Amazon Lookout for Equipment uses industrial data from your equipment to detect potential failures so you can take action, such as performing maintenance before a breakdown, to avoid unplanned downtime.
Documentation
Getting started sample
This getting started sample can be used to develop hands-on experience on how to query the Amazon Lookout for Equipment API. Use this content to get started with ingesting data, building models, and building nice visualizations to review your model results.
Getting started with Lookout for Equipment console
This getting started focuses solely on the Lookout for Equipment console. This will walk you through an end-to-end journey using Lookout for Equipment from ingesting the data to deploying an anomaly detection model. All of this, without writing a single line of code!
Amazon CloudWatch Custom Widgets dashboard
Do you need non-developers to review your model and inference results? What about using CloudWatch custom widgets to build beautiful dashboards for any internal user? This repo comes with a CloudFormation template you just need to deploy before following this Read Me note.
Python SDK
Dedicated to Python developers, the Amazon Lookout for Equipment Python SDK is an open-source library that allows data scientists and software developers to build, train, and deploy anomaly detection models for industrial time-series data using Amazon Lookout for Equipment. This library, available from the PyPI package repository, allows you to ingest data, train models, and display beautiful visualization you can incorporate with a few Python lines of code. Read the full documentation and check out a short example illustrated in a concise notebook.
GitHub | Documentation
Lookout for Equipment demo
The AWS Samples GitHub repository for Amazon Lookout for Equipment contains examples illustrating how you can start building your anomaly detection application for your industrial assets. The examples are in Jupyter notebooks and contain detailed commentaries and explanations, making it easy to understand how to use the service. They include step-by-step guidance for configuring the Boto3 API for Lookout for Equipment and invoking various APIs for preparing the data, creating a dataset, training a model, evaluating a model, and scheduling an inferencer. You can also find helper functions for visualizing your time-series data.
Lookout for Equipment Installation Instructions
The Lookout for Equipment Web App is an application you can deploy in your own account with a simple CloudFormation template. This application will help you assess quickly if your industrial data contains any historical anomaly of interest. After you upload a dataset containing sensor measurements from your industrial equipment or manufacturing process, the app will guide you to train an anomaly detection model. You will then be able to visualize your model results and deploy it, making it ready to receive your shop floor live data. This application also includes an operational dashboard to visualize your live results.
Videos
Blogs
New – Amazon Lookout for Equipment Analyzes Sensor Data to Help Detect Equipment Failure
by Harunobu Kameda
Dec 1, 2020
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Strengthening Operational Insights for Industrial Assets with AWS IoT AIML Solution (part 1)
by Julia Hu, Dastan Aitzhanov, Michaël Hoarau, and Sebastian Salomon
Dec 16, 2021
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Strengthening Operational Insights for Industrial Assets with AWS IoT AIML Solution (part 2)
by Julia Hu, Theodore Bakanas, Dastan Aitzhanov, and Michaël Hoarau
Dec 16, 2021
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Enable predictive maintenance for line of business users with Amazon Lookout for Equipment
by Johann Fuechsl and Michaël Hoarau
Mar 28, 2023
Deploy a predictive maintenance solution for airport baggage handling systems with Amazon Lookout for Equipment
by Michaël Hoarau, Moulham Zahabi, and Fauzank
Apr 12, 2023
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Get started building with Amazon Lookout for Equipment in the AWS Management Console.