Core Technologies

System Architecture
Perceptive Intelligence
Decision Intelligence
Collaborative Intelligence
Customer Value

System Architecture
Perceptive Intelligence
Decision Intelligence
Collaborative Intelligence
Customer Value

Perception, decision-making and collaboration drive the continuous optimization of the manufacturing system

Industrial intelligence is not a single algorithmic capability, but a complete closed-loop process that encompasses the entire journey from identifying the on-site conditions, conducting business modeling analysis, to generating the optimal strategies and providing feedback on their execution. Through the continuous cycle of "perception - decision - collaboration - optimization", the system becomes more stable as it operates and more intelligent as it is used.

Establish a genuine and reliable on-site perception capability

Perception intelligence focuses on production site state recognition and industrial data collection, achieving transparency in the production process through machine vision, equipment monitoring, and process parameter perception, providing a real, timely, and reliable data foundation for decision analysis and collaborative execution

Core functionality

visual inspection

Defect Identification: Millisecond-level detection of surface defects on products
Dimension Measurement: Multi-dimensional automatic measurement, supporting SPC quality traceability
Application scenarios: Power equipment

State Recognition

Real-time monitoring of equipment operation status (running, stopped, alarm)
Automatic recognition of production rhythm
Dynamic update of inventory

Industrial data acquisition

Supports 100+ protocols such as OPC-UA and Modbus
Supports multi-source data collection for equipment, process, quality, and energy consumption
Data is encrypted and securely stored

abnormal warning

Early warning for equipment failures
Automatic alarm for abnormal product quality
Real-time prompt for deviations in process parameters

Process visualization

Real-time display on production board
Track the full chain flow of materials, orders and products
Supports multi-dimensional drilling analysis

Realize global oriented intelligent optimization decision-making

Decision intelligence revolves around key business scenarios such as production planning, process control, and logistics scheduling. Through data modeling and algorithm optimization, it continuously generates optimal operational strategies to improve resource utilization and overall operational efficiency

Core functionality

Optimization of production scheduling

Constraints: Order delivery date, production capacity, and resource constraints
Optimization objectives: Maximize the on-time fulfillment rate, minimize inventory, and reduce costs Algorithm: Mixed integer programming + heuris

Optimization of process parameters

Based on the production process model and real-time quality data, key parameters such as fuel and energy are dynamically adjusted
The AI model continuously optimizes and learns the optimal process curve
Typical effect: Overall energy consumption is reduced by 3% or more, and product quality fluctuations are decreased.

Optimization of Logistics path

Based on real-time inventory location, order priority, and equipment status
optimize the running paths of AGVs and four-way vehicles, reducing waiting time
Support dynamic scheduling strategies: shortest path / priority scheduling / traffic balancing
Typical effect: Logistics cycle is shortened by 25-30%.

Optimization of Storage location

Improve storage space utilization and material flow efficiency

Energy Consumption Optimization

Continuously reduce unit energy consumption and operating costs around key technological processes

Establish a cross system full process collaboration mechanism

Collaborative intelligence focuses on the full process rhythm collaboration in complex manufacturing scenarios, ensuring efficient implementation of optimal strategies through unified linkage between equipment, systems, processes, and organizations, and achieving overall operational efficiency improvement

Core functionality

Cross device collaboration

Realize the establishment of a database AGV、 Unified scheduling and operation of conveyor lines, robots, and other equipment

Cross process collaboration

Ensure stable connection between upper and lower processes, reduce waiting and backlog during production

Cross system collaboration

Connect the data loop of logistics system, production system and process system

Cross role collaboration

Realize efficient collaboration among multiple roles such as planning, production, warehousing, and quality

End-to-end collaboration

Drive unified optimization and configuration of resources throughout the entire chain around delivery goals

Continuous improvement in technical capabilities, service, and business results

The core value of industrial intelligence lies not in system construction itself, but in continuously improving enterprise delivery capabilities, operational stability, and business efficiency, so that technological capabilities can truly be transformed into long-term competitive advantages.

Improved delivery capability

Through collaborative optimization throughout the entire process, we aim to improve delivery efficiency and production stability

Artificial dependence reduction

Reduce experience driven and human intervention, and improve the standardization level of the system

Comprehensive cost optimization

Continuously optimize inventory, production scheduling, routing, and energy consumption to reduce overall operating costs

Stable improvement in quality

Real time monitoring of key quality nodes to reduce fluctuations and rework risks

Continuous evolution of the system

Based on real-time data and model iteration, achieve long-term self optimization capability

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Technologies

Perception, decision-making and collaboration drive the continuous optimization of the manufacturing system

Establish a genuine and reliable on-site perception capability

Core functionality

visual inspection

State Recognition

Industrial data acquisition

abnormal warning

Process visualization

Realize global oriented intelligent optimization decision-making

Core functionality

Optimization of production scheduling

Optimization of process parameters

Optimization of Logistics path

Optimization of Storage location

Energy Consumption Optimization

Establish a cross system full process collaboration mechanism

Core functionality

Cross device collaboration

Cross process collaboration

Cross system collaboration

Cross role collaboration

End-to-end collaboration

Continuous improvement in technical capabilities, service, and business results

Improved delivery capability

Artificial dependence reduction

Comprehensive cost optimization

Stable improvement in quality

Continuous evolution of the system

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