Integrating OPC UA Machine Events into the Amazon Virtual Andon Solution

Introduction

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In today’s tech landscape, discussions around microservices and system integration are prevalent. However, on the shop floor, a variety of protocols from different machine vendors complicate matters. Even with a well-established protocol, implementing adapters to unify data formats is often necessary.

This blog explores how we can simplify data extraction through standards that modern machine vendors are adopting. One such standard is umati (universal machine technology interface), designed to enhance connectivity and data exchange for any machine that adheres to this interface. We will illustrate how this can be incorporated into a cloud framework to monitor machine status, a frequent request from our users.

Monitoring machine status and integrating it into contemporary communication systems—like virtual andons, mobile notifications, and data lakes for historical insights—are crucial first steps toward establishing a data-driven manufacturing environment. The response to this data varies depending on specific use cases. Fortunately, AWS offers an array of technologies to facilitate this. For instance, by sending data to AWS IoT Core, which allows connection of billions of IoT devices and routing of trillions of messages to AWS services without the need for infrastructure management, you can easily trigger mobile push notifications when certain conditions are met. Furthermore, for advanced analytics, this data can be forwarded to Amazon Simple Storage Service (Amazon S3) using Amazon Kinesis Data Firehose, enabling the reliable loading of near-real-time streams into data lakes, warehouses, and analytics services.

Typically, initial monitoring of machines is conducted via an Andon solution—an AWS tool designed to alert operators about quality or process issues. The AWS Solutions Implementation, Amazon Virtual Andon, provides a scalable system to optimize processes, support predictive maintenance, and avert future equipment problems. It features customizable front-end dashboards and workflows for engineers and operators, and it can seamlessly integrate with other systems like ticketing and ERP solutions.

Let’s examine how we can automatically detect machines on the shop floor that comply with the umati standard based on Open Platform Communications Unified Architecture (OPC UA), and integrate the alarms and event interfaces into Amazon Virtual Andon for smooth data exchange.

Understanding OPC UA Events

The OPC UA standard allows equipment to publish events and conditions, effectively communicating state changes. Defined in part 9 of the OPC UA specification, it is especially useful for events not reliant on sensor data. Conditions like a jammed motor can be visualized on a human-machine interface or further processed to trigger alerts or maintenance tickets, as we will demonstrate here.

Introducing umati

While OPC UA events contain metadata, such as severity and event type, they often lack contextual information needed to respond appropriately. Additional details about the originating machine or system are crucial for determining how to handle an event. The umati companion specification standardizes the discovery of machine information using OPC UA while also defining a standard event model applicable to all machines that follow this standard, enabling seamless communication with other systems without manual integration.

Connecting Machine Events to Amazon Virtual Andon

How can we utilize the capabilities provided by standardization efforts like the umati companion specification to seamlessly integrate shop floor machines with a cloud-based solution like Amazon Virtual Andon?

The architecture for this integration is illustrated in the accompanying diagram. On one side, there’s an umati-compatible OPC UA server that provides alarms and conditions from one or multiple machine tools. On the opposite side, the plant operations teams and the company’s IT systems, such as ticketing or ERP systems, are depicted.

The process of extracting alarm and condition data from the umati server and delivering it to a cloud solution that responds to events in near real-time can be broken down into three main components:

1. Discovery of machine tool inventory from the shop floor using umati
2. Subscription to relevant machine events (alarms and conditions) through OPC UA
3. Processing and delivering the events to Amazon Virtual Andon

This architecture primarily relies on two AWS services in addition to Amazon Virtual Andon:

• AWS IoT Core: A managed cloud environment that enables secure interactions between connected devices and cloud applications.
• AWS IoT Greengrass: An open-source edge runtime and cloud service for building, deploying, and managing device software.

For this discussion, we will commence with the umati server and trace our data pipeline through each stage until it reaches the plant operations teams and IT systems. To interact with physical machines on the shop floor, a local gateway device, typically an industrial PC, is necessary to access the local network.

The architecture diagram illustrates this industrial PC on the left as an AWS IoT Greengrass core device. While using the AWS IoT Greengrass Core software isn’t mandatory to register a device with AWS IoT or facilitate information exchange, it streamlines the process by bundling AWS IoT functionalities into a user-friendly command line interface.

Software on a connected device managed by AWS IoT Greengrass is referred to as a Greengrass component. Our sample implementation, depicted in the diagram, consists of three such components. The discovery process is managed by UMATIInventory and UMATIDiscover.

UMATIInventory is tasked with accurately displaying a complete inventory of umati-compatible machines within a local factory network. This inventory is accessible in an AWS IoT Device Shadow, which helps in managing machine tool metadata and correlating incoming events with specific machines or stations on the shop floor. This contextual information aids operators in associating events with detailed resolution instructions or understanding their downstream impact.

UMATIDiscover supplies the inventory information to UMATIInventory. Periodically, this component scans the local factory network (or specific IP addresses that can be configured) for OPC UA servers. Each server identified is then scanned for umati-compatible machines. Given that the representation of these machines in the OPC UA server is standardized, the component can uniformly structure all machines’ data, typically in JSON format.

Generally, communication between components takes place through AWS IoT Greengrass’s local interprocess communication capabilities.

Subscription

Once the machine inventory in AWS IoT Core is established, event data can be extracted from the identified machines. This process involves subscribing to the relevant OPC UA events. For more insights on this topic, you may find this blog post helpful: Amazon VGT2 Las Vegas.

In conclusion, integrating OPC UA machine events into the Amazon Virtual Andon solution streamlines operations and enhances data-driven decision-making in manufacturing environments. For additional authoritative insights, check out chvnci.com.

For a deeper understanding of potential pitfalls and best practices, refer to this excellent resource: LinkedIn Post by Alex Simmons.