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Transforming Enterprise Manufacturing Management – The Digital Twin Way
Transforming Enterprise Manufacturing Management – The Digital Twin Way

February 10, 2022

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John loves his car. Every morning before he drives to work, dropping his children at school on the way, he likes to walk around his silver-grey V8 beauty and take a peek under the hood, looking for potential signs of trouble before they arise.

While John swears by the utility of his morning routine, it is a considerable source of annoyance for his 10-year-old twins Peter and Lucy, who are already in the backseat waiting for their school drop-off.

John’s actions here are similar to the legacy approach towards plant and equipment management, involving an active, physical monitoring of assets for potential signs of failure, and reacting to those challenges. While this supervising is quite useful in itself, it is time-consuming, reactive, and costlier in the long run.

How about a scenario where the smart sensors in John’s car monitor the vehicle health in real time, and inform him of any potential failures before they happen? Enter digital twin.

When Reality Meets Virtual: Leveraging a Digital Twin Solution

Digital twin technology was recognized as one of Gartner’s Top 10 Strategic Trends for 2017. It involves the creation of a virtual alter ego for a physical product, which could be a locomotive, a wind turbine, an entire factory, or even John’s car. These objects are embedded with sensors that collect and share data in real time with their digital counterpart, making it possible to understand and predict outcomes under different scenarios. The digital avatar of the physical equipment can then be leveraged for undertaking a what-if analysis, and acts as a key enabler for initiating predictive maintenance requests.

Now let us expand this scenario to cover a manufacturing setup. Incorporating digital twin technology in a factory floor would allow access to real-time monitoring data from all key machinery, enable digital scenario analysis without undue risk to the physical components, empower us to streamline maintenance schedules, and help minimize downtime.

In other words, the virtual recreation of the physical setup would drive a better understanding of the production line – both now, and in the future. This in turn would boost overall equipment effectiveness, help optimize productivity, and improve overall business profitability.

Digital Twin in Action

While simulation is the starting point of any digital twin framework, its strength lies in the ability to incorporate real-time inputs and updates. During a regular simulation, engineers are limited in their ability to conduct assessments and tests on a static version of the physical asset, unless new parameters can be introduced. On the other hand, a digital twin setup receives real-time inputs from the relevant physical asset, system, or process, enabling the team of engineers to undertake their analysis under real-world conditions. The state of the digital twin changes dynamically and matures as it receives new data from its physical world counterpart, delivering an output that is therefore more accurate and valuable.

A digital twin solution consists of three main elements:

  1. Historical data, including, past performance data from individual machines, the overall processes, and particular systems.
  2. Current data, including real-time inputs from the equipment sensors, data feed from the manufacturing systems and platforms, and information from the diverse systems constituting the distribution chain. This can also include inputs from systems across other business units, including customer servicing and purchasing systems.
  3. Future data, including, machine learning results and inputs from the expert engineers.

The framework leverages all these data streams to drive enhanced decision making, even from a remote location, and delivers an overall enhanced outcome across operability, productivity, and profitability.

Towards Transforming Enterprise Manufacturing

The global market for digital twin solutions was valued at USD 3.1 billion in 2020, and is expected to reach USD 48.2 billion by 2028, a phenomenal 58% CAGR during the forecast period. This growth trajectory has been further boosted by the COVID-19 pandemic, which has driven home the need for a whole new outlook in plant maintenance and manufacturing processes across industries.

A growing need for remote-work options in legacy roles, and the imperative to return to ‘business-as-usual’ at the earliest has resulted in an expansion in the adoption of digital twin. While earlier manufacturers were looking at this digital technology offering as a way to optimize maintenance costs, the new restrictions arising from the pandemic have added a significant dimension by underscoring the need for remote monitoring.

Again, virtual prototyping of products has emerged as a key application area for digital twin technology, enabling OEMS to deliver customized offerings to different groups of customers by leveraging a better understanding of the product’s characteristics and failure modes. Healthcare and pharmaceutical companies are also looking to incorporate the technology in their offerings to drive better patient monitoring, improve medical data collection, and enhance their delivery capabilities.

Manufacturers the world over are therefore looking to embrace this incremental innovation to transform their operations in a rapidly evolving global scenario.

And lest we forget, the twins Peter and Lucy are quite happy these days – the digital twin of the family car has liberated them from the boredom of John’s morning routine!   


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