In a Galaxy Far, Far Away...
Apollo 13 crew are fighting for survival as their oxygen tanks prematurely explode early in the mission. The world holds its breath as one of the most famous rescue missions unfolds. The new mission: fix life-threatening trouble 320,000 kilometres away in space. But it’s never been done before. Key to the rescue mission: NASA’s digital twin, allowing engineers to test solutions on Apollo 13 from Houston.
Real-time diagnosis of mission critical equipment located a thousand miles away on a remote outback mine from the comfort of air-conditioned offices in the CBD.
Thousands of sensors: sight, sound, vibration and altitude means you can ‘twin’ anything from anywhere for unprecedented clarity and control over visualisation.
Digital twins enable:
- Remote Monitoring
- Optimise Maintenance Schedules
- Real-Time Assessments and Troubleshooting
- VR Simulations for Technical Support
- Staff Training and Onboarding
See Around the Corner
Smarter, more accurate decision making with the power of foresight through predictive modelling so you can proactively respond to anomalies before they impact your business.
What is a Digital Twin?
A digital replica, a virtual model of a physical (real-world) thing.
That “thing” can be a process, product or service; be it a building, a vehicle, a train line network, or an entire city.
Our very own James Litjens built a digital twin of his home whilst in Covid lockdown.
See the full story here
4 Steps To Your Digital Twin
ARQ’s proprietary process to creating your bespoke digital twin happens in our 4 step methodology:
Identify The Ecosystem
Process mine your operations.
Research and recommend optimisations.
Journey map data flows and interactions between the physical and virtual.
Source the IoT you’ll need.
Map your twin strategy. Unlock new capabilities.
Connecting The Ecosystem
Secure your cloud platform.
Centralise your controls.
Modular configuration so new physical sites can be added without impact to back end services.
Serverless deployment means no infrastructure to maintain. Pay only for what you use.
Edge computing: real-time response and immediate action to events.
Visualise and Impact The Ecosystem
Design your service, placing data and cognitive insights into your people, products and processes.
Identity specific user and task workflows.
Machine learning increases real-time efficiencies, monitoring and optimising response times.
Dashboard transparency of system status in real-time, accessed from anywhere.
Real-time monitoring displays unique data for each user.
End-point heartbeats measure health status.
Searchable log history for detailed analysis.
Prediction and Forecasting
Predictive maintenance monitors real-time sensors to build a cost-benefit maintenance schedule.
Anomaly detection in fleet vehicles identifies non-maintenance related issues.
Near-time schedule optimisation through machine learning (ML). Unforeseen events happen, ML automatically recalibrate schedules and forecasts.
We build rich physical models of equipment and systems for scenario planning and simulation, augmenting your data driven forecasting. Predictive system testing at scale.
Manufacturers simulate machinery (yet built) by replicating real-world physics (and wear and tear) to determine which parts would likely fail first, and when. This opens-up a world of preventative maintenance intelligence helping avoid costly downtime for industries such as mining.
Hospitals track infection agents via real-time epidemiology data identifying who is at risk by contact. Patient organs digital twins allow doctors to test different care delivery approaches and prevent conditions that are years apart, enabling patient-specific surgery training to prepare for complex invasive procedures.
Data collection detects deviations in normal farming practice. Dairy monitors on cattle detect heat and health analysis, visualising dairy production inconsistencies, enabling action plans to correct diary flow.
In times of natural disasters like hail or floods, digital twins provide real-time information on flood levels and hail damage in precise locations. Predictive modelling alerts the infrastructure in jeopardy, allowing immediate action by deploying resources exactly when and where needed.
Book a Free Digital Twins consultation today
Digital Twins: Industry 4.0
The next big thing in the Fourth Industrial Revolution is here: Digital Twins – powering the development of new products, processes and the optimisation of existing, enabling:
- Proactive Planning
- Operational Efficiencies
- Reduced Costs
Finding a Grain of Rice in a Big City
Woolworths Smart Deliveries
Woolworths smart delivery platform allows real time tracking of orders, trucks and baskets through a combination of physical sensors, smartphone apps for drivers, intelligent middleware, and a visualisation dashboard for Customer Support Agents.
Finding a grain of rice delivered across any big city in Australia is child’s play with digital twins for logistics.
Posties See the Unseen
Virtual Reality, Alexa and the Unreal Gaming Engine
Providing address intel for improved CX and delivery optimisation
A proof of concept (PoC) explored in partnership with Australia Post using VR, Amazon’s Alexa and the Unreal gaming engine.
The PoC: create a digital twin environment for Posties to capture and surface important information along their delivery routes, including customer preferences like: safe to leave parcel unattended, locked gate, and protective dog.
Global Mining Giant
(We'd love to tell you who, but we signed an NDA)
Methane release means downtime, and downtime costs millions when you’re one of the world’s largest mining companies. The mission: investigate factors leading to methane release to reduce downtime. By creating a digital twin we unified data assets, consolidated and cross-linked geospatial and operational mine data. The outcome? Significant reduction in unplanned downtime resulting in substantial ROI.
In an open cut mine, efficiency improvements of a shovel-truck circuit can lead to significant ROI. ARQ implemented a new way to model circuit operations, based on cross-linking disparate vehicle, shift, sensor and operational data, resulting in improvements in circuit efficiency and supervisor decision making.