On the Digital Transformation of the Automobile Manufacturing Industry in the Chengdu-Chongqing Economic Circle:Mechanism of Action and Feasible Paths

With a long industrial chain and a powerful ability to drive other industries,the automobile manufacturing industry has a prominent strategic position in the national economy.In recent years,many countries have put on their agenda the digitalization of the automobile manufacturing industry,leading to an connected,autonomous,shared,and electric(also known as CASE)①development trend in the industry.As one of the six major automobile industry clusters in China,the Chengdu-Chongqing economic circle has achieved initial results in the digital transformation of the automobile manufacturing industry.However,the region is still faced with some constraints,such as insufficient digital infrastructure,relatively slow development of new automobile products,insufficient innovation ability of the automobile industry,and complex digital transformation of small and medium-sized automobile enterprises(automobile SMEs).This paper intends to construct a framework for the mechanism of action of the digital transformation in the automobile manufacturing industry,analyze the effects of the digital transformation of the automobile manufacturing industry in the Chengdu-Chongqing economic circle,and propose feasible paths for the digital transformation of the automobile manufacturing industry in the region by drawing on domestic and international experience in this regard.The specific paths include:(a)Smoothing the“dual-core”data chain to facilitate the digital transformation of the automobile manufacturing industry;(b)Developing the new energy vehicle(NEV)industry to upgrade the quality of automobile products;(c)Achieving corner overtaking in the digital transformation of the automobile manufacturing industry with digital technology;(d)Jointly building the automobile industrial park to promote the digital transformation of the industry;(e)Addressing problems facing automobile SMEs in digital transformation via targeted policy tools.

Practical Analysis of Mechanical Automation Technology in Automobile Manufacturing

In today’s rapidly developing modern society,automobiles,as an important part of transportation and industrial fields,play a pivotal role.With the improvement of people’s living standards and the increase in traffic demand,the automobile manufacturing industry has been continuously developing and growing globally.However,to cope with increasingly fierce market competition and ever-changing consumer demands,the automobile manufacturing industry is also facing the challenges of improving production efficiency,reducing costs,and improving product quality.In this context,automation technology has gradually become a major trend in the automobile manufacturing industry.As an important support of modern industry,automation technology has shown great application potential in many fields.From industrial production to daily life,automation technology can be seen everywhere.In the field of manufacturing,especially in automobile manufacturing,the application of automation technology is getting more and more attention.Automated production lines,intelligent robots,and automated warehousing systems have all changed the face of automobile manufacturing to varying degrees,bringing companies higher efficiency,more stable quality,and greater competitive advantages.The application trend of this automation technology in various fields not only meets the needs of modern industry for efficient,precise,and sustainable development but also provides new ideas and paths for the future development of the automobile manufacturing industry.

Application of the BASNEF Model in Safety Training in Automobile Manufacturing Plants

After controls,including engineering and management,thefinal way to control noise is to use hearing protection devices.Duetothelack ofastandardized questionnaireregarding investigatingworkers’use of hearing protection devices on the basis of the BASNEF behavioral model,the present study was conducted to investigate the effect of health education based on the BASNEF model on the use of hearing protection devices in workers of an auto-mobile manufacturing plant in Iran.This quasi-experimental and prospective intervention study was performed on 80 workers at an automobile manufacturing plant who are exposed to noise levels above 85 decibels and donot use hearing protection devices.In this study,40 people working in a cast iron foundry were selected as the inter-vention group,and 40 working in aluminum casting were chosen as the control group.Questionnaires were ana-lyzed at the beginning of the intervention and three months after the intervention in the intervention and control groups.There was no significant difference between the intervention and control groups before the intervention.There was a significant difference between the intervention and control groups after the intervention in the area of knowledge.A significant correlation was observed between the intervention and control groups after the inter-vention program in all areas of the BASNEF educational model except behavioral intention.In this study,the effect of educational intervention on the use of hearing protection devices was investigated,and with the educa-tional intervention,it was tried to get help from influential people and enabling factors in education based on the BASNEF model.The results showed that the educational intervention based on the BASNEF model can improve the knowledge of individuals in both the intervention and control groups.

A new grey predictionmodel for forecasting the automobiles ownership in China

The average relative simulation and prediction percentage errors of the new model are only 0.092%and 3.023%,respectively.The simulation and prediction errors obtained from the classical GM(1,1)and the DGM(1,1)models are,respectively,2.064%and 6.980%in the first case,and 1.942%and 7.360%in the second.The findings show that the GM(1,1,4)model has the best performance,which confirms the effectiveness of the structure improvement.The new model can enhance the smoothness of the background value and weaken the effects of extreme values in the raw sequence in the model’s performance.Therefore,the simulation and prediction performances of the GM(1,1,4)model are better than those of the traditional grey prediction models.The prediction show that the ownership for automobiles in China will grow rapidly in future.Findings could help the government in formulating adjustments to the industrial structures,and facilitate making rational yield plans for automobile firms.