5 reasons you need digital twins to accelerate sustainability goals

Digital twins of factory

Heavy industries will have a crucial role to play in reaching net zero objectives as it is the second largest global producer of carbon emissions after the energy sector. As per IEA, nearly 60% of total industrial energy consumption and around 70% of CO2 emissions from the industry sector come from three heavy industries: Chemicals, Steel, and Cement.

Heavy Industry emitting high carbon

In 2020, China accounted for more than 60% of the world’s production of cement and steel combined. The biggest challenge from a sustainability standpoint is to continue producing these business-critical materials without generating excess carbon.

With the planet in distress, businesses across industries have announced that they will reduce their carbon footprints to “net zero” in the coming decades. Industries, including energy, oil and gas, and others, have established sustainability targets as a routine procedure. A growing number of companies, including C-suite executives and investment professionals, believe that ESG programs will contribute more shareholder value in the near future and in the long term.

Digital twins – much more than virtual replica

As per Gartner, the digital twin market will reach $183 billion by 2031. With the convergence of our physical and digital worlds, digital twins are set to play a major role in solving the plethora of sustainability issues.

The most essential element of a digital twin is its source of information – relevant and accurate data. AI-driven digital twins make use of operational data and process information to show a clear picture, that can aid in business decision-making.

More than just showing the virtual representation of the physical world, digital twins can help with digital simulations, forecasting potential outcomes of critical decisions, and comparing probable scenarios. Be it maintenance schedules, process optimization, or emission tracking – digital twins come with prolific possibilities for the industrial world.

Here are the five reasons digital twin solutions are a “must-have” for every industrial company to meet sustainability targets.

  1. The advanced digital twin solutions evolve from descriptive duties to predictive insights where corrective actions are proposed. Information on throughput, quality, and its impact on emissions can make companies aware of their carbon footprint in real time.
  2. Asset managers today face the challenging task of meeting organizational goals in a rapidly changing, disruptive, and unpredictable world. The precision and foresight provided by digital twins can contribute to accurate KPI tracking – resulting in operational reliability which significantly reduces production wastage.
  3. In many industrial plants, a digital divide exists between physical asset management and digital strategy as the majority legacy asset management tools are outdated and not compatible with the industry 4.0 technologies. Digital twins merge asset management with business process operations and information technology – to align decision-making with the organization’s sustainability goals.
  4. Digital twins’ real-time insights can help industrial companies identify the optimum usage of resources with the intent of reducing emissions. Our world’s natural resources are rapidly depleting to the point where they can no longer meet the way of today’s modern life. Digital twins can help industrial companies estimate and meet the demands of energy and materials.
  5. In adapting to an increasingly competitive industrial landscape, the ability to improvise can make a big difference. With digital twins, AI, and predictive simulations, industrial companies can take advantage of self-learning, and dynamic systems to achieve economic and environmental goals.

Explainable AI by Eugenie – Human-Centric Approach

Most AI-based digital twin tools operate in black boxes which means – they provide insights without traceability. The algorithms populate recommendations without the transparency of how they were derived. At Eugenie, we have developed a unique approach to traceability in all our insights through real-time machine data, satellite data, and physics-based models. In a nutshell, data becomes more powerful when combined with other data – leading to an increase in the accuracy of insights manifold.

Eugenie’s solutions enable easy navigation of complex asset hierarchies to identify anomalous assets before more damage can occur. The deep dive modules of Eugenie’s ecosystem can trace similar events in past for easy context establishment which can be consumed in an easy-to-use UI. This results in human-like reasoning for identifying opportunities for operational efficiency and resource management – which are critical for reducing emissions.

Single Source of Truth – Nightmare of Asset Management

From our extensive experience of working with heavy industries, we have seen that many industrial companies do not possess an authentic asset management plan due to a lack of a single, integrated tool, or synchronized group of tools, that can manage various asset types. Asset managers frequently need to switch between tools and asset types. Data too is rarely stored centrally in the bulk of industrial companies.

This makes it extremely challenging to make informed judgments for the entire plant. More often, the legacy asset management tools were created by engineers whose areas of competence were in IT rather than physical asset management.

Forward-thinking businesses are focusing on gaining insights into the effects of larger strategic changes rather than utilizing sensors to create digital twins of specific assets. In other words, process control digital twins must be integrated with asset control digital twins for gaining a holistic overview of the operations.

Business leaders can repeatedly test and experiment with process modifications in virtual environments by using predictive digital twins to apply to end-to-end processes, rather than isolated equipment or manufacturing lines.

This integrated approach enables business leaders to test new supply chain strategies, for instance, without running the risk of risking their current operations.

Eugenie offers both types of digital twins – asset control and process control as part of our comprehensive offerings. Our award-winning solutions enable deploying more than a hundred real-time models for a complex hierarchy of assets. Digital twins of Eugenie enable easy navigation of complex hierarchies and identify problematic assets through real-time alerts.

The Quest for Sustainability 

Simply put, the way we currently live cannot be sustained. We urgently need to find a way to reduce our negative effects on the environment because we are currently using up the earth’s natural resources faster than they can be replenished. The good news is –  data can really help.

We can enhance efficiency and lessen our impact on the environment by collecting data from physical surroundings such as industrial assets. We can then apply the most cutting-edge predictive technologies, like AI and digital twins to reduce the harmful effects of industrial operations.

Eugenie’s digital twins have helped leading industrial companies around the globe across varied domains such as mining, oil & gas, manufacturing, etc. in reducing carbon emissions through improved operational reliability. To know more about Eugenie’s products, schedule a product demo with us. Alternatively, you can write to us at support@eugenie.ai

    This site uses cookies to offer you a better browsing experience. By browsing this website, you agree to our use of cookies.