Key Performance Indicators Integrating Collaborative and Mobile Robots in the Factory Networks

Abstract

Measuring performances of collaborative robots in Industry 4.0 applications is an open research area since the emergence of collaborative and mobile robots as a support for semi-automatic manufacturing processes. A compelling management problem is the definition of convenient performance measures on which to assess the new generation of robots, to improve process performances both at the robotic cell design stage and at the production stage. A consequent problem is to gather the required data to measure performances. Data must be obtained automatically and in real time. Different levels of communication protocols have to be harmonized in order to transfer data from robots and other factory machines to the cloud on the internet and eventually to the production control system. A case study allows to demonstrate the operation of data acquisition system for collaborative and mobile robots and the real-time monitoring dashboard. The outcome of the study is the gathering of data at field level, the evaluation of robot performances at machine level in order to execute the real time production control at factory level.

Proposal of a Monitoring System for Collaborative Robots to Predict Outages and to Assess Reliability Factors Exploiting Machine Learning

“…Moreover, a cobot system can be integrated with additional sensors to detect gas or ambient pollution and then inform the human operator about the hazard. The present paper focuses on the integration of data acquisition and machine learning in a cobot monitoring system; networking communication and the application layer with management indicators have already been discussed in [18,31,32].…”

“…The importance of such parameters and variables as the load, end-effector force/torque, payload, robot and temperature of the robot and joints and robot speed were identified and classified in these researches according to the tasks of the cobots in the HRC assembly. The measurment of the performance, monitoring and prediction of the above mentioned parameters are employed in the computation of the key performance indicators (KPI)s of cobots [16][17][18].…”

“…Node-red dashboard allows the data to be presented in various forms such as charts, text fields and gauges, commands are also triggered from the GUI using sliders, switches, text fields and buttons. Additional details about communication protocols and KPI computations of the cobot on the dashboard are given in the aforementioned papers [18,31].…”