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What Challenges do Digital Twin Solve? How the Twin Can Be Your Aspirin

What challenges do digital twin solve

Interscale Content Hub – Digital twins can help Australian industries avoid common problems like downtime, design issues and supply chain disruptions. But, what challenges do digital twin solve?

Digital twin technology is already being used on projects across Australia.

It is being used to save energy in the Sydney Opera House and to make construction processes more efficient on the West Gate Tunnel Project.

So, knowing how digital twins can help is about how you can stay competitive in today’s fast-paced AEC landscape.

Challenges Addressed by Digital Twin Technology

Predictive Maintenance and Downtime Reduction

Unexpected breakdowns can be a real money-spinner, especially in sectors like manufacturing, energy and transportation.

Digital twins, as the team at Nature Computational Science point out in their piece on “The increasing potential and challenges of digital twins,” are a great way to make predictive maintenance a reality.

By keeping an eye on the data from sensors in physical assets, these virtual copies can spot irregularities and predict potential failures before they happen.

This means you can do maintenance before something goes wrong, which cuts down on downtime and makes everything run more smoothly.

Take the mining industry, for example. It’s a major contributor to the Australian economy, and digital twins are being used to monitor the health of heavy machinery.

By looking at data on things like vibrations, temperature and other parameters, you can spot potential issues early on, stopping costly breakdowns and making sure your workers are safe.

The great news is that Deloitte says in “Predictive maintenance and the smart factory” that predictive maintenance can cut inventory carrying costs by 5-20% and maintenance planning time by 20-50%.

Design and Prototyping

The design and prototyping stage of product development can be really time-consuming and expensive. 

Rafael da Silva Mendonç and colleagues talk about digital twins in their paper, “Digital Twin Applications: A Survey of Recent Advances and Challenges.” 

For da Silva Mendonç et al., using digital twins is transforming this process.

Engineers can create virtual prototypes and test them out in different situations to see how they work, find out where there are problems with the design and make them work better before they build the real thing.

And it doesn’t just speed up the development process, it also means we can create more reliable and efficient products.

A study in Nature Computational Science found the use of digital twins in product design helps to improve outcomes by allowing for testing of different scenarios and design configurations in a virtual environment.

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These digital twins become a real turning point for sectors like automotive and aerospace, where precision and safety are key.

As a starting point, you can readDigital Twins Technology in Manufacturing: The Most Efficient of Them All,” to get an idea of how useful digital twins can be in manufacturing.

Operational Efficiency and Optimization

Digital twins give us a live view of how complex systems work, so we can keep an eye on them and make improvements as we go along.

This is especially useful in industries like manufacturing, logistics, and energy, where even small improvements in efficiency can make a big difference to the bottom line.

For instance, a digital twin of a manufacturing plant can monitor production rates, spot bottlenecks and tweak production schedules.

This can mean more throughput, less waste, and better overall efficiency.

In Australia, where we have huge transport networks, digital twins can be used to make sure traffic flows smoothly, cut down on congestion and make logistics more efficient.

Quality Control and Assurance

Keeping an eye on things in real time helps us make sure we’re producing top-quality stuff and fixes any problems quickly.

Consequently,  we don’t waste time and resources on rework.

This means you can step in and make corrections right away, stopping defects and making sure the products are up to scratch.

This digital twins approach is especially useful in industries with high-quality standards, like pharmaceuticals, food processing, and aerospace.

Take the food processing industry, for instance. Digital twins can keep an eye on things like temperature and humidity to make sure everything’s up to food safety standards.

Any issues can be spotted straight away and fixed, stopping contamination and making sure consumers are safe.

Supply Chain Management

During the COVID-19 pandemic, we saw how vulnerable global supply chains can be.

The U.S. Office of Research Facilities in “Digital Twins Part 2: Enabling Technologies and Challenges,” offers a way to reduce the risks of digital twins by providing real-time visibility into inventory levels, production schedules, and transportation logistics.

By running different scenarios through a digital twin, businesses can spot potential problems and implement plans to ensure smooth operation.

For Australian businesses with global supply chains, digital twins could be a real game-changer.

Digital twins can help businesses predict delays due to things like port congestion, weather events or other unexpected issues.

This means they can adjust their operations and keep their customers as up to date as possible.

Energy Management and Sustainability

As the world faces up to the challenges of climate change, energy management and sustainability are high on the agenda.  Digital twins are becoming a pretty powerful tool in this area.

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By modelling how energy is used and testing out different ways to save energy, businesses can spot ways to improve and cut their carbon footprint.

Digital twins can look at how energy is used and suggest ways to make improvements, which helps businesses to be more sustainable.

For example, digital twins can help cut energy use by making sure different systems in a building are working as efficiently as possible.

Safety and Risk Management

The great thing about digital twins is you can test safety measures in a virtual environment, so companies can get ahead of potential problems before they affect the real thing. 

In industries like construction and oil and gas, digital twins help spot potential problems and put plans in place to avoid them.

For instance, a digital twin of a mine can simulate emergency situations like fires or collapses, allowing operators to test evacuation procedures and identify potential safety hazards.

As you can see, there are a lot of challenges to overcome, right? Just to flag, the challenges you read about could still increase.

If you want to get a feel for the kind of challenges you might face in a project, you can read the review of digital twins challenges on Quora.

For that reason, ensuring everything is implemented correctly is a big part of getting your project up and running. Now, how do we do that?

Implementing Digital Twin Technology

One of the main hurdles in rolling out digital twins is getting all that data from different sources to work together seamlessly.

As da Silva Mendonç points out, this data can come from sensors, SCADA systems, historical records, and other sources.

So, it’s pretty important to get all this data into a format that’s easy to use and reliable.

Also, to get digital twins up and running successfully, you need to bring together lots of different advanced technologies, including AI, machine learning and cloud computing.

It’s also worth mentioning that creating an accurate and reliable digital twin model is a pretty complex task that requires expertise in various areas, including engineering, physics, and data science.

The model needs to accurately represent how the physical asset behaves and what it’s made of.

It also needs to be checked and adjusted regularly against real-world data to make sure it’s still accurate.

That’s why it’s crucial to keep making improvements and to keep stakeholders involved if digital twins are going to stay effective and relevant.

This means regularly updating the digital twin models with new data and feedback from users.

All of this means that the initial investment in hardware, software and staff can be pretty high, and then there’s the ongoing maintenance and updates to think about as well, which can add to the overall cost.

That’s why it’s a good idea to start with pilot projects on critical assets when you’re implementing digital twin technology.

READ  Digital Twin Technology in Manufacturing: Applications, Benefits, Challenges, & Limitations

These pilot projects are a great way for companies to test the waters and get a feel for what digital twins can do.

They also help companies build a solid foundation for predictive models and understand the ins and outs of implementing digital twins. 

The Nature Computational Science shows how starting small and scaling up based on the results of pilot projects helps to reduce risks and make sure that deployment is more manageable.

When all is said and done, implementing digital twin technology means a change in mindset and culture within an organisation.

It’ll involve different departments, like engineering, IT, and operations, working together, and it might mean making changes to existing processes and workflows.

This means you need to encourage your company to be innovative and to work together.

If you need a Python technical reference, kindly checkHow to Build a Digital Twin in Python: Roadmap to Python-Powered Project.”

Future Trends and Innovations

The future of digital twins looks bright, with new developments in AI and machine learning set to boost their potential.

We can look forward to more advanced simulations, combining with augmented reality (AR) for a more immersive experience, and seeing them used in new areas like healthcare and retail.

As data analytics gets better and better, businesses will be able to make better decisions and come up with new ideas.

A study published in Nature Computational Science says the combination of AI and machine learning with digital twins will let us create more precise and adaptive simulations.

This means you will open the door to new possibilities for predictive analytics and operational optimisation.

How to Set Up a Support System for Digital Twins?

When you’re looking at what digital twins can do, it’s important to understand the challenges of putting them in place and managing them.

Many businesses struggle with the initial setup and ongoing maintenance of digital twin systems. 

That’s why Interscale provide customized solutions to help you overcome these challenges.

Our team of experts can walk you through every step of the process, from data collection and integration to model development and analysis.

We can also help your team learn to use the digital twin to achieve the desired results.

What does that mean for your business?

That means we’ll be there to support you, helping you work more efficiently, make better decisions and bring new ideas to market faster.

Don’t hesitate to drop us a line to arrange a meeting. We’re here for you 24/7.

Alternatively, if you’re looking for a quick start, you can visit and read some basic info on our Interscale BIM Management Support page here.

In Closing

Digital twins are changing the game for industries across Australia, tackling the big issues head-on. 

They’re also helping businesses become more sustainable by making sure they’re using energy wisely and reducing their impact on the environment. 

So, what challenges do digital twins solve? The list is pretty long, including ways to help your business grow.