Smart factory operation and O&M
The operation and O&M of smart factories includes a centralized management and control system and a real-time production supervision system, which can realize the centralized monitoring and control of smart factories and promote the operation management mode of "unmanned on duty, few people on duty".
The centralized management and control system can be built into a standardized production data platform for smart factories, providing technical support and data guarantee for intensive management. The centralized management and control system is divided into two parts: basic functions and industrial control side network security.
The production implementation supervision system can realize the unified collection, transmission and storage of real-time data in smart factories, and provide unified data interfaces for third-party applications. It enables the company to conduct real-time monitoring, online supervision, statistical analysis and equipment early warning of the production process.
Provide rich training data for autonomous driving, enhance the model's adaptability to diverse traffic scenarios, reduce data collection costs, and enhance the model's generalization performance
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Service Process Management
This includes help desk, issue management, change management, knowledge base management, service level management, incident management, configuration management, release management, request management, and periodic plan management.
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Monitoring and Management
Covering event handling, performance management, business health, business models, alarm rules, and business topology.
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Configuration Management Database
This involves business modeling, data linkage, mapping and visualization, service impact analysis, and notification.
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Automated management
Includes automated orchestration, execution reporting, tracking audits, regular inspections, and process templates.
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AI Platform
Provides knowledge base management, scene models, APIs, model training, agents, and orchestration.
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AI infrastructure
This involves private LLMs (large language models), vector models, managed LLMs, and vector databases.
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