools of Ontology-Based Engineering based on the MfM model to obtain data. In addition, Semantic Technologies are used for data processing through an OWL structure, also formalizing the information through semantic rules in SWRL. This research aims to: (I) Obtain data extracted from Sheet Metal Parts and structure them from ontology; (II) Formalize information about this data using semantic rules; (III) Validate information between product and manufacturing projects to identify and address inconsistencies in advance.