Collaborative and traditional robotic assembly: a comparison model
Collaborative and traditional robotic assembly: a comparison model
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DOI：
10.1007/s00170-018-03247-z
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发表时间：
2019-06-01
影响因子：
3.4
通讯作者：
Rosati, Giulio
中科院分区：
文献类型：
--
作者：
Faccio, Maurizio;Bottin, Matteo;Rosati, Giulio
在过去的十年里，机器人制造商已经开始生产协作式工业机器人，这种机器人可以在与人类操作员安全共享工作空间的同时工作。通过这种方式，机器人的重复性与人类的灵巧性相结合，可以将自动化组装提升到一个新的灵活性水平。本文的目的是研究这种被称为协同装配系统(CAS)的系统能够比传统的手动或自动装配系统更好地执行的条件。为了进行比较，考虑了生产能力和单位直接生产成本。在传统的自动化装配系统中，这样的性能数据的估计是直接的，但在协作系统的情况下变得更加复杂。事实上，人类和机器人之间的任务分配以及它们在装配过程中相互协作/干扰的方式都会影响CAS的吞吐量。为了考虑这些参数，我们引入了一组系统变量和一个数学模型，用来估计在工业场景中实施CAS的真正便利性。本文应用该模型对复杂适应系统与手工装配和非协同自动装配进行了比较，得到了文献中的参数，并进行了实例研究。最后，推导出一组与最大化CAS性能的任务分配相关的实现条件。
In the last decade, robot manufacturers have started to produce collaborative industrial robots, that can work while safely sharing the workspace with a human operator. In this way, robot repeatability, combined with human dexterity, can move automated assembly to a new level of flexibility. The aim of this paper is to investigate the conditions at which such systems, called collaborative assembly systems (CAS), can be better performing than the traditional manual or automated assembly systems. Throughput and unit direct production cost are considered for the comparison. The estimation of such performance figures, which is straightforward in traditional automated assembly systems, becomes more complex in the case of collaborative systems. In fact, both task allocation between the human and the robot, and the way they collaborate/interfere with each other during assembly, affect the throughput of CAS. With the aim of taking into account such parameters, we introduce a set of system variables and a mathematical model which allow to estimate the real convenience of the implementation of CAS in the industrial scenario. In the paper, the model is applied to compare CAS to manual assembly and to noncollaborative automated assembly, both with parameters derived from the literature and in a case study. Finally, a set of implementation conditions is derived, related to the task allocation that maximises CAS performance.