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Background

AIOT’s role in industrial automation is not only “observer”, but also “decision maker”.

With the development of AI technology. StarsPlas has found that data processing does not have to take place at the aggregation end. AI technology sinks intelligence into the edges of IoT systems — sensors, cameras, mobile devices, and other hardware. The integration of AI and IoT moves data analysis to the IoT device itself, eliminating any delays in processing. The edge devices of the Internet of Things can not only sense the environmental data. But also, through artificial intelligence technologies such as deep learning. The devices can recognize the surrounding information, evolving the Internet of Things into the intelligent Internet of Things. StarsPlas has turned its main research direction to the establishment of AIOT IoT factory. 

Industrial automation itself is one of the most important application scenarios of Internet of Things technology. Sensory equipment layout at each joint of production collects information such as equipment status and raw material information, which can significantly increase manufacturing efficiency, improve product quality, and reduce product costs and resource consumption.

Support

In industrial automation, IoT technology provides support in the following two aspects:

1. Data acquisition and storage: the sensor regularly collects and sends back the data of each link in the manufacturing process, collects and stores it to the central control room.

2. Data analysis and control: Big data analysis and other technologies are adopted to present the characteristics of data in the form of visualization, so as to provide a basis for operators to carry out production control, maintenance and transformation.

The integration of artificial intelligence technology adds a new function to the Internet of Things technology: decision-making.

Industrial automation pursues three heights: high network, high information and high automation. AIOT is not only limited to visualizing data to operators, but also to making decisions and judgments based on the characteristics of the data. This ability to make decisions endows the equipment with wisdom and brings a higher level of automation.

Development

With the support of artificial intelligence and Internet of Things technology, modern digital factories are gradually transforming into smart factories. AIOT’s role in industrial automation is not only “observer”, but also “decision maker”. The intelligent system can collect the data of each link of production immediately and accurately. By strengthening the information management and service. The production process can be clearly grasped, the production process control can be strengthened, and the production schedule can be arranged reasonably.

The application of AIOT in the industrial field is mainly concentrated in the following aspects:

1. Supply chain management

The supply chain is a data-intensive industry, but huge amounts of data are only recorded, without the ability to provide early warning and guide the future. AI makes raw material procurement and sales more predictable, and can make supply chain selection, inventory management, allocation and replenishment decisions.

2. Optimization of production process

Sensors arranged in the production line process detect equipment data in real time, monitor equipment running state and monitor material consumption state. AI analyzes the data to improve the level of intelligent monitoring, intelligent control, intelligent diagnosis, intelligent decision-making and intelligent maintenance in the production process. In the process of production, the width, thickness and temperature of SPC flooring products can be monitored in real time, so as to improve product quality and optimize the production process.

3. Industrial safety production management

The image acquisition device or wearable device can monitor the health condition and working mode of the operator, and in case of illegal operation and other situations, the alarm can be sent in time to avoid accidents. AI can also monitor the safety of the working environment in real time. For example, when sensors are embedded and equipped into the SPC floor grooving equipment, AI can sense the safety status information of the staff, equipment, machine and surrounding environment in dangerous environment, which is especially useful for the staff in high-risk environment.

4. Quality control and fault diagnosis

Quality inspection of industrial products based on machine vision and artificial intelligence technology has been widely used. Image detection algorithm is used to assist workers to locate and classify defects, effectively control quality abnormalities, reduce labor costs and labor intensity. Experienced operators can tell if the equipment is in normal condition by the sound of its running condition. AI assists in fault analysis by modeling key equipment operating parameters and locating abnormal parameters.

In the future, intelligent automation and intelligent innovation brought by AI+IoT will significantly improve production efficiency, yield rate of production line, speed up the deployment and transformation of production line, and realize customized and flexible production. Expand output, improve quality, ensure long-term and stable profit growth of enterprises.

Some application can be found in this link: http://www.extrusionpanel.com/manipulator/

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