Proactive Scheduling for Job-Shop Based on Abnormal Event Monitoring of Workpieces and Remaining Useful Life Prediction of Tools in Wisdom Manufacturing Workshop
Proactive Scheduling for Job-Shop Based on Abnormal Event Monitoring of Workpieces and Remaining Useful Life Prediction of Tools in Wisdom Manufacturing Workshop
复制标题
智慧制造车间基于工件异常事件监测和刀具剩余寿命预测的车间主动调度
DOI：
10.3390/s19235254
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发表时间：
2019-11
期刊：
影响因子：
3.9
通讯作者：
Zhang Fudong
中科院分区：
文献类型：
--
作者：
Zhang Cunji;Yao Xifan;Tan Wei;Zhang Yue;Zhang Fudong
车间作业调度是制造企业提高响应速度、降低成本、改善服务的重要途径。提出了一种基于无线射频识别（RFID）和无线加速度传感器的工件异常事件监测和刀具剩余寿命预测的车间主动调度方法。首先，构建了加工作业的感知环境，建立了车间作业调度的数学模型，提出了主动调度的框架，采用了基于实时事件和预测事件的混合调度策略。然后，采用多目标双编码双进化双解码遗传算法（MD3GA）进行重调度。最后，通过一个实际的加工作业原型平台，对所提出的调度方法进行了验证.结果表明，该方法解决了加工工件的动态调度和主动调度的集成问题，减少了调度中冗余时间的浪费，避免了异常扰动的不利影响。
The job-shop scheduling is an important approach to manufacturing enterprises to improve response speed, reduce cost, and improve service. Proactive scheduling for job-shop based on abnormal event monitoring of workpieces and remaining useful life prediction of tools is proposed with radio frequency identification (RFID) and wireless accelerometer in this paper. Firstly, the perception environment of machining job is constructed, the mathematical model of job-shop scheduling is built, the framework of proactive scheduling is put forward, and the hybrid rescheduling strategy based on real-time events and predicted events is adopted. Then, the multi-objective, double-encoding, double-evolving, and double-decoding genetic algorithm (MD3GA) is used to reschedule. Finally, an actual prototype platform to machine job is built to verify the proposed scheduling method. It is shown that the proposed method solves the integration problem of dynamic scheduling and proactive scheduling of processing workpieces, reduces the waste of redundant time for the scheduling, and avoids the adverse impact on abnormal disturbances.
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DOI：
--
发表时间：
2014
期刊：
Computer Integrated Manufacturing Systems
影响因子：
--
作者：
Xi-fa Yao
通讯作者：
Xi-fa Yao
DOI：
10.1088/1757-899x/114/1/012052
发表时间：
2016-02
期刊：
IOP Conference Series: Materials Science and Engineering
影响因子：
--
作者：
Ari Setiawan;R. Wangsaputra;Yatna Yuwana Martawirya;Abdul Hakim Halim
通讯作者：
Ari Setiawan;R. Wangsaputra;Yatna Yuwana Martawirya;Abdul Hakim Halim
影响因子：
2.2
作者：
SRINIVAS, M;PATNAIK, LM
通讯作者：
PATNAIK, LM
影响因子：
22.7
作者：
D. Tennenhouse
通讯作者：
D. Tennenhouse
DOI：
--
发表时间：
2011
期刊：
Computer Integrated Manufacturing Systems
影响因子：
--
作者：
Xiao-hua Zhao
通讯作者：
Xiao-hua Zhao