Root Cause Analysis

Move fast when things break

Uncover the root causes of production issues in minutes, not days. When something goes wrong, Ethon instantly runs a root cause analysis across all process data and surfaces the parameters driving the issue.

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Detect, explain, and resolve production issues faster and more precisely than anytime before.

The first root cause analysis that provides automated diagnostics with Causal AI technology.

More than

More effective root-cause detection

Benchmarks show Ethon’s causal models consistently uncover more relevant drivers than other causal discovery methods.

Up to

Faster issue resolution

Customers have solved complex production issues in minutes instead of weeks through automated diagnostics.

USD

0M+

Annual savings per plant

Verified causal insights and faster resolution eliminate recurring issues while reducing downtime, scrap, and product recalls.

01 Detect

Detect emerging issues automatically

Ethon continuously scans thousands of process parameters to flag anomalies and emerging issues in real time. Each detection automatically creates an incident and launches a diagnostic workflow.

02 Aggregate

Auto-aggregate all relevant data

Once an issue is detected, Ethon brings together all relevant parameters and context. The workflow uses the process knowledge graph to mirror how production actually works, ensuring every analysis starts with a complete and correctly framed dataset.

03 Model

Model root causes automatically

Ethon's Reasoning Model builds a causal graph that mirrors the physical relationships within the process. It models how parameters influence one another, reveals the interaction patterns behind the deviation, and produces a graph-based view of the drivers most likely responsible for the issue.

04 Explain

Explain root causes in plain language

Ethon translates the causal graph into a clear, structured report. It summarizes what happened, explains why the issue occurred, and highlights the key drivers in plain language — supported by ranked parameters, visual graphs, and quantified effects.

05 Operationalize

Turn findings into repeatable SOPs

Engineers can turn findings into SOPs, rule-based monitors, and prescribed corrective actions. Ethon alerts operators when defined conditions recur, ensuring issues are addressed consistently, preventing repeated failures, and embedding process knowledge into daily operations.

Frequently asked questions

What are typical use cases for root cause analysis?

Ethon’s Root Cause Analysis is used to investigate production issues like increased scrap rates, spec limit violations, quality issues, product recalls, process deviations, and unplanned downtime. It helps teams find the underlying causes behind drifts, instability, and performance variations across lines and factories.

What data does Ethon need to perform a root cause analysis?

Ethon connects to existing factory data sources such as MES, PLCs, Historians, sensors, and IoT platforms. The more complete the process data, the more precise the causal explanations, but even limited datasets can provide meaningful insights.

How much data is needed to get meaningful insights?

What matters most is variation, not volume. If a process always runs at one fixed setpoint, no algorithm can find what drives the problem. Ethon works with anything from 30–40 batches or parts to millions of production runs, and from about 10 to several thousand measured parameters. As long as the data shows enough change, the software can reveal true cause-and-effect relationships.

Does Ethon require data scientists to use?

No. The workflow is designed for process experts and operators. Analyses are triggered automatically, and results are presented as clear, explainable reports. That said, many data scientists use Ethon through our Jupyter notebook integration to pull results directly, compare them with custom analyses, and extend workflows using Python.

Can Ethon really deliver results in minutes?

Yes. By combining automated diagnostics with causal reasoning, Ethon can identify, explain, and report issues in minutes. Customers who once spent weeks diagnosing problems that cost millions now uncover the true causes instantly and prevent them from recurring. Additionally, independent benchmarks show that our Causal Reasoning Model identifies over four times more relevant drivers of production issues than other causal discovery methods.