Multi-engine modeling for monitoring, diagnostics, optimization and control

This system takes raw data from industrial machines or processes and first adds descriptive tags to it. It then uses a flexible analytics engine that can dynamically create and run various analysis tools, such as models, optimizers, or classifiers, based on the annotated data. These tools can work together, exchanging information to monitor, diagnose, optimize, or control the industrial operations.

Why it matters: Since 2017, significant advancements in machine learning frameworks and cloud infrastructure have made developing and deploying such modular, data-driven analytical engines more practical and scalable. The ability to dynamically instantiate and integrate diverse analytical models has greatly improved.

Status: ExpiredProtection ended and was never renewed
How hard to build: SpecializedComplex software, data integration, machine learning models

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