The manufacturing industry has long relied on telemetry data to measure, evaluate, and draw conclusions about the way they produce goods. AI and machine learning algorithms promise to introduce profound changes to what we can do with data collected from a large number of real-time telemetry sensors, video streams, and audio streams.

This new PDF report, co-created by Emerj and MayaHTT, explores the different ways AI leverages the new capabilities in computer vision and deep learning, to take full advantage of rising digital technologies in continuous manufacturing processes.

In This 14-Page Guide You'll Learn:

1. Unlocking the ROI of Telemetry Data

For decades, researchers relied on simple thresholds and assumptions when working with telemetry data, limiting its applicability. Today, data scientists and data engineers create data pipelines to reliably process and serve telemetry sensor data for AI-enabled processes. You can find the right fit and build the right roadmap to establish data-driven decision-making as part of your organization's DNA.

2. High ROI Applications of AI in Discrete Manufacturing

How to prevent lost time and resources down the line utilizing the proper AI algorithm, how to accelerate production time while keeping the production quality constant, and simulate the real world and its impacts on the production process.

3. High ROI Applications of AI in Continuous Manufacturing

How sensor telemetry, video streams, and other data sources can be leveraged to train AI models and reduce variance, reduce wasted products, improve startup conditions and enhance the quality of the production process results.