New Amazon Virtual Andon 3.0 – Automate Issue Resolution via APIs and Predictive Services
AWS Architecture BlogNew Amazon Virtual Andon 3.0 – Automate Issue Resolution via APIs and Predictive Servicesby Ajay Swamy | on15 NOV 2021| inArchitecture,Internet of Things,Manufacturing|Permalink|ShareDeveloping 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 onIndustry 4.0 technologiesdiscusses 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 anAmazon Web Services (AWS) Solutionthat 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 featuresAVA 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 withAmazon Machine Learning (ML)services, such asAmazon Lookout for EquipmentandAmazon 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 APIsThe solution introduces GraphQL APIs viaAWS AppSync, secured throughAWS 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 thecreateIssueAPI 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 automaticallyWith AVA APIs, you can integrate with predictive services like Amazon Lookout for Equipment (L4E). AVA provides anAWS Lambdafunction 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.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 integrationAVA provides the capability to integrate with IoT devices viaAWS IoT Core. You can configure your IoT devices to send data to theava/issuesAWS IoT Core topic. Additionally, AVA can send messages to theava/devicesAWS IoT Core topic toautomatically raise issuesvia 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 dashboardsAVA usesAmazon DynamoDBto store factory configuration and issues data. All AVA data is exported from the DynamoDB database to anAmazon S3bucket via anAWS Glueworkflow. You can then useAmazon Athenato query underlying data and create custom reports using business intelligence (BI) solutions likeAmazon 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 QuickSightArchitecture and workflowFigure 3. AVA 3.0 architectureTheAWS CloudFormationtemplate deploys the following infrastructure, shown in Figure 3:The AWS CloudFormation template provides anAmazon CloudFrontweb interface that deploys into anAmazon Simple Storage Service (Amazon S3)bucket configured for web hosting.AnAmazon Cognitouser pool allows this solution’s administrators to register users and groups using the web interface.AWS AppSyncGraphQL APIsandAWS Amplifypower the web interface.Amazon DynamoDBtables store the factory data.AnAWS IoT rule enginehelps you monitor manufacturing workstations or devices for events. It then routes the event to the correct engineer for resolution in real time.Authorized users can interact with and receive notifications from this solution. AnAWS Lambdafunction andAmazon Simple Notification Service (Amazon SNS)send emails and SMS notifications.Issues created, acknowledged, and closed in the web interface are recorded and updated using AWS AppSync and DynamoDB.The AWS AppSync GraphQL APIs can becalled directlywith HTTP POST requests.If you are using L4E to monitor your machines, enter the name of the Amazon S3 bucket where inference files will be delivered in theAnomaly Detection Output BucketCloudFormation parameter. This solution can beconfiguredto automatically raise issues if an anomaly is detected.When theActivate Glue WorkflowCloudFormation parameter is set to“Yes”, an AWS Glue workflow will be created to extract data from DynamoDB. It delivers this data via anAWS Glue Data Cataloginto Amazon S3. For more information, refer to theData Analysissection.You can use an existing SAML provider as an additional identity provider for access to this solution. You can configure the AmazonCognito Domain Prefix,SAML Provider Name, andSAML Provider Metadata URLCloudFormation parameters. For more information, refer toSAML identity provider.An intuitive UI with nested eventsWith 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 thisprevious 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)ConclusionAmazon 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 withAmazon Virtual Andontoday.TAGS:predictive analyticsAjay SwamyAjay Swamy is Senior Product Lead at AWS Solutions Group. He is responsible for managing a portfolio of AWS Solutions that offers quick, easy to deploy cloud-based solutions for complex technical and business problems. He is based in NYC.
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 […]
Ajay Swamy
Architecture Internet of Things Manufacturing