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The purpose of this paper is to analyze the force and basic rating life of angular contact ball bearings of RV reducer under the actual operating condition.

Force analysis of angular contact ball bearing under the actual operating condition, calculate the axial, radial load and internal load distribution, calculate the basic rating life of angular contact ball bearing under variable load conditions.

The external load has a great influence on the radial load of angular contact ball bearing, further affecting the basic rating life of angular contact ball bearing, which is a great influence on the overall life of RV reducer under the condition of high frequency and heavy load.

This paper provides important ideas for the design and manufacture of RV reducer in theory and experiment technology.

Aiming at the high temperature, high speed, high precision and high surface quality of the copper belt cold rolling, the purpose of this paper is to develop a new type of lubricant for cold rolled copper belt.

The component of the developed oil was determined based on the physical and chemical properties of the base oil and the tribological properties, the oxidation resistance properties, the rust resistance properties, the anti-foam properties, the demulsibility and the other properties of the additives. The orthogonal experiment method was used to determine the optimum adding amount of the additives; finally, the developed oil formulation was determined.

The physical and chemical experiment results show that the developed oil has a good performance of oil film bearing capacity and oxidation resistance. The simulation of rolling experiment found that the developed oil can significantly reduce rolling pressure and effectively reduce the friction in the process of rolling.

The experimental results show that the developed oil has excellent performance and can meet the requirement of lubrication in the process of cold rolling copper belt.

The purpose of this paper is to use the wavelet neural network and genetic algorithm to study the effects of polyalphaolefin, TMP108 and OCP0016 on the kinematic viscosity, viscosity index and pour point of lubricating oil.

Wavelet neural network is used to train the known samples, test the unknown samples and compare the obtained results with those obtained with a traditional empirical formula.

It is found that the wavelet neural network prediction value is closer to the experimental value than the traditional empirical formula calculation value.

The results show that the wavelet neural network can be used to study the physical and chemical indexes of lubricating oil.

This paper aims to use this method to explore a new approach and possible technical optimal design for lubricant formulation.

The component of the developed oil was determined based on the physical and chemical properties of the base oil and the tribological properties. The analytic hierarchy process (ANP) method and SuperDecisions software were used for hydraulic oil modeling and calculation while taking performance index, work circumstance and economy into consideration.

The hydraulic oil formulation can be optimized using the ANP method, where the technical performance, economy and working circumstances of the hydraulic oils were taken into consideration in the evaluation system. The experiment analyzed and scored and screened the hydraulic oil formula in an objective and comprehensive manner.

The experiments showed that the newly developed hydraulic oils could meet the performance requirements for new energy vehicles equipped with hybrid hydraulic engines.

The implementation of the digital economy has had a considerable influence on the manufacturing industry, and this paper aims to address the important issues of how to capture the opportunities presented by digital innovation and promote the transformation and upgrading of the manufacturing industry, as well as the improvement of quality and efficiency.

Using panel data from 30 Chinese provinces and cities between 2010 and 2021, this study establishes the panel vector autoregression (PVAR) model and uses impulse response function analysis to evaluate the influence of the digital economy on the high-quality transformation and upgrading of China's small home appliance industry across five dimensions under the digital economy.

The development of digital infrastructure has not demonstrated a noteworthy capacity for advancing the transformation and upgrading of the small home appliance industry. Furthermore, digital industrialization has exerted a minimal restraining influence on this process. Nevertheless, digital governance has consistently exhibited a substantial impact on facilitating the transformation and upgrading of the small home appliance industry. While both industrial digitization and digital innovation hold significant potential for promoting the transformation and upgrading of the small home appliance industry, their sustainability remains limited.

The organization should logically join independent innovation and open innovation, construct an industrial ecosystem for the profound convergence of the digital economy and compact household appliances, use digital-wise science and technology to empower the establishment of brand effects, strengthen the portrayal of the digital standard framework for the intelligent compact household appliance industry, advance the development of a public stage for computerized administrations in the compact household appliance industry and develop a strategy ecosystem for computerized assets in the compact household appliance industry.

This study offers systematic evidence of the relationship between the digital economy and the development of the small home appliance industry. The results of this research contribute to the literature on the impact of the digital economy on the manufacturing sector and provide a logical explanation for the transformation and upgrading of the small home appliance industry within the context of the digital economy.