Cloud data & AI are fundamentally changing industrial operations by optimizing production, reducing costs and automating quality assurance. Companies benefit from predictive maintenance, more efficient manufacturing processes and intelligent supply chains.
Artificial intelligence analyzes sensor data in real time to detect failures early and proactively manage maintenance. Machine learning improves production planning by optimizing demand forecasts and efficiently allocating resources. Computer vision enables automated quality control, while data-driven process optimization minimizes error rates. Shop floor analytics help to monitor machine uptime and material flows in real time, identify bottlenecks and make production processes more efficient. Process mining uncovers inefficiencies and supports continuous process improvement.
With over 30 years of experience and more than 3.000 successful projects, synvert is the ideal partner for companies that want to drive their digital transformation with cloud data & AI.
Pioneering self-service Data Mesh platform implementation – Using Cloudera Data Platform on AWS at a global commercial vehicle manufacturer.
Built a cloud data platform from scratch in Azure for a leading global manufacturer of consumer goods, including an automated forecasting tool to improve their manufacturing timelines and drive profit margins.
Natural Language Processing in Automotive Reporting. An ingestion mechanism including OCR digitization, artefact removal and text cleansing was created and has since been fed well over a million reports. As a final step in the NLP pipeline, topic modelling was used to tag the documents according to their content.
Automatic classification of cars by their model – A deep convolutional neural network was trained to identify car types. It can identify roughly 200 different types of cars with near-human level accuracy.
Development of new and improved ETL processes of the production data warehouse (pDWH) for evaluating production parameters, quantity runs and dependent KPI values for a manufacturer of electronic components.
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