Energy consumption parameter analysis of industrial robots using design of experiment methodology

David A. Guerra-Zubiaga, Kennesaw State University
Kimberly Y. Luong, Kennesaw State University


During the last decade, industrial robot installations have increased greatly, contributing to higher energy consumption at the process level. To align with Industry 4.0 objectives to reduce energy consumption, further Industrial Internet of Things, and advance Smart Manufacturing, this paper explores energy consumption optimisation of process-level industrial robots through Design and Analysis of Experiment methodologies. The operating parameters of a Kawasaki ZZX130L, 6 DOF model industrial robot, investigated herein are speed, acceleration, payload, and temperature using a linear factorial experiment analysis. It is this paper’s goal to determine which of the explored parameters contribute most to energy consumption. Statistical analysis of data was conducted using Minitab 19, an industry standard tool, and it was found that linear speed and acceleration contributed to nearly 95% of energy consumption in any of the first three joints of the Kawasaki robot, with the other factors, payload and temperature, contributing the rest. It remains important to explore other factors contributing to EC and seek to minimise them in any way possible.