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According to a report from Markets and Markets, with a compound annual growth rate (CAGR) of 47.9% from 2022 to 2027, the worldwide artificial intelligence in manufacturing market is expected to dominate price 16.3 billion USD. Furthermore, according to a survey by Deloitte, manufacturing is the leading industry in terms of huge amounts of data. Manufacturers will need to apply AI to analyze the large amounts of data generated.
Therefore, manufacturing companies are leveraging the power of AI to improve efficiency, accuracy, and productivity in a variety of processes.
Artificial intelligence applications in manufacturing include a variety of use cases, such as predictive maintenance, supply chain optimization, quality control, demand forecasting, and manufacturing process automation export. If you are a manufacturer, it’s time to think about using AI in the manufacturing sector.
Supply chain management
Supply chain management plays a vital role in the manufacturing industry and artificial intelligence has emerged as a game changer in this sector. By harnessing the power of AI and ML in manufacturing, companies achieve significant improvements in efficiency, accuracy and cost-effectiveness.
AI in the supply chain enables leveraging predictive analytics, optimizing inventory management, enhancing demand forecasting, and streamlining logistics operations. For example, companies like Amazon are leveraging AI-powered algorithms to speed up deliveries and reduce the distance between products and customers. ML algorithms can analyze historical data, identify patterns, and make accurate predictions about demand fluctuations. For example, an auto parts manufacturer can use an ML model to forecast demand for spare parts, allowing them to optimize inventory levels and reduce costs.
AI solutions can analyze many variables, such as transportation costs, production capacity, and delivery times to optimize the supply chain network. This ensures timely delivery, reduces shipping costs and enhances customer satisfaction
Predictive maintenance
A study conducted by Oneserve (UK) has shown that manufacturers could lose more than £180 billion per year, with 3% of total working days potentially lost due to errors. from machinery and equipment leading to production shutdown. These damages can be predicted and remedied with predictive maintenance solutions, allowing companies to proactively monitor and predict equipment failures, minimize downtime and optimize scheduling. maintenance. Ultimately, it improves operational efficiency and cost efficiency.
In an article about optimizing industrial operations with artificial intelligence, Roland Busch – CTO of Siemens said:
“By analyzing data, artificial intelligence applications can produce results about machine health and find abnormalities to enable predictive maintenance.”
Quality control
Balancing mass production with quality control is a challenging task. The faster manufacturers push the process, the more likely they are to encounter errors and reduce output quality. With Artificial Intelligence, brands can leverage cameras powered by computer vision algorithms to identify errors and detect the root cause of errors instantly. This enables manufacturers to identify and resolve manufacturing defects by quickly detecting anomalies across hundreds of units in seconds.
The practical application has been applied by a textile manufacturing company Welspun in India in controlling the accuracy of fabric samples, ensuring that each product meets quality standards and the weave pattern is even. In addition, classify and identify defects such as tangled fibers, small holes, or discoloration on textile products. AI technology helps Welspun monitor product sample consistency across the entire production line.
Automation with virtual assistants in the manufacturing industry
Virtual assistants serve as interactive and agile platforms for internal and external communication. It creates efficiency and keeps processes moving forward between partners across different time zones without human intervention. Virtual assistants can also provide answers to almost any question. That simplifies or even eliminates the need to search a supplier’s website extensively.
Furthermore, tracking order status is critical given current supply chain conditions. Manufacturing companies no longer need to wait for human responses to monitor outstanding orders and current inventory levels. The virtual assistant can even respond to delivery details and status.
Virtual assistants also maximize opportunities for long-term customer relationships through their round-the-clock availability and consistent communication. Customers can get answers 24/7 through any device as they work across all channels. Virtual assistants can help customers place orders or track items quickly. They can also provide regular updates and send payment reminders. And an added bonus: The virtual assistant can be multilingual.
See more: How can AI virtual assistants help the manufacturing industry?
Conclusion
For the manufacturing industry, AI helps administrators make quick, accurate decisions in real time and predict future operations. This not only helps reduce operating costs but also enhances revenue and increases customer satisfaction with the product. AI can be considered a “leap” for the manufacturing industry, an important opportunity for businesses that are flexible and willing to apply AI in their operating processes.
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