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WisSPC Statistical Process Control System

预览界面

A visual and intelligent analysis tool that integrates sampling, analysis, and alerting. It helps enterprises more easily and efficiently achieve real-time acquisition of quality data throughout the production process, rapid analysis, risk assessment, defect alerts, and quality traceability. And embed AI into the system,It also includes MSA analysis for measurement data, helping enterprises establish real-time quality control systems.

Key Features

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- Multiple Data Acquisition Methods

PC applications, mobile applications, shop-floor dashboards, and edge-device drivers can all be quickly connected for analysis, enabling real-time access to quality data.

 

- Flexible Control Chart & Rule Configuration

Customize sample sources, control limits, subgroup sizes, and other control chart parameters and rule settings—configured once and used permanently.

 

- High-Efficiency Data Processing

Through distributed deployment with multi-node joint analysis and single-node streaming computation, millions of data points can be processed within seconds.

 

- Advanced Graphical Statistical Analysis

Eight rule-based anomaly detection criteria and nine types of common attribute/variable control charts can be extended into rich graphical statistical analysis modules for a variety of manufacturing scenarios.

 

- All-Round Quality Monitoring

Implement quality monitoring and risk alerts through unhandled timeouts, multi-channel message notifications, and automatic escalation of alert events.

 

- Strong Scalability & Easy O&M

The platform adopts a B/S architecture with no installation required—upgrades take effect immediately by updating the server, making maintenance convenient and scalability strong.

 

-  AI+SPC intelligent prediction

Breaking through the limitations of traditional SPC systems, it possesses the ability to predict future quality trends, helping enterprises to cope with potential quality risks.


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Application Benefits


- Through quality data analysis and optimization, overall product quality is improved by 2%–8%.

- Automatic calculation and delivery of CPK and CP process capability metrics improve management efficiency by 10%–15%.

- Supports integrated enterprise management and operational decision-making, increasing decision accuracy by 20%–30%.

- Scientifically distinguishes between normal and abnormal variation during production processes.

- Significantly reduces product defect rates and lowers rework-related costs.

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