Artificial Intelligence In Manufacturing Market - Forecast (2023 - 2028)

The application of artificial intelligence in manufacturing encompasses a wide range of use cases, such as predictive maintenance, supply chain optimization, quality control, and demand forecasting. The global artificial intelligence (AI) in manufacturing market size is expected to reach $25.2bn by 2018 from $4.1bn in 2022. By applying AI to manufacturing data, companies can better predict and prevent machine failure. This in turn reduces expensive downtime in manufacturing processes. AI in manufacturing has many other potential uses and benefits, such as improved demand forecasting and reduced waste of raw materials.

Artificial Intelligence (AI) is changing the manufacturing industry by making it much more efficient and better at controlling quality. AI is changing how production is done because it can analyze vast amounts of data, make real-time decisions, and automate processes.
- Predictive Maintenance: Sensor data from machinery and equipment can be analyzed by AI-powered systems to predict possible breakdowns and plan preventive maintenance. By finding problems before they happen, manufacturers can avoid expensive downtime, extend the life of their equipment, and increase their total productivity.
- Quality Control: AI lets inspection and quality control tasks be done automatically. Machine learning systems can look at data from cameras and sensors to find problems, deviations, and oddities in real time. This ensures that products meet strict quality standards, lowers the chance that customers will get broken items, and improves the general quality of the products.
- Process Optimisation: Data from production lines, supply chain systems, and inventory management can be used by AI algorithms to improve the efficiency of industrial processes. AI can suggest process improvements, reduce waste, and improve operational efficiency by finding patterns, bottlenecks, and inefficiencies.
- Supply Chain Management: AI-powered systems can improve how the supply chain works by looking at data about inventory levels, demand trends, and how healthy suppliers are doing. This helps manufacturers predict demand more accurately, keep the right amount of stock on hand, and improve their ties with suppliers, which saves money and speeds up delivery.
- Better Decisions: AI gives producers data-driven insights that help them make better decisions. AI algorithms can help with production planning, resource sharing, and product development by analyzing vast amounts of past and present data. This lets manufacturers make intelligent choices, lower risks, and improve their business strategies.
- Collaboration Between Humans and Robots: AI-driven robots and cobots (collaborative robots) can work with humans to do repetitive or physically demanding jobs quickly and accurately. This improves worker safety and frees up human workers to work on more complicated and strategic tasks.



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