| 摘要(英) |
Currently, the electronics manufacturing industry traditionally relied on demographic dividend. The labor cost expenditures are enormous due to the employment of over one hundred thousand workers. Because labor cost was lower relatively, there was less urgency for the electronics manufacturing in-dustry to establish automated production and smart factories. Equipment up-date, production capacity increase and business expansion were the operational focus of electronics manufacturing industry. There have been instances where the cost of investing in an automated production line is higher than the cost of using labor. The barrier to Industry 4.0 is likely to be the fact that the accumu-lated cost of labor is lower than the cost of constructing an automated produc-tion line.
The demographic dividend has disappeared in recent years due to infla-tion. The electronics manufacturing industry that set up factories in China in the past faced challenges in terms of the supply of manpower. Over the past few years, the way that relied on demographic dividend is going to disappear because of fertility decline, labor cost increases, and the Covid-19 pandemic. The factory is forced to solve the labor cost problem. Many companies are be-ginning to evaluate and implement smart manufacturing to enhance their com-petitiveness, improve quality, and reduce labor costs. The electronics manufac-turing industry is bound to move towards Industry 4.0 in the future. Through the process of digital transformation in the case company, the research aims to delve into its four major processes: Surface Mount Technology, WAVE Solder-ing, PCBA Testing and System Assembly. Improving processes through the analysis of process automation, logistics automation, digitization, and the intel-ligent implementation of projects in each process. The total manpower for the production line has been reduced from 67 to 52, a decrease of 15 workers, re-sulting in a 30.2% increase in hourly output per person. To investigate the actu-al benefits of implementing smart manufacturing for industries, this study will examine various data and outcomes before and after implementation and pro-vide practical cases as examples. |
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