Collaborative robot UR10 integration with CNC lathe Haas ST10

Abstract

The article describes the process of integrating a UR10 collaborative robot with a Haas ST10 CNC lathe. The integration has been implemented in order to operate the lathe in the technological process of shaft machining. The control systems for both devices were integrated using the digital input and output method. Correctness tests of the programmed machining cycle were carried out.

A Method of Assessing the Effectiveness of the Use of Available Resources When Implementing Production Processes

“…The method was developed in response to the research gap identified in the literature review [2,14,16,17,[27][28][29][30][31][35][36][37][38][39][40][41], which showed that there is a lack of a quantitative method for assessing the production processes effectiveness, which, taking into account the categorization of the production losses, would allow at the same time to evaluate the main areas (production and production-related) contribution in the generation of these losses. The literature review of the latest research in the field of manufacturing engineering [7,[19][20][21][22][23][24][25][26] showed that researchers are currently focusing more on developing digital tools for Industry 4.0 than on assessment methods. Since the method is complex and detailed, it can be used to support the verification of solutions used in multifactor processes-especially in the coming era of Industry 5.0, which emphasizes human collaboration with other resources.…”

“…In connection with the above, the aim of this work was to develop a method for assessing the effectiveness of the use of available resources when implementing production processes. Recent research in manufacturing engineering [7,[19][20][21][22][23][24][25][26] mainly focuses on developing Industry 4.0 ideology, e.g., developing smart production planning systems or implementing digital tools in the processes. The aspect of complex and detailed effectiveness assessment could influence (even in the era of Industry 4.0, even more so in the coming era of Industry 5.0) the development or at least the possibility of verifying the effectiveness of other proposals for new methods or improvements in manufacturing engineering.…”

Predictive Monitoring System for Autonomous Mobile Robots Battery Management Using the Industrial Internet of Things Technology

“…Predictive maintenance is an often adopted approach for mitigating downtime of automated production systems by monitoring the condition of parts of the system to perform maintenance when it is most cost-effective [ 1 ]. Predictive monitoring on the other hand focuses on optimizing the production in real time, based on the monitored parameters in industrial applications [ 2 , 3 ]. In the context of battery management, predictive monitoring is widely used in electric vehicles, where the battery state of charge data can be used to plan the optimal route of the vehicle [ 4 ] but also to optimize the health of the battery [ 5 ] and its charging process [ 6 , 7 ].…”