What does this AWS Solutions Implementation do?

This solution implementation helps industrial customers use the data produced by their factory equipment to create the reporting needed to actively monitor their assets 24x7 for machine breakdowns. This solution empowers production personnel to proactively respond to production interruptions and maximize asset availability.

Benefits

Visibility into disparate production processes

Access near real-time views of machine status across lines and factories.

Responsive web interface for monitoring

Monitor and view factory equipment using a responsive web-based interface that shows historical views of a machine’s availability and performance.

Flexible configurations
.

Configure machine data such as tags and values, based on your unique needs. 

Visualize machine data
.

Provision a flexible data model and an intuitive, configured user interface to map, group, and visualize machines in a factory floor setup.

AWS Solutions Implementation overview

The diagram below represents the architecture flow you can automatically deploy using the solution’s implementation guide and accompanying AWS CloudFormation template.

Machine Downtime Monitor on AWS | Architecture Flow Diagram
 Click to enlarge

Machine Downtime Monitor on AWS Solutions Implementation architecture

The AWS CloudFormation template deploys the following serverless infrastructure and web content for Machine Downtime Monitor on AWS:

  1. An Amazon Kinesis data stream serves as the solution’s entry point after a connection method for sending machine data into AWS is established.
  2. The Kinesis data stream serves as an event source for the Filter Kinesis Stream AWS Lambda function, which filters for messages reporting machine status.
  3. Machine status and production count messages are written to the Real Time Data Amazon DynamoDB table, which is the data source for the historical view in the dashboard. Machine names and status changes are stored in the UI Reference DynamoDB table, which is used to display the machine overview in the dashboard.
  4. AWS AppSync serves as the solution’s API layer. Changes in machine status result in a GraphQL mutation, which updates the solution’s dashboard. The dashboard requests data via GraphQL queries and receives updates using GraphQL subscriptions.
  5. View the dashboard component using an interactive web interface, which lets you set up and monitor machine status events. This dashboard is distributed using Amazon CloudFront and an Amazon S3 bucket as its origin. An Amazon Cognito user pool and identity pool manage user authentication and authorization.
  6. Machine data sent to the Kinesis data stream is stored in a raw data S3 bucket via Amazon Kinesis Data Firehose.
  7. An AWS Glue workflow activates daily at 1:00 AM (UTC). The workflow starts AWS Glue jobs that process the raw data and store the results in the processed data Amazon S3 bucket. Then, the workflow starts an AWS Glue crawler that updates the AWS Glue Data Catalog.
  8. Query the AWS Glue Data Catalog manually using Amazon Athena or visualize the data using Amazon QuickSight.

Machine Downtime Monitor on AWS

Version 1.0.0
Released: 04/2021
Author: AWS

Estimated deployment time: 5 min

Estimated Cost Source Code  CloudFormation template 
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Solving with AWS Solutions: Machine Downtime Monitor on AWS
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