Solution Feature
An AI module that automatically searches connected machine data, recognizes patterns and makes visible which systems have potential for improvement, which process parameters drive rejects and which factors influence availability.
Contact usFunctional classification
The Copilot is an AI extension of the Bytefabrik platform. It builds on existing production data, alarms and technical context information and adds an additional level of processing and interpretation.
The aim is not to replace traditional analysis interfaces, but to guide teams more quickly to relevant contexts, questions and next steps in the analysis.
The co-pilot not only searches for known messages. It actively evaluates the available data with the help of AI, recognizes recurring patterns and automatically highlights the correlations that are really relevant for quality, availability and continuous improvement.
Copilot continuously searches connected production and machine data for patterns that often become visible too late or only with a great deal of manual effort in day-to-day operations.
Copilot automatically searches connected machine data for recurring patterns and highlights systems, lines or areas where performance, stability or quality can be specifically improved.
Instead of just describing individual alarms, the copilot shows which parameters, states or combinations are typically associated with high scrap, rework or unstable processes.
The AI links historical data, events and production context and makes visible which factors influence availability, which patterns occur before disruptions and where preventive action can be taken.
Less reading, more product feel
Conspicuous patterns are automatically translated into comprehensible stories with charts, context and concrete indications of areas for improvement.
More about Data StoriesThe Copilot combines automatic pattern search, context processing and interaction based on the same platform data.
What the function is based on
The Copilot is based on existing production, alarm and context data and supplements it with an additional evaluation layer.
Assets, stations, process references or product contexts must already be technically describable so that signals can be meaningfully categorized.
The Copilot does not replace data collection or specialist applications, but supports teams in interpreting and prioritizing existing information.
In practice, the copilot is not created in isolation, but as an extension of an existing data and analysis environment.
First of all, signals, alarms, histories and relevant system or process contexts must be available on the platform.
The co-pilot identifies relevant events and prepares them in a structured way with history, context and initial information.
Teams use chat, story views or linked analyses to categorize the situation more quickly.
Documented cases and recurring patterns are retained and can be used again for future incidents.
Demo
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