{"title":"考虑认知负荷的聚合物加工流变仪可靠性预测","authors":"W. Hou, Jing Yao, Yongming Liu","doi":"10.1109/ICRSE.2017.8030780","DOIUrl":null,"url":null,"abstract":"In order to evaluate the reliability of a certain polymer processing rheometer accurately and effectively, and solve the problem of reliability prediction error is bigger which due to ignoring the man-machine interaction existing in the process of reliability prediction, we put forward building a reliability prediction model by using the combination of cognitive load evaluation technique and grading method. Finally, calculated the reliability level based on the corrected failure rate of each component and the reliability relationship of individual components with polymer processing rheometer. The prediction results showed that MTBF of the overall polymer processing rheometer was 2610h, exceeding 2000h which was stipulated in the specification. At the same time, by analyzing the prediction result, it was concluded that main measure and control module was the weak module of the whole polymer processing rheometer, and bracket assembly of main measure and control module and single screw capillary module was the weak component.","PeriodicalId":317626,"journal":{"name":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","volume":"4 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reliability prediction for polymer processing rheometer considering the cognitive load\",\"authors\":\"W. Hou, Jing Yao, Yongming Liu\",\"doi\":\"10.1109/ICRSE.2017.8030780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to evaluate the reliability of a certain polymer processing rheometer accurately and effectively, and solve the problem of reliability prediction error is bigger which due to ignoring the man-machine interaction existing in the process of reliability prediction, we put forward building a reliability prediction model by using the combination of cognitive load evaluation technique and grading method. Finally, calculated the reliability level based on the corrected failure rate of each component and the reliability relationship of individual components with polymer processing rheometer. The prediction results showed that MTBF of the overall polymer processing rheometer was 2610h, exceeding 2000h which was stipulated in the specification. At the same time, by analyzing the prediction result, it was concluded that main measure and control module was the weak module of the whole polymer processing rheometer, and bracket assembly of main measure and control module and single screw capillary module was the weak component.\",\"PeriodicalId\":317626,\"journal\":{\"name\":\"2017 Second International Conference on Reliability Systems Engineering (ICRSE)\",\"volume\":\"4 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Second International Conference on Reliability Systems Engineering (ICRSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRSE.2017.8030780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Second International Conference on Reliability Systems Engineering (ICRSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRSE.2017.8030780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reliability prediction for polymer processing rheometer considering the cognitive load
In order to evaluate the reliability of a certain polymer processing rheometer accurately and effectively, and solve the problem of reliability prediction error is bigger which due to ignoring the man-machine interaction existing in the process of reliability prediction, we put forward building a reliability prediction model by using the combination of cognitive load evaluation technique and grading method. Finally, calculated the reliability level based on the corrected failure rate of each component and the reliability relationship of individual components with polymer processing rheometer. The prediction results showed that MTBF of the overall polymer processing rheometer was 2610h, exceeding 2000h which was stipulated in the specification. At the same time, by analyzing the prediction result, it was concluded that main measure and control module was the weak module of the whole polymer processing rheometer, and bracket assembly of main measure and control module and single screw capillary module was the weak component.