The manufacturing industry is the foundation of the country, the foundation of a strong country, and the "ballast stone" of a large economy, and it is of great significance to enhance the quality advantage of the manufacturing industry to promote the mid-to-high-end leap of the industrial chain, build a new development pattern, and accelerate the high-quality development of the economy.
The deep integration of the new generation of information technology and quality management represented by big data produces quality big data, continuously improves the digital, networked and intelligent level of quality management activities of all factors, whole value chains and whole industrial chains in the manufacturing industry, and accelerates the digital transformation of the manufacturing industry.
In order to give full play to the basic supporting role of a new generation of information technology such as big data on quality improvement and help the high-quality development of the manufacturing industry, the Ministry of Industry and Information Technology issued the "Quality Big Data", hereinafter referred to as "Quality Big Data", "Focusing on the boundary connotation, architecture system, resource construction, implementation path, development trend and practical cases of quality big data".
Figure: Quality data resource system cataloging.
When identifying quality data resources and building a quality data resource system catalog, from the perspective of the whole life cycle of the product, the enterprise quality big data resource system is divided into five dimensions: product design quality data, chain quality data, product production quality data, product after-sales operation and maintenance quality data, and product scrap quality data, and at the same time, according to the characteristics and attributes of the five-dimensional data of design, chain, production, after-sales operation and maintenance, and scrapped quality, it is divided into fifteen categories and forty-two four-level categories. Form a reference architecture for cataloging the enterprise quality big data resource system.
As a pilot unit of national high-tech product standardization of product quality big data, Beijing SunwayWorld Technology Co., Ltd. is committed to the implementation of national quality infrastructure (NQI) informatization services, and has participated in the drafting of a series of national standards related to data management.
After years of technology precipitation, SunwayWorld's TQM (Total Quality Management) quality management platform is based on the quality management needs of the whole life cycle of enterprises, combined with SunwayWorld's information construction experience in testing, R&D, quality control and quality assurance, and has become an important part of the quality big data system through the integration of the three management system functions of R&D management system RDMS, laboratory information management system LIMS and quality management system QMS. It brings mature integrated solutions for the digital improvement of quality in manufacturing enterprises.
A basic overview of SunwayWorld's TQM
Figure: The development stage of quality management thought.
SunwayWorld TQM follows the current mainstream management ideas, based on cloud computing and big data technology, brings together the business management functions and quality management functions of RDMS, LIMS and QMS to build a complete set of quality data management platform, which fills the data resource gaps at the R&D, production quality control and quality assurance ends for the overall planning of enterprise quality big data, and improves the compliance and efficiency of R&D, testing and QA work through business functions, so as to ensure the quality and circulation efficiency of data input from the source of quality big data.
SunwayWorld TQM has strong data collection, integration, analysis and application capabilities, which can help enterprises build a comprehensive quality management system. The platform integrates the three major systems of RDMS, QMS and LIMS, realizes the seamless connection and sharing of data within the enterprise, and plays an important role in the quality management process.
Figure: SunwayWorld SW-TQM functional matrix.
Among them, the R&D management system RDMS manages the whole life cycle of R&D projects from the perspectives of R&D progress, R&D budget and R&D quality, and helps the R&D process and improves the quality data management capabilities in the R&D stage through capabilities such as ELN, formula design, process design, R&D data statistics and correlation analysis.
In accordance with the management requirements of the laboratory quality system of various industries, LIMS has built LIMS solutions in different industries, comprehensively improved the management from the business process of the laboratory to the quality management requirements, combined with IoT technology to realize instrument data collection, and established a data integrity management mechanism for the whole process of the laboratory.
According to the management scope of the QA department, QMS designs the whole business domain management process such as document management, training management, supplier management, release management, nonconforming product management, deviation management, corrective and preventive measures, quality risk, quality complaints, etc., and can summarize the data of R&D, production quality control and other processes to establish a complete quality statistical view, and provide complete information tools for enterprise quality management.
SunwayWorld's TQM products integrate three systems: RDMS, QMS and LIMS to form a unified data management and analysis platform, providing a complete set of information tools for the quality improvement of production laboratories.
The application of SunwayWorld TQM in the quality big data system
SunwayWorld's TQM platform guides R&D, testing, quality control, and QA personnel to carry out daily work through various business function modules, and collects quality data at the same time, which can digitally collect and manage all kinds of quality data generated by enterprises. It enables the acquisition of standardized quality data from different business processes to ensure data accuracy and consistency.
Based on the quality data collected in various business processes, SunwayWorld's TQM platform can help enterprises plan and model quality big data through mature data analysis and modeling functions. Through the analysis and mining of big data, the root cause of quality problems can be identified, potential improvement opportunities can be discovered, and future quality trends can be identified.
In addition, SunwayWorld TQM also provides a variety of analysis tools and algorithms, such as SPC, discriminant rules, trend warning, statistical analysis, and can mine the correlation between quality data through artificial intelligence to support more in-depth quality analysis.
Thanks to SunwayWorld's self-developed business intelligence analysis platform, all kinds of quality data can be built into visual dashboards for real-time presentation, and several statistical large-screen cockpits can be built according to needs to monitor key management data in real time.
To sum up, SunwayWorld TQM has complete system functions, which can fully cover the daily business management of R&D laboratory, testing laboratory, quality control laboratory and quality assurance department. TQM enables companies to effectively collect critical quality data from the R&D, QC, testing and quality assurance processes, which are essential and indispensable components for quality control of production enterprises.
In the process of quality big data combing, manufacturing enterprises should not only pay attention to the quality data collection of the production process, but also not ignore the data collection of R&D, quality control and QA process, and fully consider the whole process of quality data management of R&D, production, quality control and after-sales + quality assurance in the overall digital architecture design, in order to truly achieve the goal of quality big data management, and establish an analysis model in line with the current situation of the enterprise through further data application and mining on the basis of this data. And ultimately enhance the quality management ability and market competitiveness of the enterprise.