MakinaRocks Expands AI Maintenance for Hyundai Motor Robots

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MakinaRocks Expands AI Maintenance for Hyundai Motor Robots
Source: MakinaRocks

MakinaRocks Expands AI Maintenance for Hyundai Motor Robots

MakinaRocks deploys AI predictive maintenance (RPMS) to 1,400 Hyundai Motor robots globally, forecasting equipment failures with 90% accuracy.

Philip Lee profile image
by Philip Lee

Seoul, South Korea  - MakinaRocks announced Thursday that it is deploying its artificial intelligence-based predictive maintenance system across approximately 1,400 industrial robots at Hyundai Motor Company’s global manufacturing facilities. 

The rollout, expected to be completed by the end of 2026, marks a significant step in Hyundai’s transition to a Software-Defined Factory model.

The solution, known as the Robot Prognostics Maintenance System (RPMS), utilizes robot motion data and deep learning algorithms to forecast equipment failures up to five days in advance. 

According to MakinaRocks, the system achieves an accuracy rate of over 90 percent. 

The company said RPMS is intended to reduce unplanned operational downtime and improve maintenance efficiency. 

Its functions include drive-unit condition diagnostics, setup anomaly detection, and state-change notifications.

The initial phase of the rollout began at Hyundai’s Asan plant and is being expanded to additional domestic and international sites, including facilities in Ulsan, Jeonju, and India. 

The technology is also being introduced to dedicated electric vehicle production lines, such as the Ulsan EV plant and the Hwaseong Kia EV plant.

The deployment extends an eight-year strategic partnership between MakinaRocks and Hyundai Motor. 

Hyundai first invested in MakinaRocks in 2018 through its open innovation platform, ZER01NE.

A Hyundai Motor representative said the company aims to standardize AI-based predictive maintenance technology across its global manufacturing network in order to improve flexibility and product quality. 

MakinaRocks chief executive Sung-ho Yoon stated that the collaboration is focused on implementing systems to address the complexities of modern manufacturing environments.

Philip Lee profile image
by Philip Lee

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