By collaborating with intelligent machines, the mental labor of human experts in the manufacturing process can be expanded, extended, and partially replaced. This updates the concept of manufacturing automation, extending it to flexibility, intelligence, and high integration.
Intelligent manufacturing systems are based on the production environment and ultimately act on the production environment. Since the logistics status, equipment status, quality status, energy consumption status, and environmental status are aspects that are closely controlled and urgently need improvement in manufacturing production management, the basic structure of the system revolves around the main management status of the production environment, forming a closed-loop control process of the intelligent manufacturing system, which includes 5 layers.
The structural model of intelligent manufacturing systems can be divided into five layers:
1. Perception Layer: Collects physical signals and environmental data through intelligent devices such as sensors and data acquisition devices to achieve perception and data acquisition of the production site and equipment.
2. Communication Layer: The collected data is transmitted through communication components, enabling real-time data sharing and transmission, and facilitating inter-device collaboration and IoT connectivity.
3. Data Layer: Extracts and processes information from the data received from the communication layer, and provides the processed data to the upper-layer system for further analysis and decision-making.
4. Control Layer: The control layer uses the data and information provided by the data layer to monitor, control, and schedule the production process and equipment in real time, thereby adjusting and optimizing the manufacturing process.
5. Application Layer: The application layer is the upper management layer of the intelligent manufacturing system. It makes decisions and manages various aspects such as production planning, manufacturing management, quality control, and maintenance management through data from the data layer and control layer.
The structure of intelligent manufacturing systems is tightly interconnected, achieving intelligent manufacturing across the entire process through collaboration among multiple stages, including data acquisition, transmission, processing, control, and management. Furthermore, with the development and application of technologies such as artificial intelligence, big data, and cloud computing, intelligent manufacturing systems will gradually realize more collaborative, flexible, and intelligent production models.
