Faculty of Mechatronics and Aerospace, Military University of Technology, Kaliskiego 2 Street, 00-908 Warsaw, Poland.
Faculty of Electronics, Military University of Technology, Kaliskiego 2 Street, 00-908 Warsaw, Poland.
Sensors (Basel). 2020 Sep 19;20(18):5378. doi: 10.3390/s20185378.
The article presents the results of computer simulations related to the selection and optimization of the parameters of robotic packing process of one type of product. Taking the required performance of the robotic production line as a basis, we proposed its configuration using the RobotStudio environment for offline robot programming and virtual controller technology. Next, a methodology for the validation of the adopted assumptions was developed, based on a wide range of input data and a precise representation of the applicable conditions in the packaging process of one type of product. This methodology included test scenarios repeated an appropriate number of times in order to obtain the result data with the desired reliability and repeatability. The main element of the research was a computer simulation of the station based on the Picking PowerPac package. It was assumed that the products on the technological line are generated pseudo-randomly, thus reflecting the real working conditions. The result of the conducted works is the optimal operating speed of industrial robots and conveyors. The developed methodology allows for multifaceted analyses of the key parameters of the technological process (e.g., the number of active robots and their load, speed of conveyors, and station efficiency). We paid special attention to the occurrence of anomalies, i.e., emergency situations in the form of "halting" the operation of chosen robots and their impact on the obtained quality of the industrial process. As a result of the simulations, numerical values were obtained, maximum efficiency, with regard to maximum overflow of items of 5%, for LB algorithm was equal to 1188 completed containers per hour, with conveyors speeds of 270 mm/s and 165 mm/s. This efficiency was possible at robot speeds R1 = 6450 mm/s, R2 = 7500 mm/s, R3 = 6500 mm/s, R4 = 6375 mm/s, R5 = 5500 mm/s, R6 = 7200 mm/s. The ATC algorithm reached efficiency of 1332 containers per hour with less than 5% overflown items, with conveyor speeds of 310 mm/s and 185 mm/s. This efficiency was possible at robot speeds R1 = 7500 mm/s, R2 = 7500 mm/s, R3 = 7200 mm/s, R4 = 7000 mm/s, R5 = 6450 mm/s, R6 = 6300 mm/s. Tests carried out for emergency situations showed that the LB algorithm does not allow for automatic continuation of the process, while the ATC algorithm assured production efficiency of 94% to 98% of the maximum station efficiency.
本文介绍了与一种产品的机器人包装过程的参数选择和优化相关的计算机模拟的结果。基于机器人生产线的所需性能，我们使用 RobotStudio 环境为离线机器人编程和虚拟控制器技术提出了其配置。接下来，我们开发了一种验证所采用假设的方法，该方法基于广泛的输入数据和对一种产品包装过程中适用条件的精确表示。该方法包括重复进行适当次数的测试场景，以获得具有所需可靠性和可重复性的结果数据。研究的主要内容是基于 Picking PowerPac 包装的工作站的计算机模拟。假设技术线上的产品是伪随机生成的，从而反映了真实的工作条件。进行的工作的结果是工业机器人和输送机的最佳运行速度。所开发的方法允许对工艺过程的关键参数进行多方面的分析（例如，活动机器人的数量及其负载、输送机的速度和工作站的效率）。我们特别注意异常的发生，即选择的机器人“停止”运行及其对工业过程获得的质量的影响等紧急情况。通过模拟，我们获得了数值，对于 LB 算法，最大效率为 5%的最大溢出量时，为 1188 个装满的容器/小时，输送机速度为 270mm/s 和 165mm/s。在机器人速度 R1=6450mm/s、R2=7500mm/s、R3=6500mm/s、R4=6375mm/s、R5=5500mm/s、R6=7200mm/s 的情况下，实现了这种效率。当输送机速度为 310mm/s 和 185mm/s 时，ATC 算法达到了 1332 个装满的容器/小时，最大溢出量小于 5%。在机器人速度 R1=7500mm/s、R2=7500mm/s、R3=7200mm/s、R4=7000mm/s、R5=6450mm/s、R6=6300mm/s 的情况下，实现了这种效率。针对紧急情况进行的测试表明，LB 算法不允许自动继续该过程，而 ATC 算法确保了 94%到 98%的最大工作站效率的生产效率。
