Tignis

Predictive and Proactive Support Solutions

Physics-Driven Analytics for Connected Industrial Systems

A New Approach to Reliability and Optimization

Tignis provides a physics-driven software solution for managing industrial assets, processes and operations. Using machine learning and digital twins, Tignis monitors mechanical systems, not just individual assets, so manufacturers can expand predictive maintenance coverage, detect and reduce risks to plant or line reliability, enhance O&M team productivity, and improve plant performance.

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How Tignis Works

Step 1: You Provide Step 2: We Create Step 3: Your Results

You Provide

We start with two items you likely already have: piping and instrumentation diagrams (P&ID) and historical sensor data.

Step 1

We Create

We quickly create a digital twin—a digital replica of your piping and instrumentation systems that shows a detailed view of the current state of your systems.

Your Results

Automated condition monitoring: fast and accurate anomaly detection, with algorithms specifically designed for connected systems. Immediate and highly accurate results: reduce the time to identify, analyze and resolve true system deviations so you can predict operational impacts.

The Tignis solution includes both software and human expertise. Our advanced technology, data scientists and subject matter experts can quickly augment your team’s capability. Tignis also enables remote monitoring.

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WATCH: A New Approach to Reliability & Optimization

System-Wide Benefits

Tignis expands your asset coverage and increases reliability—all while using your existing sensors and staff. You’ll experience fewer false alarms, achieve better outcomes, and expand coverage across all assets with just one subscription to Tignis.

Expanded Coverage
Continual Optimization
Early Warning
Energy Savings

Get Started with Tignis Today

Tignis can quickly help you improve reliability and efficiency. Getting up and running with Tignis requires very limited effort on your part and maximizes the assets you already have.

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The Physics and Machine Learning Blog

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Tignis TV: Jason McColly Interview