Industrial Computing
What is Industrial Computing?
Core concepts of industrial computing
Automation and control:
Use computer control systems to automate production processes to improve efficiency and consistency.
Including programmable logic controllers (PLCs), distributed control systems (DCSs) and industrial robots.
Data collection and analysis:
Collect production and operation data through sensors and network devices.
Use big data analysis and machine learning technologies to identify trends, predict problems and optimize processes.
Interconnection:
Use Internet of Things (IoT) technology to connect devices and systems to achieve real-time sharing and interaction of information.
Support remote monitoring and management to improve collaboration efficiency.
Intelligent decision-making:
Apply artificial intelligence (AI) technology for predictive maintenance, quality control and supply chain optimization.
Help companies make smarter business decisions through data-driven insights.
Key technologies of industrial computing
Cloud computing: provides scalable computing resources and storage capabilities, supports large-scale data processing and real-time analysis.
Internet of Things (IoT): enables interconnection between devices and systems, and provides support for data collection and monitoring.
Artificial intelligence (AI) and machine learning: used for data analysis, pattern recognition, predictive modeling, etc. to optimize industrial processes.
Edge computing: performs computing close to the data source to reduce latency and improve real-time processing capabilities.
Big data analysis: analyzes large amounts of production and operational data to extract valuable insights.
