China's Intelligent Mechanical Cloud Platform Recently Launched Industrial Data Analysis and Mining Services

For many traditional manufacturing industry, in the general trend of intelligent upgrading of the industry, the transformation of traditional manufacturing industry is facing great challenges. Data analysis and excavation in the industrial field show its superiority more and more. The higher the level of data analysis, the more efficient the business will be, and ultimately the productivity gains will be translated into productivity. The introduction of third-party cloud data system monitoring and management has become one of the most commonways for most manufacturers to explore the road. Many leading enterprises have taken the lead in integrating artificial intelligence and data analysis and mining technology, actively promoting the deployment and use of intelligent industrial systems, and achieved effective results, to achieve the goal of reducing cost efficiency.

And each enterprise has its own needs of the special, according to the current industry is facing the actual pain point, China's intelligent machinery cloud platform for everyone to launch seven industrial areas of big data analysis and mining solutions, to help your enterprise intelligent upgrade, to achieve cost-effective.

Scenario One.

DC_TOOLS tighten tool real-time decision-making system.

Source: Tightening Tool (Grab Tight Data from oracle Database)

Acquisition cycle: 2 seconds.

Data format: json.

Project background: traditional industrial scenarios, the determination of tightening results is based only on thresholds, can not track the entire tightening process, resulting in a lot of tightening process there are hidden dangers.

System value and results: The intelligent system has been widely praised by the business segment with its high accuracy judgment, user-friendly user interface, intuitive analysis report and real real-time multi-channel alert alert mechanism. After three months on the line, the overall success rate of tightening work increased by 1.5 percentage points.