Repair and Maintenance Methods of Mechanical Equipment
Xue, Shunyun (2024)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024051712950
https://urn.fi/URN:NBN:fi:amk-2024051712950
Tiivistelmä
The purpose of this study was to conduct an in-depth study of maintenance strategies and methods for mechani-cal equipment. In the study it was focused on the maintenance of mechanical equipment.
Mechanical engineering plays an important role in mechanical equipment maintenance strategies and methods, and the effectiveness of this framework has been verified through experimental studies.
Extensive market analysis reveals the main issues currently facing the maintenance of machinery and equipment. This study uses reliability engineering principles and Failure Mode and Effect Analysis (FMEA), combined with actual on-site conditions, to optimize the design of the maintenance process, and proposes solutions based on equipment condition monitoring and predictive maintenance methods.
In terms of the application of data analysis in mechanical equipment maintenance, historical maintenance data was deeply analyzed, and machine learning algorithms were used to establish an equipment fault prediction model, enabling early diagnosis and prevention of potential faults. At the same time, economic analysis was used to evaluate the cost-effectiveness of different maintenance strategies.
In summary, a new framework for mechanical equipment repair and maintenance that combines market analysis and data analysis is proposed in this study, and its effectiveness is verified through empirical research. It can significantly improve equipment maintenance efficiency, reduce failure rates and maintenance costs, and improve the efficiency of industrial production systems. Reliability and economic benefits have important theoretical signif-icance and application value for industrial enterprises with growing demand for efficient maintenance.
Mechanical engineering plays an important role in mechanical equipment maintenance strategies and methods, and the effectiveness of this framework has been verified through experimental studies.
Extensive market analysis reveals the main issues currently facing the maintenance of machinery and equipment. This study uses reliability engineering principles and Failure Mode and Effect Analysis (FMEA), combined with actual on-site conditions, to optimize the design of the maintenance process, and proposes solutions based on equipment condition monitoring and predictive maintenance methods.
In terms of the application of data analysis in mechanical equipment maintenance, historical maintenance data was deeply analyzed, and machine learning algorithms were used to establish an equipment fault prediction model, enabling early diagnosis and prevention of potential faults. At the same time, economic analysis was used to evaluate the cost-effectiveness of different maintenance strategies.
In summary, a new framework for mechanical equipment repair and maintenance that combines market analysis and data analysis is proposed in this study, and its effectiveness is verified through empirical research. It can significantly improve equipment maintenance efficiency, reduce failure rates and maintenance costs, and improve the efficiency of industrial production systems. Reliability and economic benefits have important theoretical signif-icance and application value for industrial enterprises with growing demand for efficient maintenance.