Risks and Faults We Can Detect Using Machine Learning and Physics

Maintenance and reliability professionals can preemptively adjust, repair, or replace affected equipment before costly or devastating consequences occur.

OK, I’ve Got 24/7 Monitoring Data. Now What?

By overlaying schematics about systems and their IoT sensors with known facts about the physics of how each element should behave, you can discover design faults, detect potentially miscalibrated sensors, and take corrective action.

How the Special Snowflake Problem Impacts Asset Management—and What You Can Do

24/7 system monitoring data received from parallel but unlike facilities can be optimized and distilled into action.

Bridging the Gap from Data to Value: 3 Ways Physics-based Modeling and a Digital Twin Can Help Overcome Sensor Limitations

Facilities are achieving a more durable, digital foundation for understanding and mapping processes and priorities.

brochures & case studies

Tignis Overview

How Tignis increases the reliability of connected mechanical systems with physics-driven analytics.

Pharma Product Overview

Advanced technologies provide the means to upgrade maintenance, reliability, production, and energy management while controlling costs and ensuring high product quality.

Powering Process & Reliability Improvements
in Semiconductor Manufacturing

Increase your process efficiency, quality, and yield through Tignis AI and ML product suite.

Case Study: Optimum Energy

Optimum Energy uses Tignis software to detect faults in vast amounts of chiller plant sensor data.