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4 ways generative AI addresses manufacturing challenges

IBM Big Data Hub

Facing a constant onslaught of cost pressures, supply chain volatility and disruptive technologies like 3D printing and IoT. Various initiatives to create a knowledge graph of these systems have been only partially successful due to the depth of legacy knowledge, incomplete documentation and technical debt incurred over decades.

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Understanding Social And Collaborative Business Intelligence

datapine

Discovery and documentation serve as key features in collaborative BI. This kind of analysis leads to feedback that can aid in improving the decision-making process, letting companies document the best practices and monitor the data that’s the most useful in this scenario. However, collaborative BI helps in changing that.

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Bridging the Gap Between Industries: The Power of Knowledge Graphs – Part I

Ontotext

Here again knowledge graphs organize and link large amounts of data on aircraft design, manufacturing, maintenance and performance. By linking this data, they facilitate tasks like asset management, predictive maintenance, documentation management, mission planning, risk management, aircraft design and optimization, and anomaly detection.

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Understanding Social And Collaborative Business Intelligence

datapine

Discovery and documentation serve as key features in collaborative BI. This kind of analysis leads to feedback that can aid in improving the decision-making process, letting companies document the best practices and monitor the data that’s the most useful in this scenario. However, collaborative BI helps in changing that.