This Guidance helps you reduce the time required to set up an in-plant computer vision (CV) quality detection system. It provides workflows and interfaces that enable quality subject matter experts to train CV models so that you don’t have to procure expensive data scientists. The architecture includes a series of interfaces for one-touch gateway onboarding, which eliminates the need for specialized personnel to set up, deploy, and manage the gateways and CV models. The architecture also uses edge technology, machine learning (ML), and user interfaces to initiate quality inference, orchestrate gateway deployments, calculate key performance indicators (KPIs), and visualize data through dashboards.

Architecture Diagram

Download the architecture diagram PDF 

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.

  • KPI and summary dashboards are a feature of this Guidance. The dashboard displays metrics such as OEE and the number of good and bad parts from the images. You can use this dashboard to examine your manufacturing operations and determine whether you are achieving expected outcomes.  

    Read the Operational Excellence whitepaper 
  • The edge-to-cloud communications use security mechanisms provided by AWS, including X.509 certificates for mutual transport layer security (mTLS) and bi-directional encryption of traffic. AWS Identity and Access Management (IAM) roles are used for deployment, and interservice communications are configured following the principle of least privilege access.  

    Read the Security whitepaper 
  • This Guidance uses managed services, which are highly available by design. The in-plant gateway is not highly available, but the Gateway Management feature provides one-touch gateway onboarding, enabling a low recovery time objective (RTO). You can configure what data to back up and where to store that data.

    Read the Reliability whitepaper 
  • Services in this Guidance were selected to reduce the undifferentiated heavy lifting for the end user while operating the solution. For example, AWS IoT SiteWise is used to collect, store, and process incoming data in near real time. This allows you to focus on KPIs important to your business rather than the underlying technology of ingesting data. AWS IoT SiteWise Edge enables the same business logic that operates in the cloud to be deployed to the edge device. This reduces efforts to maintain multiple disparate systems.  

    Read the Performance Efficiency whitepaper 
  • When choosing services for this Guidance, we considered the overall costs of maintaining the architecture, not just the costs for operating a service. For example, although AWS IoT SiteWise Edge has a significant monthly cost, this service will help you save on costs related to customer development, support, and maintenance.  

    Read the Cost Optimization whitepaper 
  • This Guidance uses a combination of managed services and services that elastically scale based on demand. As managed services, AWS IoT Core, AWS IoT SiteWise, and Amazon S3 provide compute and storage on demand. Amazon EKS is configured to scale up and down based on usage.  

    Read the Sustainability whitepaper 

Implementation Resources

A detailed guide is provided to experiment and use within your AWS account. Each stage of building the Guidance, including deployment, usage, and cleanup, is examined to prepare it for deployment.

The sample code is a starting point. It is industry validated, prescriptive but not definitive, and a peek under the hood to help you begin.

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This [blog post/e-book/Guidance/sample code] demonstrates how [insert short description].


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 Amazon EC2 instances or using Amazon S3 storage.

References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon 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.

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