
Equipment design
Mechanical and control design based on battery specifications and process conditions, with operation and maintenance considered from the start.
Experience from the production floor
HITEC has specialized in lead-acid battery manufacturing equipment since 1990. Our work covers mechanical design, electrical controls and line integration, followed by installation, operator training and spare parts support.
View equipment
Mechanical and control design based on battery specifications and process conditions, with operation and maintenance considered from the start.

Plan equipment layout, transfer between stations and control connections, with production data integration where required.

Installation and operator training help bring equipment into use. Spare parts and technical support continue during operation.
Our history
Began work in lead-acid battery automation, developing production equipment with Yuasa Taiwan.
Developed the COS NP4-6 battery manufacturing system.
Developed the COS motorcycle battery manufacturing system and expanded overseas.
The second-generation team took over, strengthening overseas markets and customer service.
The third-generation team took over, continuing equipment development and intelligent integration.
Global track record
150+
Battery assembly lines worldwide
Our equipment is widely used by leading lead-acid battery manufacturers around the world, including companies with top-tier production volumes in motorcycle and lead-acid batteries. We have earned strong customer trust.

CIM / AI
Connect equipment and control signals. Bring production quantities, process parameters and anomaly records together for status monitoring and quality tracking.
The integration scope is planned around line conditions.
Connect workstations and equipment. Integrate control signals.
Collect quantities and process parameters. Bring anomaly records together.
Monitor equipment status. Support quality tracking and decisions.
Within the CIM (Computer-Integrated Manufacturing) / AI framework Hitec provides, we focus on equipment integration, data collection, status management, and quality tracking, combined with AI applications, to help customers build a clearer, more stable, and more manageable production process. The system can be customized to different line requirements, while retaining the flexibility to expand into AI-driven intelligent scheduling, data analytics, and quality control systems in the future.
Based on the customer's line requirements, we can design data-collection mechanisms for equipment operation data, production quantities, anomaly records, and process parameters — forming the basis for subsequent reporting analysis and management decisions.
Reduces information gaps caused by manual recording, makes it easier for managers to grasp line status, and leaves room to expand into visual reporting, trend analysis, and smart-manufacturing applications in the future.
We can integrate equipment status signals according to line needs — such as running, standby, fault, stoppage, and capacity information — helping customers build a foundational framework for equipment status management.
Lets on-site personnel grasp equipment conditions faster, shortens anomaly reporting and troubleshooting time, and supports later planning of maintenance records, utilization statistics, and equipment efficiency improvements.
Based on product models, process flows, capacity conditions, and on-site needs, we can help customers plan production scheduling and line-dispatching logic, improving the management efficiency of the manufacturing process.
Helps customers reduce scheduling confusion, waiting time, and manual workload, giving line arrangements a stronger basis — and retaining the flexibility to adopt automatic scheduling or AI-assisted decision-making in the future.
We can integrate inspection data, process parameters, and quality records according to customer needs to build a product production history, supporting subsequent quality tracking, anomaly analysis, and improvement management.
Makes the source of quality issues easier to trace, reduces the time spent manually searching for data, and serves as the data foundation for future adoption of SPC (Statistical Process Control) or advanced quality analysis.
Start with your process requirements