G. Kakandikar, Omkar Kulkarni, Sujata L. Patekar, Trupti Bhoskar
{"title":"用萤火虫算法优化汽车尾盖断裂","authors":"G. Kakandikar, Omkar Kulkarni, Sujata L. Patekar, Trupti Bhoskar","doi":"10.1504/ijsi.2020.106396","DOIUrl":null,"url":null,"abstract":"Deep drawing is a manufacturing process in which sheet metal is progressively formed into a three-dimensional shape through the mechanical action of a punch forming the metal inside die. The flow of metal is complex mechanism. Pots, pans for cooking, containers, sinks, automobile body parts such as panels and gas tanks are among a few of the items manufactured by deep drawing. Uniform strain distribution in forming results in quality components. The predominant failure modes in sheet metal parts are springback, wrinkling and fracture. Fracture or necking occurs in a drawn part, which is under excessive tensile loading. The prediction and prevention of fracture depends on the design of tooling and selection of process parameters. Firefly algorithm is one of the nature inspired optimisation algorithms and is inspired by firefly's behaviour in nature. The proposed research work presents novel approach to optimise fracture in automotive component-tail cap. The optimisation problem has been defined to optimise fracture within the constraints of radius on die, radius on punch and blank holding force. Fire fly algorithm has been applied to find optimum process parameters. Numerical experimentation has been conducted to validate the results.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"104 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimising fracture in automotive tail cap by firefly algorithm\",\"authors\":\"G. Kakandikar, Omkar Kulkarni, Sujata L. Patekar, Trupti Bhoskar\",\"doi\":\"10.1504/ijsi.2020.106396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep drawing is a manufacturing process in which sheet metal is progressively formed into a three-dimensional shape through the mechanical action of a punch forming the metal inside die. The flow of metal is complex mechanism. Pots, pans for cooking, containers, sinks, automobile body parts such as panels and gas tanks are among a few of the items manufactured by deep drawing. Uniform strain distribution in forming results in quality components. The predominant failure modes in sheet metal parts are springback, wrinkling and fracture. Fracture or necking occurs in a drawn part, which is under excessive tensile loading. The prediction and prevention of fracture depends on the design of tooling and selection of process parameters. Firefly algorithm is one of the nature inspired optimisation algorithms and is inspired by firefly's behaviour in nature. The proposed research work presents novel approach to optimise fracture in automotive component-tail cap. The optimisation problem has been defined to optimise fracture within the constraints of radius on die, radius on punch and blank holding force. Fire fly algorithm has been applied to find optimum process parameters. Numerical experimentation has been conducted to validate the results.\",\"PeriodicalId\":44265,\"journal\":{\"name\":\"International Journal of Swarm Intelligence Research\",\"volume\":\"104 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2020-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Swarm Intelligence Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijsi.2020.106396\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Swarm Intelligence Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijsi.2020.106396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Optimising fracture in automotive tail cap by firefly algorithm
Deep drawing is a manufacturing process in which sheet metal is progressively formed into a three-dimensional shape through the mechanical action of a punch forming the metal inside die. The flow of metal is complex mechanism. Pots, pans for cooking, containers, sinks, automobile body parts such as panels and gas tanks are among a few of the items manufactured by deep drawing. Uniform strain distribution in forming results in quality components. The predominant failure modes in sheet metal parts are springback, wrinkling and fracture. Fracture or necking occurs in a drawn part, which is under excessive tensile loading. The prediction and prevention of fracture depends on the design of tooling and selection of process parameters. Firefly algorithm is one of the nature inspired optimisation algorithms and is inspired by firefly's behaviour in nature. The proposed research work presents novel approach to optimise fracture in automotive component-tail cap. The optimisation problem has been defined to optimise fracture within the constraints of radius on die, radius on punch and blank holding force. Fire fly algorithm has been applied to find optimum process parameters. Numerical experimentation has been conducted to validate the results.
期刊介绍:
The mission of the International Journal of Swarm Intelligence Research (IJSIR) is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications.