The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system （MES）. Accompanied with turning the MES into service-oriented manufacturing execution system （so-ME...The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system （MES）. Accompanied with turning the MES into service-oriented manufacturing execution system （so-MES）, real-time e-quality tracking （e-QT）, in which real-time data are computed, has played more and more important roles in manufacturing. This paper presents an e-QT model through the study of real-time status data tracking and quality data collecting. An implementing architecture of the e-QT model is constructed on the basis of radio frequency identification devices （RFID） data-tracking network. In order to develop the e-QT system, some key enabling technologies, such as configuration, data collection, and data processing, etc, are studied. The relation schema between hardware is built for the RFID data-tracking network based on the configuration technique. Real-time data are sampled by using data collecting technique. Furthermore, real-time status and quality data in a shop-floor can be acquired in terms of using the real-time data computing method. Finally, a prototype system is developed and a running example is given so as to verify the feasibility of methods proposed in this paper. The proposed research provides effective e-quality tracking theoretical foundation through the use of RFID technology for the discrete manufacturing.展开更多
This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-pl...This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-play (PnP) application modules of the dc-IUS are presented in the fields of machining process and quality control,material flow and inventory control,and factory resource tracking. Different schemes are discussed about how and where to apply these functions. Then some running examples are studied to demonstrate the feasibility and reliability of dc-IUS. At last,the challenges of applying WM are discussed and a conclusion is given.展开更多
目的阐明2016—2022年深圳市≥55岁常住人口的肿瘤疾病负担。方法测算2016—2022年33个肿瘤类型造成的早死损失寿命年(years of life lost,YLLs)、伤残损失寿命年(years lost due to disability,YLDs)、伤残调整寿命年(disability-adjus...目的阐明2016—2022年深圳市≥55岁常住人口的肿瘤疾病负担。方法测算2016—2022年33个肿瘤类型造成的早死损失寿命年(years of life lost,YLLs)、伤残损失寿命年(years lost due to disability,YLDs)、伤残调整寿命年(disability-adjusted life years,DALYs)。采用Joinpoint回归模型计算DALYs粗率的平均年度变化百分比,以量化其时间变化趋势;构建年龄-时期-队列模型,分解重点肿瘤的YLLs粗率和YLDs粗率,以估计其年龄、时期和出生队列效应。结果≥55岁常住人口DALYs粗率和YLLs粗率的前3位肿瘤类型相同,从高到低依次为:(1)气管、支气管和肺癌;(2)肝癌;(3)结肠癌和直肠癌。YLDs粗率的前3位肿瘤类型从高到低依次为:(1)结肠癌和直肠癌;(2)气管、支气管和肺癌;(3)乳腺癌。重点肿瘤的年龄效应从55岁起上升(最高率比=5461.86,95%CI:5121.36~5824.99);1956年后的出生队列,结肠癌和直肠癌(最高率比=1.81,95%CI:1.68~1.95)、胰腺癌(最高率比=1.94,95%CI:1.74~2.15)的风险升高,肝癌(最高率比=0.77,95%CI:0.73~0.82)风险降低;与2020年相比,重点肿瘤的时期效应于2021年升高(最高率比=1.08,95%CI:1.04~1.13),2022年降低(最低率比=0.91,95%CI:0.89~0.94)。结论深圳市≥55岁常住人口的肿瘤负担以气管、支气管和肺癌、肝癌、结肠癌和直肠癌为主。展开更多
基金supported by Natinoal Basic Research Program of China (973 Program, Grant No. 2011CB706805)National Natural Science Foundation of China (Grant No. 50875204)
文摘The method of acquiring the real-time data has influenced the implementation of the manufacturing execution system （MES）. Accompanied with turning the MES into service-oriented manufacturing execution system （so-MES）, real-time e-quality tracking （e-QT）, in which real-time data are computed, has played more and more important roles in manufacturing. This paper presents an e-QT model through the study of real-time status data tracking and quality data collecting. An implementing architecture of the e-QT model is constructed on the basis of radio frequency identification devices （RFID） data-tracking network. In order to develop the e-QT system, some key enabling technologies, such as configuration, data collection, and data processing, etc, are studied. The relation schema between hardware is built for the RFID data-tracking network based on the configuration technique. Real-time data are sampled by using data collecting technique. Furthermore, real-time status and quality data in a shop-floor can be acquired in terms of using the real-time data computing method. Finally, a prototype system is developed and a running example is given so as to verify the feasibility of methods proposed in this paper. The proposed research provides effective e-quality tracking theoretical foundation through the use of RFID technology for the discrete manufacturing.
基金National Natural Science Foundation of China(No.50875204)National Basic Research "973" Project(No.2011CB706805)
文摘This study proposesan over all framework for applying wireless manufacturing(WM)technologies in a smart factory and establishes a smart factory data computing and information using system (dc-IUS). Several plug-and-play (PnP) application modules of the dc-IUS are presented in the fields of machining process and quality control,material flow and inventory control,and factory resource tracking. Different schemes are discussed about how and where to apply these functions. Then some running examples are studied to demonstrate the feasibility and reliability of dc-IUS. At last,the challenges of applying WM are discussed and a conclusion is given.
文摘目的阐明2016—2022年深圳市≥55岁常住人口的肿瘤疾病负担。方法测算2016—2022年33个肿瘤类型造成的早死损失寿命年(years of life lost,YLLs)、伤残损失寿命年(years lost due to disability,YLDs)、伤残调整寿命年(disability-adjusted life years,DALYs)。采用Joinpoint回归模型计算DALYs粗率的平均年度变化百分比,以量化其时间变化趋势;构建年龄-时期-队列模型,分解重点肿瘤的YLLs粗率和YLDs粗率,以估计其年龄、时期和出生队列效应。结果≥55岁常住人口DALYs粗率和YLLs粗率的前3位肿瘤类型相同,从高到低依次为:(1)气管、支气管和肺癌;(2)肝癌;(3)结肠癌和直肠癌。YLDs粗率的前3位肿瘤类型从高到低依次为:(1)结肠癌和直肠癌;(2)气管、支气管和肺癌;(3)乳腺癌。重点肿瘤的年龄效应从55岁起上升(最高率比=5461.86,95%CI:5121.36~5824.99);1956年后的出生队列,结肠癌和直肠癌(最高率比=1.81,95%CI:1.68~1.95)、胰腺癌(最高率比=1.94,95%CI:1.74~2.15)的风险升高,肝癌(最高率比=0.77,95%CI:0.73~0.82)风险降低;与2020年相比,重点肿瘤的时期效应于2021年升高(最高率比=1.08,95%CI:1.04~1.13),2022年降低(最低率比=0.91,95%CI:0.89~0.94)。结论深圳市≥55岁常住人口的肿瘤负担以气管、支气管和肺癌、肝癌、结肠癌和直肠癌为主。
