{"title":"通过灵敏度分析和改进的QFD方法进行产品平台规划","authors":"Lei Zhang, Hansi Chen, Zhenlong Yuan, Xuening Chu","doi":"10.1109/IEEM.2018.8607691","DOIUrl":null,"url":null,"abstract":"The identification of platform parameters plays a key role to keep equilibrium between the external diversity and internal commonality. The relationship between the performance parameter and the design parameter in the traditional Quality of House (QoH) was evaluated by a correlation degree rather than an influence degree. The influence degree measures the design parameter’s influence on the performance parameter, and be more effective to evaluate the performance-design relationship. Hence, based on virtual orthogonal experiment, a method incorporated sensitivity analysis into the improved Quality Function Deployment (QFD) is proposed. Firstly, the virtual experiment scheme is designed through the orthogonal experiment table. Secondly, a virtual experiment environment is built by the built-in software, in which the design parameters are assigned with different values and the corresponding performances are monitored in real-time. Then the sensitivity matrix for design parameter is constructed to replace the correlation matrix in the QoH. Thereafter, the improved QFD can be used to identify the platform parameters. A case study for the smartphone of Samsung Galaxy A series is implemented to verify the effectiveness of the proposed method.","PeriodicalId":119238,"journal":{"name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Product Platform Planning through Sensitivity Analysis and Improved QFD Approach\",\"authors\":\"Lei Zhang, Hansi Chen, Zhenlong Yuan, Xuening Chu\",\"doi\":\"10.1109/IEEM.2018.8607691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The identification of platform parameters plays a key role to keep equilibrium between the external diversity and internal commonality. The relationship between the performance parameter and the design parameter in the traditional Quality of House (QoH) was evaluated by a correlation degree rather than an influence degree. The influence degree measures the design parameter’s influence on the performance parameter, and be more effective to evaluate the performance-design relationship. Hence, based on virtual orthogonal experiment, a method incorporated sensitivity analysis into the improved Quality Function Deployment (QFD) is proposed. Firstly, the virtual experiment scheme is designed through the orthogonal experiment table. Secondly, a virtual experiment environment is built by the built-in software, in which the design parameters are assigned with different values and the corresponding performances are monitored in real-time. Then the sensitivity matrix for design parameter is constructed to replace the correlation matrix in the QoH. Thereafter, the improved QFD can be used to identify the platform parameters. A case study for the smartphone of Samsung Galaxy A series is implemented to verify the effectiveness of the proposed method.\",\"PeriodicalId\":119238,\"journal\":{\"name\":\"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM.2018.8607691\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2018.8607691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Product Platform Planning through Sensitivity Analysis and Improved QFD Approach
The identification of platform parameters plays a key role to keep equilibrium between the external diversity and internal commonality. The relationship between the performance parameter and the design parameter in the traditional Quality of House (QoH) was evaluated by a correlation degree rather than an influence degree. The influence degree measures the design parameter’s influence on the performance parameter, and be more effective to evaluate the performance-design relationship. Hence, based on virtual orthogonal experiment, a method incorporated sensitivity analysis into the improved Quality Function Deployment (QFD) is proposed. Firstly, the virtual experiment scheme is designed through the orthogonal experiment table. Secondly, a virtual experiment environment is built by the built-in software, in which the design parameters are assigned with different values and the corresponding performances are monitored in real-time. Then the sensitivity matrix for design parameter is constructed to replace the correlation matrix in the QoH. Thereafter, the improved QFD can be used to identify the platform parameters. A case study for the smartphone of Samsung Galaxy A series is implemented to verify the effectiveness of the proposed method.