Sustainability Indicators in Industrial Robotic Systems

Abstract

Nowadays, the application of industrial robots in manufacturing is widespread to automatize tedious and repeatable precision-sensitive processes. Modern robotic cells compete with the human workforce and specialized industrial machines in general efficiency. Additionally, robotic cells can be typically reprogrammed for different tasks, thus providing flexible applications, especially compared to more traditional methods. Advanced autonomous and intelligent capabilities are widespread in modern robotic systems, supplying quantitative factors like higher availability, fault tolerance, precision, and system flexibility. Robotic systems typically work measurably more efficiently regarding resource usage, electrical power, and waste than other industrial production line systems. New intelligent and interconnected methods (e.g., cooperative robotics, big data analysis, cyber-physical systems) contribute further to the operation efficiency. Recently, sustainability has become a significant question in robotics: modern technical society faces problems such as decreasing availability of natural resources, workforce scarcity, and environmental challenges. This work focuses on industrial robotic systems as a primary pillar for sustainability efforts in numerous production sectors, such as metallurgy, assembly lines, and construction. This paper aims to review and analyze possible sustainability indicators of the industrial applications of robotics. Based on the analysis, the paper presents a manufacturing process model with industrial robots that considers sustainability indicators. This model highlights the relationship between industrial robotization and sustainability from a quantitative and qualitative perspective. The model indicates that energy efficiency and data interconnectivity play a crucial role in the sustainability of industrial processes. The aim of the model is to help identify indicators playing a role in the sustainability of industrial robot-based manufacturing lifecycle and maintenance.