Application of big data and artificial intelligence in industry

9662-610 The first is smart manufacturing. For example, if the yield of a machine tool drops, then the machine tool can guess that the tool may be worn, take the initiative to change the knife, or the furnace temperature is overheated, and the temperature will be lowered two degrees. If the device can autonomously inform, autonomously change, rather than operate according to pre-set logic, this is intelligent.

What should a real digital workshop look like? There are three levels:

9662-610 The first layer is big data integration. Big data can establish a data integration system that allows decision makers to see what is happening on each production floor, what the control parameters are, and what the detection parameters are. Such a data integration system with material as the center and process flow as the axis can provide more and better decision information for the adjuster.

The second level is big data statistical analysis. Can the good batch data and the bad batch data be superimposed and compared to see the difference in control parameters? Big data can guess the cause of the problem, or at least sort it, so that the adjuster can check and adjust it according to the sort;

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9662-610 The third layer is the mechanism model. Through a large amount of data and feedback, industrial enterprises can build a relatively accurate and positive simulation model, and debug it in the digital twin and digital space, and finally test it in the factory, which is the intelligent system brought by the digital twin.

So what does the logic of the industrial Internet change for intelligent manufacturing? From a business point of view, the industrial Internet pays more attention to the boundaries of the industrial Internet, and does not pay attention to the production links within the enterprise, which can be summarized into three integration cross-border:

9662-610 First, cross-border business integration. Through the expansion of the upstream and downstream business boundaries of the industrial chain, enterprises can try to integrate the upstream of the upstream, and also serve the downstream of the downstream. We are a big factory from the perspective of industrial chain collaboration.

Second, data chain integration and cross-border, the expansion of business brings the expansion of data boundaries, today’s data is not limited to the original data of the enterprise. For example, to serve the builder, you need environmental data, operational data, meteorological data;

Compared with the development of IT technology, industrial software and the IT industry are not on the same development curve, but now through cloud computing technology can lightweight users to do such development, which can produce technology spillover opportunities in many areas. The emergence of the industrial Internet platform allows industrial enterprises to spend a lot of time to develop simulation models may precipitate into small and fine new forms of industrial software.