AI in production: opportunities, areas of application and challenges

Before we talk about AI applications in production, it's worth taking a look at the basics.
The term “artificial intelligence” is frequently used but rarely explained precisely.

Artificial intelligence refers to systems that are able to learn from data, recognize patterns and derive recommendations for action. Algorithms form the basis for this. In the context of AI in industrial production, this means that machine and process data is continuously evaluated in order to identify optimizations or deviations at an early stage.

Machine learning is a sub-term of artificial intelligence. Instead of predefined threshold values, the system itself learns what is “normal” and automatically detects deviations.

Deep learning is an evolution of machine learning and uses multi-layered neural networks. They can recognize highly complex patterns.
Typical areas of application of AI in industrial production with deep learning:

Deep learning plays an important role in automated quality control, especially in artificial intelligence production.

NLP enables machines to process and interpret speech. In production, it can be used for:

The introduction of AI applications in production is complex and requires more than just technology. Organizational and technical requirements must be met.

For AI to be successfully implemented in industrial production, companies must create acceptance. AI applications in production require a rethink, not only technically but also culturally. The full potential of artificial intelligence can only be realised when employees understand how it supports their work.

High-quality data, reliable sensors, powerful IT systems and interfaces are the basis for AI in production. Without a clean data base, AI applications cannot be effective in production. Companies like aiomatic naturally support successful implementation.

Many companies are faced with the big question: How do we implement AI sensibly and economically in our production?
‍The challenge lies not only in the technology itself, but in the structured introduction, the right data basis and integration into existing processes.
This is exactly what you need a strong, experienced partner.
‍Aiomatic already monitors over 2,000 machines and knows what is important in practice: from initial data analysis to ongoing optimization of AI models. aiomatic accompanies companies companies step by step through the entire implementation process: structured, transparent and with a clear focus on measurable added value.
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AI in production is fundamentally changing industrial value creation. Artificial intelligence ensures data-based decisions, less downtime and optimized processes. AI applications in production are scalable, economically feasible and suitable for both large companies and SMEs. AI in industrial production is not a temporary trend, but the basis for competitive production systems nowadays.
Companies that rely on AI in production are securing long-term efficiency and quality advantages.