Digital Twin is one of the technologies that is changing the dynamics of the industrial sector. They are virtual replicas of objects or processes that simulate the behavior of their real counterparts. In this new publication of IT GoForMore, we spoke with Soring Hornoiu, Head of Digital platforms & Infrastructure Services of LafargeHolcim EMEA Digital Center, who will explain the influence that this technology has had and will have on the development of the industry.
What is “Digital Twins” and where does this concept come from?
In simple words, a digital twin is the virtual representation of a physical asset, “replicating” the behaviour of the real thing due to the usage of Internet of Things (IoT) sensors that gather data from the physical world and send it to machines to reconstruct in the virtual space.
While the Digital Twins concept gained recognition in 2002, digital twin technology itself has actually been a concept practised since the 1960s.
After the launch of Apollo 13 on April 1970, no one could have predicted it would become a fight for survival as the oxygen tanks exploded early into the mission. It became a famous rescue mission as the world held its breath, with technical issues needing to be resolved from up to 300,000 km away. A key to the rescue mission, however, was that NASA had a digital twin model of Apollo 13 on earth which allowed engineers to test possible solutions from ground level. Of course, systems have now become predominantly virtual rather than physical simulations.
With the concept already being practised for a few decades, the digital twins have been highly familiar since 2002, after the presentation of Michael Grieves first using the terminology. The presentation involved the development of a product lifecycle management centre, containing all the elements familiar with the digital twin: real space, virtual space and the spreading of data and information flow between real and virtual space.
Although the digital twins have been highly familiar since 2002, only as recently as 2017 has it become one of the top strategic technology trends. The Internet of Things enabled digital twins to become cost-effective so they could become as imperative to business as they are today.
Wouldn’t it be extraordinary to simulate plant operation or build what-if scenarios for the products, facilities, and processes you wished to change before you actually put real-world resources behind real-world implementation? That’s the promise of digital twins.
What success stories can be taken as an example of the integration of these technologies in the 4.0 industry?
Successful enterprises are using a full stack of technologies to achieve the goals of Industry 4.0: efficiency, speed, agility, and customer-centricity.
Spurred by market forces, such as worker shortage, customer demands for personalization, and global competition, manufacturers are not only leveraging technologies to differentiate, but also to uncover new business opportunities.
Intelligent use of data is central for Industry 4.0 and with the right technology data can be harnessed and used into context, deliver it in specific and relevant ways, and drive operational efficiency.
One of these technologies is the Digital Twins. In fact, it’s now recognized as a key part of the Industry 4.0 roadmap; a recent study predicted at 30 per cent of G2000 companies will have implemented advanced digital twins to optimize operations by 2020.
One of the primary reasons Digital Twins technology is rapidly being adopted is that there are multiple use cases across the industrial enterprise: engineering, manufacturing and operations, and maintenance and service. Digital twins are made possible (and improved) by a multitude of Industry 4.0 technologies – IoT, AR, CAD, PLM, AI, edge computing, to name a few – to create a powerful tool that’s driving business value.
Visualization for Data & Analytics
The technology associated with Industry 4.0 produces or requires a tremendous amount of data.
Key to the success of Industry 4.0 is using these data to drive improvements and find efficiencies across the value chain. For this purpose, the Digital Twin is a highly effective instrument to deliver data and insights in context, in a consumable and actionable format.
With a Digital Twins, engineering and design teams are analyzing real-world data within the context of physics-based engineering simulations, resulting in insights into how the product is being used and user experience.
Whirlpool, for example, is using this type of Digital Twins to test new innovations with minimal investment. As a result, is accelerating innovation and getting products to market faster.
Many businesses struggle with lack of transparency across their value chain. These operations are often driven by disconnected and disparate information systems.
Increasingly, enterprises are looking to gain greater visibility into their operations through the implementation of the digital thread, a single set of related data along the entire product lifecycle, from design inception to customer service. This single source of truth presents myriad opportunities for a Digital Twins to mirror a product or a process.
Using Digital Twins, through simulations or analysis of patterns within the data, enterprises are uncovering ways to optimize upstream and downstream operations.
GE is using Digital Twins as a” replica” of Power Plant in their Predix Platform.
As the plant is operated, the Digital Twins continually improves its ability to model and track the state of the plant. The Digital Twins allows plant operators to optimize the instantaneous and transient control of the plant for efficiency or performance, make informed decisions regarding performance versus part life, assign loads and lineups through time, and perform the right maintenance tasks at the ideal time.
Companies use Digital Twins technology for many reasons including also for employees training – Virtual / Augmented Reality technology on top of the “digital replica” of the equipments and processes.
What will be the future of this technology and its influence on what is already known as the fourth industrial revolution?
There is a general consensus in Cement industry regarding the main direction where we must focus in order to remain competitive:
- Analytics-Driven Predictive Maintenance
- Optimization via Digital Twin
- Predictive Quality Analytics
- Alternative Fuel Optimization
Technology as IIoT, Machine Learning- AI or Augmented / Virtual Reality became more accessible and will play a key role in our ambition is to create digital, circular and interconnected plants.
How does LafargeHolcim EMEA Digital Center use this technology in the development and conceptualization of its product and services?
A year ago, business in LafargeHolcim began blueprinting the “Plants of Tomorrow” initiative, that enable us to shift from machine focused operations to an end-to-end operating model that identifies the most effective process flows between materials, products and customers.
EMEA Digital Center is engaged in this journey, with the focus on improving our skills in the field of IIoT, Machine Learning and Augmented Reality and validating the way that these technologies must be integrated in our existing landscape.
As our motto is: “Learning by doing”, we initiated a PoC (5 weeks duration) with the goal to create a Digital Twin for a (relatively complex) Cement equipment. This is a joint exercise with business functions.
At the end of this exercise we would like to validate:
- The concept of Cement Plant integration (IIoT) and computing data (including Machine Learning models) at EDGE and in the Cloud.
- Capability to have a plant integrated in less than 5 days, respecting all LafargeHolcim security standard.
- The procedure and technology to define the analytic models representing the physical assets and processes
- Operating model of such landscape and capabilities to scale
This will be our contribution in the general effort to digitize our Cement plants and transform our current cement manufacturing operating model with effect in reducing operating costs, significantly increasing workforce productivity, and improving safety and working conditions.