Artificial intelligence in manufacturing

AI - it's hard to imagine everyday life without it as a constant little helper (admittedly also when writing this article).

But what could application scenarios in production be? And how do we at EVOMECS actually deal with them? Because we are being asked this question more and more frequently. On the latter question: apart from initial tests, we have not yet carried out any real implementation. Why is that? Because the foundations have to be laid first. Without high-quality data, there are no meaningful use cases for AI. And that brings us to the first question: what are the possible application scenarios? From EVOMECS' point of view, there are two overarching areas of application: onboarding the system and as features in the application.

1. scalable onboarding - becoming productive faster with AI

The introduction of a new system is a critical moment for many companies. Complex data has to be transferred, processes digitally mapped and new users trained. This is precisely where AI has enormous potential - not as a replacement for project management, but as a digital assistant that takes over routine tasks and reduces complexity.

A conceivable scenario:

Automated system setup:
Instead of manually creating each machine, tool and article, an AI analyzes existing data sources such as Excel lists, CAM systems or ERP exports and creates structured suggestions for system configuration.

Interactive guided setup:
New users are guided step-by-step through typical use cases - context-based, adaptive and understandable. The AI recognizes whether the user is faltering or making mistakes and responds with targeted help.

Error management in real time:
Misunderstandings in operation (e.g. incorrectly assigned workflows, missing resources) are automatically detected - and responded to directly with suggested solutions or offers of correction.

Personalized training recommendations:
The AI recognizes which areas a user uses intensively - or avoids - and suggests suitable training, tutorials or in-app explanations.

The effect: onboarding becomes faster, more efficient and less dependent on external support. This creates real added value, especially for smaller teams or companies with high staff turnover.

2 AI-powered store floor management - intelligent support during ongoing production

AI can also help to improve decisions, stabilize processes and make day-to-day work easier during ongoing operations. The foundation for this has already been laid with EVOMECS - through end-to-end data flows, digital work plans, networked machines and structured feedback.

A possible future scenario:

Automated production planning:
The AI creates an optimized plan based on the order situation, machine availability, tool status and empirical values - or adapts it dynamically if conditions change (e.g. machine breakdown, lack of material).

Adaptive worker instructions:
Instead of rigid work plans, the machine operator receives situational instructions, e.g. in the event of deviations in the process, expected risks or possible optimizations. The AI learns from input, repeat orders and previous machining operations.

Tool strategy and tool life optimization:
The AI analyses wear data, recognizes patterns in usage and recommends targeted changes to tool selection, changeover timing or process parameters - individually for each machine and each application.

Long-term: self-learning processes:
Over the course of many uses, digital experience knowledge is created that the AI uses to make suggestions independently - or to act autonomously within defined limits, for example when changing tools or adjusting plans.

EVOMECS as a foundation: why AI only works in the system

All of these scenarios - from smart help with getting started to intelligent production control - are based on a simple truth: without high-quality data generated by a consistently digital system, AI is of little use.

EVOMECS is designed in such a way that all relevant information is centrally available, contextually linked and structured close to the process - from CAM data records to tool information and machine status. This is the only way to create the digital depth that AI needs to make meaningful decisions.

Our conviction:
Artificial intelligence is not an add-on - it is the result of a consistent digital model. If you lay the foundations, you can build real automation on them.

AI is not a goal, but a tool

The ideas described are not finished product features - but rather a blueprint for gradual, realistic development. Together with our customers, we want to evaluate which functions bring real benefits, which requirements are necessary - and how the EVOMECS platform can continue to develop step by step in the direction of AI support.

Many other application scenarios are conceivable - for example in the area of predictive maintenance, automated QA or production optimization.

The important thing is: Only those who digitalize in a structured way today will be able to use AI effectively tomorrow.