How Amazon Lookout for Equipment works - Amazon Lookout for Equipment

How Amazon Lookout for Equipment works

Amazon Lookout for Equipment uses machine learning to detect abnormal behavior in your equipment and identify potential failures. Each piece of industrial equipment is referred to as an industrial asset, or asset. To use Lookout for Equipment to monitor your asset, you do the following:

  1. Provide Lookout for Equipment with your asset's data. The data come from sensors that measure different features of your asset. For example, you could have one sensor that measures temperature and another that measures pressure.

  2. Train a custom ML model on the data.

  3. Monitor your asset with the model that you've trained.

You need to train a model for each of your assets because they each have their own data signatures. A data signature indicates the distinct behavior and characteristics of an individual asset. This signature depends on the age of the equipment, its operating environment, what sensors are installed (including process data), who operates it, and many other factors. You use Amazon Lookout for Equipment to build a custom ML model for each asset. For example, you would build a custom model for each of two assets of the same asset type, Pump 1 and Pump 2.

The model is trained to use data to establish a baseline for the asset. It's trained to know what constitutes normal behavior. As it monitors your equipment, it can identify abnormal behavior that might indicate a precursor to an asset failure. Amazon Lookout for Equipment uses machine learning to detect deviations from normal behavior because asset failures are rare and even the same failure type might have its own unique data pattern. All detectable failures are preceded by behavior or conditions that fall out of the normal behavior of the equipment, so Lookout for Equipment is designed to look for those behaviors or conditions.

If you have the data available, you can highlight abnormal equipment behavior using label data. The trained model can use the anomalous behavior in the dataset to improve its performance.

When you train a model, Amazon Lookout for Equipment evaluates how different types of ML models perform with your asset's data. It chooses the model that performs the best on the dataset to monitor your equipment.

You can now use the model to monitor your asset. You can schedule the frequency with which Amazon Lookout for Equipment monitors the asset.

Although Amazon Lookout for Equipment can warn you of a potential failure, it cannot tell you the exact failure mode. It can use the sensors from which it analyzed data to indicate a failure. You can use this information to see if your equipment is in a state that could lead to a failure.

To use Amazon Lookout for Equipment to monitor your equipment, you must do the following:

    1. Create and properly format .csv files containing your sensor data. For more information, see Formatting your data.

    2. Upload your data to Amazon Simple Storage Service (Amazon S3). For more information, see Uploading your data into Amazon S3.

    3. Use a schema to create a dataset from the .csv files that you've uploaded. A schema defines the organization of your data in JSON format. The dataset that you generate from this process is a container for the sensor data that you've uploaded. For more information, see Creating a dataset in Amazon Lookout for Equipment.

    4. Ingest the dataset into Amazon Lookout for Equipment. Ingesting the dataset imports it into a format that the ML model can use for training. For more information, see Ingesting a dataset.

    5. Train a model on the dataset. For more information about training a model, see Training a model.

    6. Monitor your asset with the model that you've trained. For more information, see Monitoring your equipment in real time.

    You repeat the preceding steps for each asset that you want to monitor. Before you use Amazon Lookout for Equipment to monitor your equipment, you need to set it up. To set up Amazon Lookout for Equipment, see Setting up Lookout for Equipment.