Developing a modern manufacturing enterprise requires careful thought and attention to several priorities. Predictive maintenance and issue resolution automation are likely high on your list. Maximizing your operational efficiency and optimizing output are critical in this competitive global market. As demand grows, manufacturers are under pressure to fulfill increased production needs.

A recent report from McKinsey on Industry 4.0 technologies discusses pandemic implementations such as digital issue detection and resolution. These solutions are critical for crisis response in the COVID-19 era. 30% of manufacturers have highlighted increased operational productivity, reduced time-to-market, and reduction in cost as major strategic imperatives for their Industry 4.0 transformation.

Amazon Virtual Andon 3.0 (AVA) is an Amazon Web Services (AWS) Solution that provides a scalable, digital Andon system to help detect and resolve issues. It optimizes processes, supports your transition to predictive maintenance, and helps prevent future equipment failures.

Overview of new features

AVA provides factory and fulfillment center associates with an intuitive, responsive web interface and workflow. This can be used to raise issues, route those issues to the appropriate engineers, and resolve them in a timely way. With AVA, you can associate explanatory root causes with resolved issues for more insightful reporting. Issue raising and resolution happen digitally. There’s no need for manual intervention (such as raising a manual alarm at a factory workstation.)

AVA introduces the capability to raise issues directly from devices and automated APIs. Flexible integrations can be made directly with your factory devices and systems. Additionally, the APIs integrate with Amazon Machine Learning (ML) services, such as Amazon Lookout for Equipment and Amazon Lookout for Vision. This enables you to automate ML inference into your AVA-based workflows.

With AVA 3.0, you can now monitor your factory floors for disruptions in near-real-time. You can respond and resolve issues quickly, minimizing production disruption. AVA 3.0 provides users with an analytics pipeline so you can create dashboards and custom reports.

Introducing GraphQL APIs

The solution introduces GraphQL APIs via AWS AppSync, secured through AWS Identity and Access Management (IAM) policies. This powers the web interface and functionality to create, route, and manage issues. With AVA GraphQL APIs, you can create and manage site hierarchies, devices, events, and raise and manage issues. For example, you can create an issue by calling the createIssue API to raise issues and track them to completion automatically.

createIssue
{
    id: "<string>",
    siteName: "<string>",
    areaName: "<string>",
    stationName: "<string>",
    deviceName: "<string>",
    processName: "<string>",
    eventId: "<string>",
    eventDescription: "<string>",
    eventType: "<string>",
    issueSource: "<string>",
    priority: "<string>",
    status: "<string>",
    created: "AWSDateTime",
    acknowledged: "AWSDateTime",
    closed: "AWSDateTime",
    acknowledgedTime: "<number>",
    resolutionTime: "<number>",
    createdBy: "<string>",
    additionalDetails: "<string>"
  }

Integration with Amazon Machine Learning services to raise issues automatically

With AVA APIs, you can integrate with predictive services like Amazon Lookout for Equipment (L4E). AVA provides an AWS Lambda function for detecting anomalies generated via L4E. It automatically calls the APIs to create issues for abnormal events.

When L4E detects anomalies in your machinery or production line, AVA can automatically raise issues for those anomalies (Figure 1). This gives you the visibility and tracking mechanism to ensure anomalies are resolved. You can create automated events and issues via APIs by integrating with Amazon Lookout for Equipment. You’re able to track anomalies with their details in near-real-time.

Fig1 ava 0 indicates that an anomaly has been detected, and AVA will raise an issue with the underlying sensor details.” width=”1063″ height=”611″>

Figure 1. AVA displays anomalies raised from L4E. A prediction score of > 0 indicates that an anomaly has been detected, and AVA will raise an issue with the underlying sensor details.

Direct device integration

AVA provides the capability to integrate with IoT devices via AWS IoT Core. You can configure your IoT devices to send data to the ava/issues AWS IoT Core topic. Additionally, AVA can send messages to the ava/devices AWS IoT Core topic to automatically raise issues via MQTT or HTTPS. It maps your machine name to an AVA device and a tag/value combination to an AVA event.

{
  "id": <ID!>,
  "eventId": String,
  "eventDescription": String,
  "type": String,
  "priority": String,
  "siteName": String,
  "processName": String,
  "areaName":" String,
  "stationName": String,
  "deviceName": String,
  "created": AWSDateTime,
  "acknowledged": AWSDateTime,
  "closed": AWSDateTime,
  "status": "open"
}

Analytics pipeline for custom dashboards

AVA uses Amazon DynamoDB to store factory configuration and issues data. All AVA data is exported from the DynamoDB database to an Amazon S3 bucket via an AWS Glue workflow. You can then use Amazon Athena to query underlying data and create custom reports using business intelligence (BI) solutions like Amazon QuickSight (Figure 2). With the analytics pipeline, you can create custom dashboards and monitor your factory operations holistically.

Figure 2. Custom dashboard generated via Amazon QuickSight

Figure 2. Custom dashboard generated via Amazon QuickSight

Architecture and workflow

Figure 3. AVA 3.0 architecture

Figure 3. AVA 3.0 architecture

The AWS CloudFormation template deploys the following infrastructure, shown in Figure 3:

  1. The AWS CloudFormation template provides an Amazon CloudFront web interface that deploys into an Amazon Simple Storage Service (Amazon S3) bucket configured for web hosting.
  2. An Amazon Cognito user pool allows this solution’s administrators to register users and groups using the web interface.
  3. AWS AppSync GraphQL APIs and AWS Amplify power the web interface. Amazon DynamoDB tables store the factory data.
  4. An AWS IoT rule engine helps you monitor manufacturing workstations or devices for events. It then routes the event to the correct engineer for resolution in real time.
  5. Authorized users can interact with and receive notifications from this solution. An AWS Lambda function and Amazon Simple Notification Service (Amazon SNS) send emails and SMS notifications.
  6. Issues created, acknowledged, and closed in the web interface are recorded and updated using AWS AppSync and DynamoDB.
  7. The AWS AppSync GraphQL APIs can be called directly with HTTP POST requests.
  8. If you are using L4E to monitor your machines, enter the name of the Amazon S3 bucket where inference files will be delivered in the Anomaly Detection Output Bucket CloudFormation parameter. This solution can be configured to automatically raise issues if an anomaly is detected.
  9. When the Activate Glue Workflow CloudFormation parameter is set to “Yes”, an AWS Glue workflow will be created to extract data from DynamoDB. It delivers this data via an AWS Glue Data Catalog into Amazon S3. For more information, refer to the Data Analysis section.
  10. You can use an existing SAML provider as an additional identity provider for access to this solution. You can configure the Amazon Cognito Domain Prefix, SAML Provider Name, and SAML Provider Metadata URL CloudFormation parameters. For more information, refer to SAML identity provider.

An intuitive UI with nested events

With AVA, you also can create nested events / issues, so you can more easily get to the root of the problem and resolve issues quickly. The solution builds upon the same intuitive UI as highlighted in this previous Amazon Virtual Andon blog post. In addition, it allows you to manage events granularly, create subevents, raise, and resolve issues and sub issues (Figure 4).

Figure 4. AVA allows you to raise issues and sub issues (for example, ‘Out of boxes’ allows you to specify the kind of boxes you need to resolve the issue)

Figure 4. AVA allows you to raise issues and sub issues (for example, ‘Out of boxes’ allows you to specify the kind of boxes you need to resolve the issue)

Conclusion

Amazon Virtual Andon (AVA) is a self-deployable solution that provides you the digital capability to create, route, manage, and resolve issues. With AVA, you can monitor your overall enterprise for issues and engage with the right engineers to resolve them promptly. It offers a clear, intuitive user interface and straightforward workflow to help team members resolve issues.

Get started with Amazon Virtual Andon today.

Categories: Architecture