Industries are evolving with the adoption of connected components, smart sensors, and robotic automation, which is greatly impacting the manufacturing process. This era emphasizes high automation and extensive data exchange, requiring cognitive and autonomous solutions for managing production.
AI-driven models enable customized manufacturing, predictions, and real-time optimization, enhancing cost efficiency, reducing downtime, and improving speed and accuracy.
With 15% of businesses using AI and 31% planning to adopt it, demand for Production automation with AI in manufacturing continues to grow. DAC Digital is one of the companies based in Europe that can support different industries with the help of their team.
What is AI in Manufacturing?
When we refer to AI in manufacturing, then we mean the application of AI technology in the following:
- Supply chain management
- Quality control
- Predictive maintenance
- Production schedule optimization.
- Increasing productivity
- Cost reduction
- Improvement of product quality.
What are the advantages of AI in manufacturing?
The following are the advantages of AI in manufacturing plants:
- Increased efficiency: AI can optimize production processes, and also reduce downtime and waste.
- Cost savings: Predictive maintenance and optimized operations can help in reducing costs significantly.
- Improved quality: Higher-quality items can be produced because AI improves quality control.
- Enhanced flexibility: AI has the potential to greatly increase manufacturing process flexibility and enable rapid adaptation to shifts in demand or production requirements.
Some examples of AI-based industries
1) Automotive manufacturing industry
In automotive manufacturing, AI revolutionizes precision tasks such as welding SUV frames and improves inspection with advanced image recognition. It enhances quality control, efficiency, and cost savings by automating tasks and optimizing processes.
2) Vehicle manufacturing industry
In next-generation vehicle production, AI, IoT, and robotics drive eco-friendly and efficient processes. AI enhances manufacturing by optimizing performance, automating paperwork, and improving maintenance, defect detection, and inspection in automotive production.
3) Food and beverage industry
In the food and beverage industry, machine learning is transforming demand forecasting. AI analyses consumer data to improve accuracy, enhancing coordination across marketing, sales, and supply chain, thus reducing lost sales and boosting efficiency.
4) Aerospace manufacturing industry
In aerospace manufacturing, AI is crucial for predictive maintenance and quality control. It monitors machine sensor data to prevent resource wastage, enhances defect detection, reduces lead times, minimizes shortages, and optimizes quality control.
5) Semiconductor manufacturing industry
In semiconductor manufacturing, AI integration has been transformative, using thousands of machine learning models to boost productivity and yields. These algorithms analyse data to optimize processes, enhance quality control, and improve decision-making.
6) Tire manufacturing industry
In tire manufacturing and beyond, AI-driven systems are setting new standards in quality and consistency. They significantly enhance manufacturing uniformity, showcasing AI’s role in improving product quality and transforming operations.
7) Electronics manufacturing industry
In the electronics industry, identifying defects is one of the most time-consuming processes, and it can be quickly performed with AI technology.
This will lead to:
- Increase in product yield
- Enhancement of operational efficiency
- Improving accuracy
- More flexibility
- Improved performance.
Conclusion
Artificial Intelligence (AI) holds the potential to enhance the effectiveness and efficiency of various manufacturing processes, resulting in more production, lower costs, and improved quality. As a result, AI will soon be used by all industries.
