Visualizing Health Metrics Data from Legacy Assets Using AWS IoT SiteWise and Urban.io
By Rob Cummings, CEO – Urban.io PTY LTD
By Vanitha Ramaswami and Thomas Cummins PhD, IoT Partner Solution Architects – AWS
By Desislava Hubanova, Technical Lead – Urban.io PTY LTD
By Lilyana Popova, Head of Software Development – Urban.io PTY LTD
Industrial organizations rely on high-value (core) machinery such as processing plant crushers and conveyors for their factory operations.
These assets are predominantly instrumented with their own control and automation systems. This automates their operation and monitors the status of the asset to ensure they are running optimally.
In these same factories, there are secondary (non-core) assets such as motors, pumps, and generators located on the periphery of customer sites.
Many secondary assets are physically isolated, disconnected, and legacy in nature, making it uneconomical to connect them into central operational systems using traditional wired sensor technologies.
This leaves the assets functioning without constant supervision, exposing that organization to potential productivity loss, safety risks, or resultant damage if they fail.
Urban.io’s Asset Monitoring Data Subscription solution removes the technical challenges typically required to connect these hard-to-reach assets within factories.
This Industrial Internet of Things (IIoT) solution combines sensor and gateway hardware for data collection with AWS IoT SiteWise—a fully managed industrial data analytics service—to make it easy to process data from the assets and determine the condition of key equipment and processes.
Raw sensor parameters, as well as computed KPIs, are available in near real-time on dashboards built and hosted within the AWS IoT SiteWise service.
In this post, we will explain how to gain situational awareness over the health of secondary (non-core), peripheral assets in a cost-effective way using wireless IoT sensors and analytics tools in a subscription-based pricing model.
Challenges with Legacy Assets
Advanced analytics software applications are available to transform data from industrial assets into actionable insights that business operators can use to increase productivity of their assets.
Cost-effective artificial intelligence (AI) and machine learning (ML) technologies are accessible and powerful, enabling software developers to build powerful industrial analytics software applications.
These advanced software applications are the primary drivers of digital transformation for industrial companies, and the data that feeds these applications is more valuable than ever.
However, one of the primary challenges in pursuing digital transformation is the efficient acquisition of raw data from the industrial assets themselves. Since the industrial assets are often physically isolated and not connected to any wired or wireless network, the cost of adding connectivity to the asset exceeds the value the data would yield.
For example, the cost of hiring a systems integrator to build and install a custom remote sensing solution that transmits industrial asset data over a wired/wireless connection may be more expensive than any potential productivity gain enabled by analyzing the data produced by the asset.
This is a fundamental dilemma when considering the digitization of existing legacy/brownfield assets. So, while operators can try to extract more value from this data in order to warrant the cost of acquiring it from disconnected assets, significantly lowering the cost of data acquisition is a more efficient approach.
New technological solutions can be combined with new business models for IoT solution deployments to enable digitization of industrial assets without any CapEx and sufficiently low OpEx so the value of the data exceeds the cost of its acquisition. Urban.io uses this “IIoT Network-as-a-Service” business model for its Asset Monitoring Data Subscription solution.
Traditionally, the process of designing, building, and deploying a complete or “edge-to-outcome” IIoT solution is complicated by the multi-disciplinary expertise required to build a solution that involves sourcing or integrating hardware and software components from multiple third parties.
The result of this complication is increased costs and delays, which negatively impact the customer. Urban.io is a full-stack IIoT solution provider that is born in the cloud with an advanced Amazon Web Services (AWS) cloud development skillset.
Urban.io offers its edge-to-outcome Asset Monitoring Data Subscription solution to enable customers to efficiently acquire data from hard-to-reach locations. This solution is a unique combination of sensors that are easy to retrofit onto existing assets with a backend software-as-a-service (SaaS) platform.
The Urban.io solution makes device onboarding easy and streaming data into a customer’s AWS IoT SiteWise service more simple.
One of the primary operational challenges in brownfield asset monitoring is the assets cannot be shut down to allow the installation of retrofit sensor hardware. These legacy assets are in production, and scheduling downtime is challenging for operators. Therefore, any data acquisition solution needs to have a minimally invasive, low-touch deployment to reduce the installation and commissioning time of the sensors and gateways.
The Urban.io solution includes sensors that can be installed and then onboarded with a simple mobile application. Once devices are onboarded and the user configures the Urban.io platform to connect with their AWS IoT SiteWise service, the asset data starts streaming.
Urban.io’s Edge-to-Outcome Solution Offering
Urban.io’s Asset Monitoring Data Subscription solution includes IP67-rated industrial grade wireless monitoring sensors that are general purpose and can be installed on a wide range of assets for secondary sensing applications.
Secondary sensing is a technique to add new sensors to existing equipment without causing any production downtime. It’s a convenient way to add the capability to monitor assets to predict failures on existing brownfield legacy assets which are already deployed in the field.
There are around 16 different types of sensors covering nearly all of the most critical industrial asset monitoring use cases, including vibration and temperature monitoring of high value assets. Acquiring these new data sources enables operators to identify when specific sensor values are departing from normal/safe ranges and take pre-emptive action.
Operators, with this new data in hand, can analyze the aberrant asset behavior, perform a root cause analysis of the problem, and take necessary action to prevent a catastrophic asset failure. Without this data, operators have no insight into asset health and are not able to predict costly asset failures.
Figure 1 – Urban.io sensors kit.
Urban.io’s solution includes physical hardware as well as a cloud software component running on AWS. The hardware component includes sensors that are retrofitted on the assets themselves, as well as a wireless gateway device that operates long-range encrypted private wireless networks.
The gateway establishes an encrypted connection to the fully managed Urban.io SaaS platform running on AWS.
Next, Urban.io provisions all of the sensor metadata into AWS IoT SiteWise running in the customer’s AWS account. Once the industrial assets are modeled within AWS IoT SiteWise, the telemetry data automatically starts streaming to its managed time-series database.
With data in AWS IoT SiteWise, customers can build sophisticated data processing applications that transform raw sensor readings into actionable insights, such as KPIs used for asset failure predictions. Operations teams can act upon these insights and KPIs to service assets before catastrophic equipment failure occurs.
The Urban.io gateway devices can be deployed onto a site such as an oil and gas well site, manufacturing plants, or other buildings in less than one hour, and function completely independently from existing IT infrastructure such as a private local area network (LAN).
By supporting an independent, secure wireless network, the Urban.io solution effectively expedites the process of connecting remote assets. This enables operations teams to bypass the often complex processes required for deploying enterprise IT network infrastructure.
Figure 2 – Indoor Gateway – 500m range (left); Outdoor gateway – 5km range (middle); One-click device onboarding through mobile app (right).
As a turnkey solution, Urban.io enables rapid commissioning of sensors via its mobile-first SaaS device administration application.
Urban.io sensor devices automatically discover and connect with Urban.io gateways; each sensor device has a QR code and Nearfield Communication (NFC) tag that enables a one-click onboarding process. Users are able to configure sensor devices using the application and have data flowing to the cloud for analysis and display on dashboards in less than a minute.
The combination of dynamic network discovery and automatic configuration removes the requirement for skilled technical installation staff and specialized installation equipment. It also empowers any operations team responsible for asset maintenance to rapidly deploy their own remote monitoring solution.
Industrial Use Case: Bucket Elevator Condition Monitoring
Figure 3 – Bucket elevator in manufacturing and processing facilities with manual operations.
Bucket elevators are used in many manufacturing and processing facilities to transport raw materials (ore, grain, flour) from the bottom to the top of a gravity-fed process. Bucket elevators commonly transport materials that generate dust; these dust clouds are often combustible or flammable, posing a major safety risk.
Figure 4 – Bucket elevator in manufacturing and processing facilities retrofitted with Urban.io IoT sensors.
A bucket elevator has multiple mechanical components that wear over time, such as bearings and drive belts. As these components deteriorate, friction increases at the rotating contact surfaces and, consequently, generates heat which can ultimately ignite the flammable dust.
Bucket elevators are typically located in remote locations of a facility such as roofs and crawl spaces, and these are inherently difficult for maintenance teams to inspect.
Figure 7 – Urban.io IoT sensors retrofitted in hard-to-reach locations, enabling remote operations.
Legacy equipment in a facility’s difficult-to-reach locations is extremely expensive to retrofit with wired sensing equipment. As a result, it’s often deemed to be economically unviable to monitor them. This leaves multiple points in a facility at risk of fire or even explosion.
Using a combination of vibration and temperature sensors, Urban.io’s Asset Monitoring Data Subscription solution enables operations teams to install a safety monitoring solution onto a bucket elevator in less than one hour. This retrofit installation does not interrupt production and provides invaluable data to operations and maintenance teams.
Urban.io’s AWS Solution
Operation teams manage the Urban.io sensors and gateways via Urban.io’s SaaS platform. Meanwhile, data is ingested into AWS IoT SiteWise for operational asset KPI metric calculation and visualization.
Figure 6 – Urban.io AWS solution architecture (SaaS platform and sensor data extended to client AWS account).
Urban.io’s cloud-native IoT device administration platform provides a simple means to onboard sensor devices deployed at a customer site and begin ingesting telemetry data.
To bring this sensor data into an AWS IoT SiteWise service, customers can launch the Urban.io for AWS IoT SiteWise Quick Start in their own AWS account.
Once the Quick Start is launched and its AWS CloudFormation stack is running, the Asset Model Converter (AMC) within the Quick Start runs and dynamically translates the structure of the wireless Urban.io network into a SiteWise Asset Hierarchy “on-the-fly” with zero coding or configuration required by the user.
This is a one-time asset metadata synchronization process between the Urban.io platform and AWS IoT SiteWise. Once this metadata synchronization process completes, the Urban.io platform then streams telemetry data into AWS IoT SiteWise via MQTT messages through the rule actions within AWS IoT Core in the users own AWS account.
This cross-account publishing is how the telemetry data gets from the Urban.io platform into the customer’s AWS account. In this way, device measurements are updated in near real-time for the asset properties of AWS IoT SiteWise assets. The Urban.io platform handles any subsequent change to the asset inventory by synchronizing the sensor metadata with AWS IoT SiteWise.
This solution ensures the deployed wireless sensor metadata remains synchronized with the asset structures within AWS IoT SiteWise.
Figure 7 – Visualization of bucket elevator bearings data in SiteWise dashboard.
AWS IoT SiteWise is a managed service that makes it easy to ingest, store, organize, analyze, and monitor data from industrial equipment and machines at scale. It helps customers to make better data-driven decisions to optimize operations, and improve productivity and availability.
Figure 8 – Identifying bearing wear as a cause of friction and potential ignition.
To extract value from the IoT data and generate near real-time insights, it’s essential to integrate the IoT data with data from other line of business systems. This requires modelling the industrial assets in AWS IoT SiteWise and adding context to the IoT data from other line of business systems.
AWS IoT SiteWise offers a flexible asset modeling capability. Asset models are declarative structures that define the individual sensor data streams, data processing capabilities, and hierarchical relationships of your assets. Asset models enforce consistent data models across multiple assets of the same type.
Optionally, AWS IoT SiteWise project owners can configure alarms for the sensor data to alert operations team when equipment or process sensor values or KPIs are sub-optimal.
To visualize sensor and asset data, AWS IoT SiteWise includes AWS IoT SiteWise Monitor. This feature gives users a no-code method to build dashboards within a managed web application.
With AWS IoT SiteWise Monitor, you can browse your library of assets to investigate particular asset properties (these are the same as the sensor data streams from Urban.io). Users can also create and share operational dashboards with any number of users for near real-time asset monitoring and visualization including visualizing performance, quality, and availability KPIs.
In AWS IoT SiteWise, project owners (administrators) can build operational dashboards in minutes via a drag-and-drop user interface (UI). These dashboards can include metrics that operators want to observe in near real-time using a variety of widget types (line charts, bar charts, scatter charts, status charts, status grids and KPI metric displays). The dashboards also augment them with trend lines or color changes when a threshold is breached.
Figure 9 – Set up no code dashboard with AWS IoT SiteWise for operations team within 24 hours.
Urban.io’s Asset Monitoring Data Subscription solution comes with unlimited hardware replacement warranties for the life of the subscription, and an unlimited network connectivity SLA to provide visibility on the health of legacy assets deployed.
AWS IoT SiteWise makes it easier to visualize the data and provides visibility into legacy assets through secondary sensing. This allows you to focus on your business applications and not have to worry about the complex wireless network requirements in the field or data ingestion to cloud.
The AWS IoT SiteWise integration makes it possible to have a unified Industrial IoT analytics platform, and makes it easier to integrate other industrial data sources from factory facilities. This helps maintenance personnel avoid unplanned downtime and improve productivity.
Urban.io – AWS Partner Spotlight
Urban.io is an AWS Partner that provides low cost, industrial grade IoT devices that help building owners and tenants optimize systems and spaces.
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