Achieving High-Precision Automated Control of Secondary Resistor-Controlled Overhead Cranes! Successfully Developed Retrofit-Type Automation Solution Without Replacing with Inverter Control!

JFE Steel Corporation (hereinafter 'JFE Steel') and Proxima Technology Co., Ltd. (hereinafter 'Proxima') have jointly developed the foundational technology for a new automation solution enabling high-precision autonomous operation of secondary resistor-controlled overhead cranes, aiming to expand crane automation. This technology is scheduled to be implemented on overhead cranes at JFE Steel's East Japan Works (Chiba District), with plans for rollout across all sites thereafter. By combining Proxima's control AI 'Smart MPC®'—capable of learning operational methods from minimal data—with JFE Steel's extensive expertise and know-how in crane automation, primarily focused on inverter-controlled cranes, the companies have achieved high-precision autonomous operation of secondary resistor-controlled overhead cranes, previously considered difficult to automate.

・High-precision automated control of secondary resistor-controlled overhead crane (actual operation)

・Autonomous operation of secondary resistor crane using Smart MPC® (simulation)

・Autonomous operation of secondary resistor crane using Smart MPC® (system screen)

[Background of Joint Development of Automation Solution]

Numerous secondary resistor-controlled overhead cranes, using wound-rotor induction motors, operate within steelworks and logistics hubs. To safely transport suspended loads via cranes, sway control and precise positioning are essential. However, sway control and positioning for secondary resistor-controlled systems face the following challenges:

・Control inputs are discrete due to notch-based operation*3.
・Speed varies significantly even at the same notch setting, depending on load weight and rail conditions.
・Operating speed at very low speeds is unstable.

Therefore, crane automation typically required retrofitting to inverter control. However, due to high costs, long project durations, and current labor shortages at operational sites, urgent automation has been a pressing challenge.

[Features of the Jointly Developed Automation Solution]

The newly developed crane automation solution uses sensor data—such as distance meters and IMU*4—installed on the crane, enabling 'Smart MPC®' to autonomously learn drive characteristics. The main features are as follows:

・Achieves high-precision sway control and positioning even in environments where load weight and other conditions vary.
・Capable of learning from approximately half a day of operational data; when combined with online learning, achieves high control performance in a short period.
・Enables full crane autonomous operation, including lateral travel, by integrating with JFE Steel's existing automation technologies.

This technology enables short-term, low-cost automation of secondary resistor-controlled overhead cranes—previously difficult to automate—without requiring replacement with inverter control.

*1 Secondary Resistor Control: A common control method for adjusting the speed and torque of wound-rotor induction motors. It involves connecting resistors to the motor's secondary circuit and adjusting the resistance value to control speed.
*2 Inverter Control: A technology that freely adjusts voltage and frequency to optimally control the rotational speed and torque of electric motors.
*3 Notch Operation: An operating method where the secondary resistance value is switched stepwise to achieve a desired speed or torque.
*4 IMU: Inertial Measurement Unit. A device equipped with 3-axis gyroscopes and 3-axis accelerometers to detect and measure an object's rotational motion and linear acceleration (3D inertial motion).

[Overview of Proxima Technology]

Company Name: Proxima Technology Co., Ltd.
Address: 7F, Kanda-Eight Building, 4-6-7 Sotokanda, Chiyoda-ku, Tokyo 101-0021, Japan
Representative: Takuya Fukatsu, President & CEO
Business: Data analytics-related services
Capital: 50 million yen
Established: November 1, 2018
URL: https://proxima-ai-tech.com