Starting the digitalisation journey: making the most of the machine

Industry commentators believe that, over time, every machine on every factory floor will have its own digital twin. Some have even been so brazen as to suggest that at least half of large industrial companies will adopt this self-learning technology by 2021.

In this article, Siemens examines what role digital twin technology must play in helping OEMs to meet growing demand, and how this caused one of its customers to reduce their time-to-market by 40%.

Today, when a customer needs a new machine, they need it now. There’s no longer any time for the traditional ‘trial and error’ approach, in which OEMs would create physical prototypes and carry out numerous tests. Testing alone can eat up weeks and months. Then, of course, there’s the often prohibitive cost.

And that’s before we consider the inevitable risk, often exacerbated by misguided management practices. Harvard Business Review has identified six common errors in new product development:

  • Not personalising planning. One size doesn’t fit all
  • Maxing out. High utilisation of resources doesn’t improve performance. Product development is unpredictable, so keep resource in hand
  • Large batches. Big is not beautiful – it’s expensive
  • Hurrying too much. You must keep an eye on ongoing production too
  • Overdoing the complexity. User-friendly means popularity – look at Apple!
  • Being too hard on yourselves. Zero tolerance of failure means taking the line of least risk – not necessarily what clients want

Mass production – or mass customisation?

Henry Ford may demur, but today the name of the game has to be mass customisation.

Mass production is a long-term concept, based on a relatively homogenous product. In a world where customers demand solutions to meet specific, individual needs, and want them yesterday, it’s no longer appropriate.

This means replacing infrastructure designed to support mass-production with a digitalised manufacturing model. And for good reason. A digitalised manufacturing approach provides the flexibility needed to handle the lower volume, short run and limited production cycles mass customised manufacturing dictates.

CROP - Digital Twin - Siemens’ ‘Mindsphere’ IoT operating system can use digital twins to help optimise product development, production management and in-service performance – image courtesy of Siemens.

 Meet the digital twin

Imagine a digital version of the new machine you propose. One that’s identical in every respect, but doesn’t commit you to any of the usual time, expense and risk? Wouldn’t that be great?

You could try as many adaptations as you like and assess the performance of every variable – without risking anything, relatively speaking.

Wishful thinking? Not any more! Meet your digital twin. Or rather, your new product’s digital twin.

A digital twin is a precise, 3D, virtual model of a machine, product or a production plant. In simple terms, it provides a virtual sandbox in which OEMs can design, commission, test and resolve problems in anything from individual machines to complete production lines. Of course, one of the main benefits of this is not having to build expensive prototypes.

Digital twins use data from physical objects to determine real-time performance and operating conditions. The data is analysed and fed back into a virtual environment which enables product development with minimal expense. Fundamentally, a digital twin provides a virtual-physical connection that allows OEMs to analyse how a machine performs under certain conditions in the real world.

By using a digital twin, OEMs can reduce the time needed to create a fully-specified product. Most importantly, it will be a new product that’s proven to work in any combination of real-life operational situations, and backed by a plan for assembly, implementation and maintenance. Every aspect is tried, tested and validated before you even begin to invest time and capital creating the physical product.

Reducing risk

Using a digital twin reduces the cost and risk involved in developing and implementing new machines by decreasing the most time-consuming aspects of building products in the real world. OEMs can carry out a similarly exhaustive range of tests as they would by using traditional methods but without the need for physical prototypes.

For example, the digital twin can be used to assess the potential impact of using machine operational settings, by running ‘what if’ scenarios replicating real-life situations. This allows customers to ‘try before they buy’ by running test scenarios based on a combination of variables.

Want to know more?

A digital twin is an invaluable and realistic investment for even the smallest OEM.

To see a digital twin and hear about its application from peers in the machine building industry, register for your free ticket to Digital Talks 2019.

After the machine has been built, it is connected to its digital twin so that it can be constantly updated with information that would previously have been collected manually.

Then, the digital twin monitors and displays the machine’s performance throughout its entire lifecycle, allowing users to predict behaviours and implement insights from previous design and production experiences. As more advanced lifecycle stages approach, the twin’s talent for obsolescence management comes into its own.

In effect, the digital twin becomes a ‘living’ mirror image of its physical counterpart, which can be used as a testbed for new machines to meet the constantly changing demands of the market. The benefits apply to both OEM and end user alike. It’s truly a way to make the most of the machine.

Adopt a twin of your own

Recent advances in IT, notably artificial intelligence, 3D printing, advanced low-cost sensors and Big Data analytics have put digital twins within reach of all levels of OEM. The convergence of these technologies means you develop your own twin for both new product design and planning.

Here are some simple steps:

  1. Decide what you want the twin to do. You may wish to include customers in your initial brainstorming
  2. Put the organisation in place. Choose just a small group from domain-related interdisciplinary teams
  3. Develop a digital twin company strategy. Make this long term, and easy to understand and execute
  4. Develop Key Performance Indicators to measure the progress on each trajectory

How TrakRap took the waste out of packaging

Digital twins can support greater collaboration throughout the value chain. This includes designers and engineers, and also customer stakeholders who bring vertical industry knowledge to the development project.

And, if a remote stakeholder wants to monitor activity or make an informed contribution based on machine insights, they can – without having to be physically present.

The digital twin can be used by OEMs and customers across the entire product lifecycle, from R&D engineering to operations. But, not every digital twin is created equal, nor does every digital twin provide the quality or accuracy of information needed to support effective machine development.

As Lancashire packaging solutions manufacturer TrakRap discovered, Siemens is the only company to take a holistic approach to the digital twin. Siemens believes that an effective digital twin must encompass all three domains: hardware, electronic and software domains. Any ‘missing’ pieces limit the OEM’s ability to connect information or gain real value from using a digital twin.

The combination and integration of the three digital twins is known as the digital thread. The term ‘thread’ is used because it is woven into data from all stages of the machine’s lifecycle that would previously have been locked into unconnected siloes.

The TrakRap story demonstrates the value of a digital twin in a collaborative machine development project which, in this case, is revolutionising the packaging industry.

The latest chapter in the TrakRap story started when the company created an alternative way of shrink-wrapping individual products, such as tubs of yoghurt. The new orbital wrapping machine was so successful that customers in other sectors of the food and beverage industry were clamouring to use the technology. It was at this point that TrakRap had to return to the virtual drawing board.

Chicken and Beef at the Market - image courtesy of Depositphotos.

From virtual development to operational success

Siemens technology has been used to virtually develop, test and commission TrakRap’s latest machine using a digital twin; a fully-functioning, 3D computer model of the machine.

By using a digital twin and eliminating the physical prototype stage, TrakRap reduced time-to-market by 40% and cut development costs by 30%.

TrakRap’s CEO, Martin Leeming, believes a precedent has been set for the company: “Our digital twin has been really useful in developing the first machine that we’re now building. We know this machine works in a way that is going to deliver exactly what we want.

“We now think of our machine not so much as a physical entity but as a flexible software platform that can adapt to different types of environment, product and set up, enabling us to predict quality, throughput and timescales.”

Martin Leeming will be speaking at:

Digital Talks 2019: Transforming Industry Together 

11 June | ACC Kings Dock, Liverpool 

Siemens Digital Talks 2019 - image courtesy of Siemens. As UK manufacturers, we need to become more competitive. Whether it’s to compete on a global stage, to bring customisation at speed or to be ultra-responsive to your customer when and where it’s needed. To do this we need to transform.

The reality is that digital technology is going to create the most significant and long term productivity improvements that will allow this transformation to unfold.

Digital transformation is a journey of continuous improvement. That’s what we’ve learned; from experience with our customers and partners.

At Siemens’ 2019 flagship event, you can learn what these continuous improvement steps could look like for your business and value chain.

To learn more, register now for your free ticket to Digital Talks 2019