Is digital twin technology a reality for SMEs?

Trends / Is digital twin technology a reality for SMEs?
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Summary: Digital twin technology is promising for manufacturers, but doesn’t deliver the ROI for SMEs. Cloud PLM is the easy way to make data-driven decisions without over-investing in data management resources and software.

Digital twins have caused a lot of hype in the manufacturing industry.

So we’re going to look at what this buzzword means and its impact on manufacturing.

We’ll also look at whether digital twin technology is worthwhile for SMEs, or if better alternatives exist.

So let’s get started.

What is digital twin technology?

First, let’s break down the term “digital twin”.

The twin component is something like a copy.

You have a physical product, and then you have a virtual replica of it (AKA your digital twin).

Digital twin technology uses sensors, the internet of things (IoT), simulation and analytics to predict how a product will perform in a variety of circumstances.

Digital twins make it possible to test new ideas virtually, instead of on physical products.

Which saves manufacturers time and money since physical prototypes aren’t necessary for every design change.

The allure of digital twins

Digital twin technology promises to streamline product development while saving manufacturers time and money.

And here’s how it lives up to that promise.

Product development

Digital twin technology is a way for engineers to test ideas more efficiently.

Instead of having to build a product to see if a design change is beneficial, the proposed change can be immediately simulated in a variety of environmental contexts, and run hundreds and thousands of simulations almost instantly.

This speeds up product development and reduces materials costs since a physical product doesn’t need to be created for design validation.

Simulation-driven design also ensures higher product quality and mitigates the risk of product recall as it allows designs to be tested in multiple settings.

This is important because it helps avoid incidents like the infamous Samsung Galaxy 7 series that burst into flames during flights because of changes in barometric pressure.

That’s not to say that if Samsung leveraged digital twins more effectively their phones wouldn’t have exploded.

It just means testing that use case is a lot easier when you can test using real product / environmental data, in a simulated environment, incredibly quickly.

Aftermarket services

Digital twin technology helps organizations understand how products perform in the long-term.

By knowing exactly when products begin to deteriorate, businesses can strategically offer aftermarket services when they are needed most.

This includes things like extended warranties, part replacement, and preventive maintenance.

And with aftermarket services 15% more profitable than new equipment sales, digital twins open the door for additional revenue generation throughout a product’s lifecycle.

Digital twin technology opens the door for additional revenue generation throughout the product lifecycle.

Future iterations

Digital twins provide manufacturers with insights into a product’s strengths and weaknesses.

By knowing what works and what doesn’t product teams can turn this information into design changes.

Incorporating real-time data into product design allows teams to make changes that directly better user experience.

And this makes future iterations of a product optimal.

SMEs & digital twin technology

There are many benefits to digital twins, but are the returns worth it for SMEs?

When it comes to implementing and maintaining digital twin technology, even Deloitte warns about the amount of work involved.

The process demands specialized labor, niche software and a large budget.

Not to mention the patience, time, and overhead needed to maintain the thing.

To get started SMEs need:

  • People to interpret the data. A team of data scientists and analysts is required to create actionable insights from the real-time data digital twins use.
  • The necessary software. This includes (at the bare minimum) design, simulation, and analytics programs.
  • The budget to pay for it all. Between salaries and software, you’re looking at hundreds of thousands annually to sustain digital twin technology.

What’s more, a digital twin is like any other tool — it’s only as good as the data you fuel it with and the time you put into it.

And digital twins are a data-hungry proposition.

You need an enormous amount of data embedded in devices to generate an accurate picture of how your product is used in the real world.

The reality is, most SMEs just aren’t there yet when it comes to the sheer volume of data you need.

Digital twin technology costs SMEs hundreds of thousands annually.

The SME Alternative

At this point, the ROI of digital twin technology for SMEs isn’t there.

But thankfully, an alternative exists.

Cloud PLM.

Cloud PLM pushes and pulls data from programs like your CAD, ERP, and PDM to surround each product in a shared version of the truth.

Its flexible APIs allow it to integrate with your organization’s data streams — including the IoT databases that hold the real-time data digital twins capitalize on, if and when you get there.

By marrying product data with real-time results, teams know how products are actually performing and can make data-driven decisions throughout the lifecycle.

Cloud PLM lets team implement data-driven strategies when it comes to thing like:

So while SMEs wait for the ROI of digital twin technology to improve, cloud PLM is a great alternative in the meantime.

Wrap Up

The benefits of digital twin technology are real in the way they improve manufacturing.

But whether or not the technology is a good fit for SMEs is still up for debate.

There’s a gap between the cost of digital twins for SMEs and the benefits they receive.

Especially when alternatives like cloud PLM exist.

Cloud PLM lets SMEs harness the power of real-time data throughout the lifecycle, without having to fork out the hundreds of thousands of dollars digital twin technology requires.

Image Credit: Alessio Lin via Unsplash

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