Download: The 2024 AI in European Manufacturing Report

How European manufacturers leverage AI – and what they expect for the future.

Artificial intelligence is nothing new in manufacturing. However, it’s now reached critical mass in awareness.

The hype is everywhere. But what’s the reality for manufacturers on the ground in Europe? And how is AI being infused into manufacturing operations?

This report presents insights into manufacturers’ priorities for AI, the main implementation challenges, and AI’s future impact.

AI: A Strategic Priority

We asked manufacturers how important AI is from a strategic standpoint. The results show that adopting AI is essential or central to most operations. The “hype” of manufacturing today is real.

The interest in AI is understandable, as manufacturers must produce increasingly complex and higher-quality products faster than ever.

The Gap Between Hype and Adoption

Here, European manufacturers show a gap between what they wish to achieve and what they currently do with AI.

Most European manufacturers aren’t using AI at all yet.

Things are different in other parts of the world. In North America, 21% of manufacturing companies say they already use an AI solution. An additional 18.5% say they’ve established AI use cases that generate business value.

Popular AI Applications

While there are plenty of applications for AI in manufacturing, some key outcomes are sought.

Some of these include:

Quality Control and Inspection: Potential faults and imperfections can be automatically identified, saving time and effort. In one use case, machinery OEM reduced assembly process failures by 70%.

Optimizing Production Planning: Manufacturers strive for efficient production planning. AI-enabled production planning helps improve decision-making and adapt to rapidly changing situations in real time. Understanding the nonlinear nature of the design process in software development is crucial, as AI can help manage this complexity and prevent the oversimplification of production planning.

Maintenance: Machines can undergo predictive maintenance with dynamic scheduling to ensure maximum performance with minimum downtime.

Supply Chain Management: AI can mitigate or prevent supply chain disruptions, helping to find alternative suppliers, onboard new suppliers, and more.

Improving Efficiency on Production Lines

Enhancing efficiency on production lines is vital for reducing production costs and boosting productivity. One effective approach is implementing lean manufacturing principles, which focus on eliminating waste and maximizing value-added activities. This can be achieved by streamlining the production process, reducing inventory levels, and adopting just-in-time production methods. Investing in automation technology, such as robots and machine learning algorithms, can significantly improve efficiency and reduce labour costs. Manufacturers can ensure a smoother, faster, and more cost-effective production process by optimising production lines.

Enhancing Product Quality

Maintaining a competitive edge in the market requires a relentless focus on enhancing product quality. This can be accomplished by implementing rigorous quality control measures throughout production. Inspecting raw materials, monitoring production lines, and testing final products are essential to ensure high standards. Furthermore, investing in research and development can improve product design and functionality, resulting in increased customer satisfaction and loyalty. Manufacturers can deliver superior products that meet and exceed market expectations by prioritising quality at every stage of the production process.

AI Challenges: Easier Said than Done

S

Survey results show that manufacturers focus on AI in their strategies but are not yet integrating it into their day-to-day processes.

We wanted to know why.

The biggest challenge cited was a lack of expertise.

The high demand for AI is outpacing the available skills, showing a significant difference between the demand for the technology and the means to implement it.

Integrating with Existing Systems

Integrating mass production with existing systems is crucial for ensuring a seamless and efficient production process. Implementing enterprise resource planning (ERP) software can help manage various aspects of production, including planning, inventory control, and supply chain management. ERP systems can significantly reduce production costs and productivity by automating tasks and reducing manual errors. Integration with existing systems allows manufacturers to streamline operations, enhance coordination, and achieve greater efficiency in their production processes.

Case Studies of AI in European Manufacturing

The adoption of artificial intelligence (AI) in European manufacturing is on the rise, with numerous companies leveraging AI-powered solutions to enhance efficiency, reduce costs, and improve product quality. Here are a few notable case studies:

• German Automotive Manufacturer: A leading automotive manufacturer in Germany implemented an AI-powered predictive maintenance system to minimize downtime and boost production efficiency. Using machine learning algorithms to analyze sensor data from production equipment, the system could predict when maintenance was needed, reducing downtime by 20%.

• French Aerospace Manufacturer: In France, an aerospace manufacturer implemented an AI-driven quality control system aimed at improving product quality and minimizing defects. By employing computer vision and machine learning algorithms, the system analyzed products and identified defects, achieving a 15% decrease in defect rates.

• UK-based Food Manufacturer: A food manufacturer in the UK implemented an AI-powered supply chain management system to improve inventory control and reduce waste. By analyzing sales data and predicting demand with machine learning algorithms, the system reduced inventory levels by 10% and waste by 5%.

These case studies illustrate AI’s transformative potential in European manufacturing. By embracing AI-powered solutions, manufacturers can significantly improve efficiency, reduce costs, and improve product quality, ultimately gaining a competitive edge in the market.

Outlook: High Hopes for the Future

European manufacturers may face challenges in implementing AI as freely as they’d like, but they’re optimistic about the future. They have high expectations of how AI will improve efficiency in the next few years and expect a massive impact.

Download the Full Report

For more insights, download the full AI in European Manufacturing Report.