Big data has become an important driving force for intelligent manufacturing. With the advancement of Industry 4.0, China's manufacturing industry urgently needs to build its own big data analysis platform to deeply connect user and factory data, drive industrial upgrading and innovation, enhance competitiveness, and occupy a higher end of the global industrial chain. Kangtopujixing big data analysis platform, the first time series database integration, greatly improve the performance of the platform, to achieve high-speed processing and accurate analysis of massive data, to provide manufacturing enterprises with efficient intelligent manufacturing big data solutions.
In the middle of 2015, The State Council issued Made in China 2025, making plans to comprehensively promote the implementation of the strategy of making China strong in manufacturing. Supporting a number of measures such as "Internet Plus" and "big data", "intelligent manufacturing" has been positioned as the main direction of manufacturing in China, among which the extensive and in-depth application of big data is an important support for the strategy of "intelligent manufacturing".
However, big data in manufacturing not only means simple digitalization of enterprises, but also takes data as the core driving force of intelligent manufacturing and uses big data to integrate industrial chain and value chain. At present, manufacturing big data basically consists of two types, one is the data generated by human trajectory, the other is the data automatically generated by machines. These two types of data make up our big Data multi-structured data sources today. Over time, there will be an increasing demand for big data analysis in manufacturing.
Without investing in big data and big data analytics to gain information from it, the efficient intelligence that intelligent manufacturing seeks will not be realized. If you use big data, predictive analytics, and the cloud to measure product performance just to understand what customers want, it means you're missing out on the biggest value of digital transformation. In the field of industrial big data, in addition to continuing to care about "human data or human-related data", we should pay more attention to the integration of "machine data or industrial data" and user behavior data.
In fact, manufacturing enterprises are not short of data. Internally, they have accumulated a large amount of internal data, including operation and maintenance, management, process and quality. In the Internet era, there are more external data, including suppliers, competitors, customer feedback and so on. But the problems are as follows: first, the effective utilization rate of big data is very low; The second is the lack of analytical ability and the need for efficient big data analysis tools.
The Polaris big data analysis platform independently developed by Comtop aims at the above problems and the current situation of manufacturing industry. On the one hand, through deep integration with time series database, high-speed time series data processing capability is obtained. The parallel processing capability of time series data in distributed environment is more than 100 times faster than that of ordinary big data analysis software. It can greatly improve the performance of data collection, storage, mining and analysis, so as to improve the utilization rate of big data. On the one hand, in view of the big data analysis needs of the manufacturing industry, three solutions including intelligent factory, equipment failure monitoring and intelligent warehousing are proposed.
Smart factory: realize intelligent interconnection by integrating transaction data of consumers and manufacturing industry; Through the production line, equipment installation sensor to obtain real-time data, realize intelligent production; Through the collection of production, equipment and external data, to guide production, sales, to realize the smart factory.
Equipment fault monitoring: It has the functions of data collection, analysis results, user benefits, analysis model summary, fault warning, equipment life cycle, identification of concurrent failures, equipment cluster and so on.
Intelligent storage: It has the functions of data collection, analysis method, user income, inventory duration analysis, short-term inventory analysis, long-term inventory analysis, input and input storage analysis, intelligent recommendation of material requester and so on.
In the future, it is not big data itself that will drive intelligent manufacturing, but the analytical technology of big data, which will be the source of the core driving force of innovation. Use Polaris big data analysis platform, use big data to achieve accurate decision-making, integration of industrial chain and value chain, whoever starts first will win the future! Baidu search "Polaris Big data analysis platform", enter the official website for more details.
About Polestar Big data analysis platform
Polaris Big Data analysis platform is an enterprise-level big data integration solution designed for massive data of large enterprises and professional institutions. It has the characteristics of high reliability, high security, easy to use, high performance, low cost, to help enterprise customers quickly build a big data platform to meet the needs of enterprises for mass data storage and analysis. As a distributed data processing system, Polaris big data analysis platform can provide powerful mass data processing functions, such as: data acquisition, data storage, data processing, data mining, data analysis, data visualization, data professional algorithm, etc., widely used in finance, electric power, manufacturing, petrochemical, gas, transportation and other industries. For more details, please search "Polaris Big Data analysis platform" on Baidu.
