With the advent of the Industry 4.0 era, big data technology has become an important driving force for the transformation and upgrading of the manufacturing industry. Bearing ring forging as the core parts of mechanical equipment, its quality is directly related to the performance, life and safety of equipment. Based on big data technology, this paper analyzes the quality problems of bearing ring forgings and puts forward corresponding improvement strategies.
Big data technology can realize real-time collection, integration and analysis of various data in the production process of bearing ring forgings. By mining the data of forging process parameters, raw material properties, production equipment status and so on, the key factors affecting forging quality can be found to provide data support for quality improvement.
In the process of data analysis, traditional quality engineering techniques, such as cause-and-effect diagrams and scatter diagrams, can be combined to more intuitively show the correlation and impact of data. In addition, the predictive ability of big data technology can also achieve early warning of forging quality problems, take intervention measures in advance, and reduce quality risks.
The quality problems of bearing ring forgings are mainly manifested in dimensional accuracy, surface quality, mechanical properties and so on. To solve these problems, the following improvement strategies are proposed:
Dimensional accuracy improvement: Through big data analysis, optimize forging process parameters, such as temperature, pressure, time, etc., to ensure that the dimensional accuracy of forging parts is within the allowable range. At the same time, the introduction of advanced measuring equipment and technology to improve the detection accuracy and efficiency.
Surface quality improvement: For forging surface defects, such as cracks, folding, etc., the use of big data technology to analyze the impact of raw material properties, heat treatment process and other factors on the surface quality, to find out the key factors and improve. In addition, strengthen the quality control in the production process to ensure the standard operation of forging, heat treatment and other processes.
Mechanical properties improvement: Through big data analysis, the influence of different materials and processes on the mechanical properties of forging is studied, and the combination of materials and processes with better performance is optimized. At the same time, increase the research and development of new materials and new processes, and constantly improve the mechanical properties of forgings.
In the process of quality analysis and improvement of bearing ring forgings, some key big data and quality analysis technologies can be used, such as random forest, neural network and so on. These technologies are capable of processing large amounts of data, mining potential correlations between data, and providing more accurate results for quality analysis and improvement.
In practical application, a bearing manufacturing enterprise introduced big data technology to establish the quality analysis system of bearing ring forgings. Through real-time collection and analysis of the data in the production process, the key factors affecting the quality of forging are found, and the process optimization is carried out. After the improvement of bearing ring forgings, dimensional accuracy, surface quality and mechanical properties have been significantly improved, and enterprise product quality and market competitiveness have been enhanced.
This paper analyzes the application of big data technology in quality analysis and upgrading of bearing ring forgings, discusses the quality problems and upgrading strategies of forgings, and gives practical application cases. The results show that big data technology can improve the quality analysis efficiency of bearing ring forgings and provide strong support for quality improvement.
Looking to the future, with the continuous development and improvement of big data technology, its application in the quality analysis and improvement of bearing ring forgings will be more in-depth. Future research can further focus on the integration of big data and other advanced manufacturing technologies, such as artificial intelligence, the Internet of Things, etc., to jointly promote the continuous improvement of the quality of bearing ring forgings and contribute to the high-quality development of the manufacturing industry.
