Autonomous intelligence in production
Revolutionary manufacturing: Using AI to create smarter and more efficient production processes.
Production planning
Which machines produce what and when? Capacity planning based on personnel and machine availability
and resource planning.
Bill of materials maintenance
Managing bills of materials in ERP systems. Assigning processing steps to stations.
Operational data acquisition
Feedback on production progress.
Evaluation of downtimes, scrap, cycle times.
Quality management
Input and evaluation of test results. Documentation of errors and rework.
Maintenance of test plans
Production controlling
Analysis of production key figures (e.g. scrap rate, throughput time)
and preparation of reports for the plant or department management.
Test data acquisition
Analysis of production key figures (e.g. scrap rate, throughput time)
and preparation of reports for the plant or department management.
Im Detail
Revolutionary manufacturing: Using AI to create smarter and more efficient production processes.
Automation of parts lists
Are read perfectly and transferred into the system.
The process: The bills of materials must be triggered in the system to start production.
Problem: For each bill of materials, it must be analyzed how the bill of materials are to be triggered. The analysis is based on the component, the days of the week, holidays and special features.
These are all undocumented.
Solution:
The agent learns the relationships and creates a configuration option to reveal its decisions in a comprehensible manner.
Thinking outside the box
Understand what isn't visible in the documents. Interpret accounts, contra accounts, and missing data.
Autonomous intelligence
in production
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Qualitätsmanagement
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Produktionsplanung
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Stücklistenpflege
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Precision that moves your business forward.
Our AI technology optimizes production processes by learning from historical manufacturing data, bills of materials, and quality reports.
The specialized AI not only analyzes data, but also understands processes and relationships – from production planning to quality assurance.
This means that production plans are dynamically adjusted, parts lists are automatically maintained, and deviations in quality management are identified at an early stage – significantly more precisely than with traditional rules or manual controls.
