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This Guidance helps you generate actionable insights for predictive maintenance management in industrial environments using HAQM Monitron and other AWS services. Machine and process failures often lead to reactive responses and require costly preventive maintenance, which can result in over-maintaining or missed issues. HAQM Monitron allows you to implement proactive, predictive maintenance and reduce unplanned downtime, so you can improve equipment health and uptime while maximizing productivity and quality. This Guidance also enables ingestion of HAQM Monitron insights and the creation of real-time reporting visualizations to support efficient asset management and strategic operational planning.
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Architecture Diagram
Step 1
Install HAQM Monitron sensors on equipment and HAQM Monitron gateway in the factory.
Step 2
Create HAQM Kinesis Data Streams using HAQM Monitron as the data source.
Step 3
Configure Kinesis Data Streams from the HAQM Monitron managed account to the customer account.
Step 4
Configure an HAQM Simple Storage Service (HAQM S3) bucket as the delivery destination of HAQM Kinesis Data Firehose. HAQM S3 serves as the storage foundation for an industrial data lake.
Step 5
Configure HAQM S3 notifications to send events to the HAQM EventBridge destination.
Step 6
Configure an AWS Lambda function as the target of EventBridge destination rules. The Lambda function processes the HAQM S3 event and sends it to an AWS IoT Events state machine.
Step 7
AWS IoT Events responds to the sensor warning state and creates an enterprise resource planning (ERP) work order using Lambda.
Step 8
AWS IoT Events responds to the sensor warning state and notifies personnel using an HAQM Simple Notification Service (HAQM SNS) topic through SMS, mobile push, and email.
Step 9
Connect AWS Glue Data Catalog to an S3 bucket. Schedule an AWS Glue job through EventBridge to update Data Catalog. HAQM Athena queries HAQM S3 data as defined by Data Catalog.
Step 10
Visualize Internet of Things (IoT) metrics and state from Athena queries using HAQM Managed Grafana.
Step 1
Install HAQM Monitron sensors on equipment and HAQM Monitron gateway in the factory.
Step 2
Create HAQM Kinesis Data Streams using HAQM Monitron as the data source.
Step 3
Configure Kinesis Data Streams from the HAQM Monitron managed account to the customer account.
Step 4
Configure an HAQM Simple Storage Service (HAQM S3) bucket as the delivery destination of HAQM Kinesis Data Firehose. HAQM S3 serves as the storage foundation for an industrial data lake.
Step 5
Configure HAQM S3 notifications to send events to the HAQM EventBridge destination.
Step 6
Configure an AWS Lambda function as the target of EventBridge destination rules. The Lambda function processes the HAQM S3 event and sends it to an AWS IoT Events state machine.
Step 7
AWS IoT Events responds to the sensor warning state and creates an enterprise resource planning (ERP) work order using Lambda.
Step 8
AWS IoT Events responds to the sensor warning state and notifies personnel using an HAQM Simple Notification Service (HAQM SNS) topic through SMS, mobile push, and email.
Step 9
Connect AWS Glue Data Catalog to an S3 bucket. Schedule an AWS Glue job through EventBridge to update Data Catalog. HAQM Athena queries HAQM S3 data as defined by Data Catalog.
Step 10
Visualize Internet of Things (IoT) metrics and state from Athena queries using HAQM Managed Grafana.
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Well-Architected Pillars
The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.
The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.
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Operational ExcellenceRead the Operational Excellence whitepaper
HAQM Monitron reduces downtime and enhances operational excellence through predictive maintenance. CloudFormation enforces consistency in deployment, reducing errors associated with manual updates. HAQM CloudWatch provides monitoring, tracking, and auditing for operational controls.
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SecurityRead the Security whitepaper
AWS Identity and Access Management (IAM) and AWS Key Management Service (AWS KMS) manage user access and data encryption. These services support data security for HAQM Monitron users. AWS CloudTrail provides auditing and tracking to support security compliance needs.
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ReliabilityRead the Reliability whitepaper
Kinesis provides reliable data streaming, supporting continuous data ingestion and data flow. Kinesis streams data in real time so your team can act on issues before they impact business continuity across your operations.
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Performance EfficiencyRead the Performance Efficiency whitepaper
Athena is optimized for fast query performance with HAQM S3. Athena automatically executes queries in parallel, so that you get query results in seconds, even on large data sets. With Athena, you don’t have to worry about managing or tuning clusters to get fast performance.
Managed Grafana automatically provisions, configures, and manages the operations of Grafana workspaces. The service auto scales to meet dynamic usage demands and simplifies data visualization for performance monitoring.
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Cost OptimizationRead the Cost Optimization whitepaper
HAQM S3 provides cost-effective, scalable data storage and tiering for large-scale IoT data. HAQM S3 Intelligent-Tiering optimizes storage costs with minimal user intervention. Additionally, HAQM S3 is an optimal destination for Kinesis Firehose and serves as the foundation for a data lake.
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SustainabilityRead the Sustainability whitepaper
This serverless architecture diagram enhances sustainability by reducing manual and unnecessary maintenance of factory equipment. This, in turn, reduces the related carbon footprint of such maintenance while improving equipment uptime. Additionally, the cloud-based services in this Guidance help ensure high availability to facilitate sustainable predictive maintenance activities.
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Disclaimer
The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running HAQM EC2 instances or using HAQM S3 storage.
References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between HAQM or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.