Challenges and solutions for introducing AI in small and medium-sized manufacturing companies

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Lack of technical know-how and human resources is an issue for small and medium-sized manufacturing companies to introduce AI. According to a Google Cloud survey, the AI ​​adoption rate in Japan's manufacturing industry is 50%, which is low compared to other developed countries. However, with the recent evolution of AI solutions, the hurdles to introduction are being lowered.

The key to success is to clarify your company's issues, prioritize them, and introduce them in stages. It is important to conduct PoC to verify the effectiveness and make continuous improvements while focusing on the quality and quantity of data.

Even small and medium-sized enterprises can improve productivity malaysia whatsapp number data and strengthen their competitiveness by introducing quality control and predictive maintenance systems using image recognition AI. By finding a way to use AI that suits your company with the support of experts, you can accelerate the digital transformation of the manufacturing industry. It is also effective to use reskilling subsidies to conduct AI training and improve AI literacy throughout the company.


4-3. Latest trends and future prospects for AI use in manufacturing
The latest trend in the use of AI in manufacturing is the fusion of edge AI and cloud AI. Combining edge AI, which performs real-time processing at the factory site, with cloud AI, which analyzes large amounts of data, enables more advanced production management. For example, efforts are underway to improve the accuracy of predictive maintenance by using cloud AI to perform detailed analysis of anomalies detected by edge AI. In

addition, the collaboration between AI and collaborative robots (cobots) is also attracting attention. By using AI to optimize work content and cobots to work in cooperation with humans, a new manufacturing environment that balances productivity and safety is being realized.