Digital Platforms

Camális

Predictive analytics to track the condition of industrial assets

Use the plant's history to identify patterns, predict behaviors and support operational diagnostics with models trained on your own data.

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Context

The challenge

Industrial plants accumulate years of data that are rarely used beyond a quick trend lookup. At the same time, much of the diagnostic work depends on the experience of a few specialists.

Camális structures this history and allows turning specialists' knowledge into models and rules that run continuously.

Benefits

What your operation gains with Camális

Failure anticipation

Models trained on the history help flag conditions that precede known failures.

Pattern identification

Behaviors that go unnoticed in isolated analysis appear when data is treated together.

Making use of history

Already-recorded data gains analytical use, with organized and labeled datasets.

Predictive models

Prediction of states and operational conditions based on monitored variables.

Less manual analysis

Repetitive checks are now carried out by the models, flagging only what deviates from expectations.

In focus

From raw data to a usable dataset

Before any model, the base needs to be organized. Camális offers labeling, classification and industrial dataset construction capabilities, a step that usually determines the quality of the result.

Data labeling and classification
Dataset construction and management
Recording specialists' knowledge as rules

In focus

Diagnostics that reach the operations team

Model results are presented as diagnostics and recommendations, in language close to that of the operation, alongside monitoring of critical indicators.

Anomaly and trend detection
Monitoring of critical indicators
Generation of diagnostics and recommendations

Capabilities

Main features

Machine Learning models

Development and execution of models applied to operational variables.

Industrial datasets

Construction, labeling and management of the databases used to train the models.

Anomaly detection

Identification of patterns, trends and behaviors outside expectations.

Diagnostics and recommendations

Translation of analytical results into guidance applicable to daily routines.

Other features

Prediction of operational states and conditions
Monitoring of critical indicators
Development of predictive models

Application

In practice

Camális receives the operation's historical and current data, runs the models defined together with the client and makes results available as diagnostics, predictions and indicators tracked by the technical team.

Business value

Why Camális can matter to your company

Knowledge about plant behavior is usually concentrated in a few people. Recording this knowledge in models and rules makes diagnosis less dependent on individual availability and allows the operation's history to be used systematically.

Want to use your plant's history to anticipate problems?

Talk to the IDUS team about the data available in your operation and the models worth applying.

Talk to IDUS

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