...
首页> 外文期刊>Procedia CIRP >Prediction and estimation model of energy demand of the AMR with cobot for the designed path in automated logistics systems
【24h】

Prediction and estimation model of energy demand of the AMR with cobot for the designed path in automated logistics systems

机译:自动物流系统中设计路径的COBOT预测与估计模型。

获取原文
           

摘要

The ecosystem of the Industry 4.0 involves many new technologies, such as autonomous mobile robots (AMR) and cobots (collaborative robots), these are characterized with higher flexibility and cost effectiveness which makes them more suitable for automated internal logistics systems. The evaluation of energy consumption of AMRs for a designed path in a real case scenario using analytical tools are challenging. This paper proposes a method of evaluation of the sustainability of new technologies of Industry 4.0 in internal logistics.The proposed framework demonstrates data management technique of the industrial robots. Since, the AMR with manipulator perform different tasks as a single system in logistics there is big demand to develop model of cyber physical system. During task execution measured robots’ physical parameters used as input data to perform analytics. Moreover, acquired data from different condition use cases have been used to monitor the battery behaviour of the AMR and preliminary results of the linear regression model is presented.
机译:行业4.0的生态系统涉及许多新技术,如自主移动机器人(AMR)和Cobots(协作机器人),这些技术具有更高的灵活性和成本效益,使其更适合自动化内部物流系统。使用分析工具的实际情况地,在实际情况下,在实际情况下对设计路径的能耗评估是具有挑战性的。本文提出了一种评估内部物流工业4.0新技术可持续性的方法。建议的框架展示了工业机器人的数据管理技术。由于,与机械手的AMR执行不同的任务作为物流中的单一系统,有很大的要求开发网络物理系统的模型。在任务执行期间,测量机器人的物理参数用作输入数据以执行分析。此外,已经使用来自不同条件用例的获取数据来监测AMR的电池行为,并提出了线性回归模型的初步结果。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号