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DIGITAL TWIN FOR TRANSFORMING MANUFACTURING SECTOR How Digital Twin is transforming the manufacturing industry

Jan 27, 2022

The acceptance of digital twin technology has increased manifolds over the past few years with its part played in manufacturing and supply chain continuing to expand at scale. Digital twins offer a prospect to manufacturers to decrease operating expenditures, make better & quicker decisions, use data and information they have at their fingertips and speed up production. The Viewpoint discusses how digital twin is transforming the manufacturing industry and driving value for the sector as a whole.

We must ask, ‘Can we take an entire manufacturing plant and create its own digital twin?’ - Anshul Agarwal, Founder & CEO, XR Central

All the data generated by IoT now has a visual medium to be read in the right manner. That is where the decision-making will happen. Companies are going to implement digital twin, but strategically. When the manufacturing industry talks about digital twin, we say, “can we have a particular turbine engine?” or “can we have a particular machine and create its digital twin?” But we need to think a little beyond this. For instance, we must ask, “can we take an entire manufacturing plant and create its own digital twin?”

If one can stimulate a particular manufacturing plant or machinery in the digital twin, it will be accessible 24/7, which is the best part. One doesn’t really need an instructor to train a particular employee, operator or trainee per se. They can consume data and content at their own will on their devices. They can, in fact, think of it as a science lab.

Digital twins drive a paperless factory, which saves tonnes of carbon footprint - Hudson George Thomas, Digital Manufacturing Consultant, Mercedes Benz Research & Development India

For the manufacturing industry, the digital twin helps optimise the product, process & factory in terms of overall cost & time. As an example, any automobile can be configured up to 70,000 combinations today. Training on all the combinations is practically impossible due to parts availability and cost during the product launch. Here, digital twins play a vital role for blue collars to understand ‘what’ and ‘how’ the product & process is different. Thus, there is a huge saving on training cost & time. Digital twins are effectively used in training for different areas, such as digital assembly, welding, painting, etc. They also drive a paperless factory, which saves tons of carbon footprint involved in the documentation & training involved. Digital twins have already become a fundamental pillar in the manufacturing industry. Thus, it is simply implemented at most organisations. Most industries already have it in one form or another. However, the discovery of how to visualise, utilise, benefit from and monetise the right data is evolving across the industry.

Simulation-based digital twin improves top-line revenue - Rafiq Somani, Area Vice President – India and South Asia Pacific, Ansys

We are currently at the application stage where digital twins can meet business objectives. Simulation allows engineers to advance solutions quicker than ever before. Accurate simulated models/digital twins provide a detailed insight at all stages of the design cycle in real-world situations. Data from field sensors is used and conditions applied to the digital twin, allowing engineers to evaluate performance in real-time and even make redesigns prior to manufacturing/testing. Simulation-based digital twin improves top-line revenue, manages bottom line costs and also gains & retains competitive advantage. When it comes to training workers, digital twins have huge implications across industries as they create a capability to devise and enact synthetic scenarios to provide training. With easy replications of real-world objects, training workers becomes easier.

Today, Industry 4.0 is being embraced to accurately predict the behaviour of common large scale, multifaceted assets in factories – a shift from expensive and slow physical prototyping. Digital twins enable industries to envisage the future and predict how changes in the design, process or environment will impact functions in the real world. When performance data from physical equipment is fed to simulation as it happens, any issue gets addressed immediately before affecting system performance, curbing downtime and saving production costs.

With the data coming from the digital twin, real-time data can now be fed to the AI models - Sunil Palrecha, Chief Digital Officer, Wissen Technology

Digital twins are often used to collect data over time that deliver insights into product performance, distribution and end-user experience. This data makes it easy to share across disciplines, enabling collaboration, improved communication and faster decision-making. Engineering, production, sales and marketing can all work together using the same data to make more informed decisions. Creating a digital twin of new products enables the simulation and testing of all aspects before real production, optimising the product at a very early stage of development. Today, simulations are primarily used for validation and testing. The simulators provide synthetic data for an AI/ML to learn. With the data coming from the digital twin, real-time data can now be fed to the AI models. The AI model can run a particular simulation 10,000 times a day and optimise in days rather than months. The cognitive digital twin using Machine Learning, Natural Language Processing and Natural Language Understanding enables intelligent assistants like Alexa, Cortana, Siri, etc, which can help train workers and enable training on-demand 24/7.

Digital twin gives one visibility into the operation of the machines - Suresha Parashivamurthy, Manager – Artificial Intelligence & Machine Learning, Faurecia India

A digital twin helps the manufacturing industry increase its productivity, flexibility and efficiency. Through data-driven decision-making, digital twins enhance efficiencies without compromising human interaction. A production system enhanced by digital simulation can be both cost and time-effective. Organisations simulate and test every aspect of production before it begins. Manufacturers can explore different materials, colours and textures prior to production with visualisation tools. A digital twin provides a design and implementation tool for constructing synthetic scenarios to be used as a training tool and continuity management tool. It gives one visibility into the operation of the machines, systems and processes. It also acts as a communication tool because one can identify which variables he/she wants to monitor digitally. Additionally, a digital twin can predict the future state of its physical counterpart. It can generate what-if scenarios that are dangerous or cost-prohibitive in reality.

One should ‘think big, start small, fail quickly, scale fast’ - Vijayakumar Kempuraj, Digital Twin Lead, Ford Business Solution

A digital twin helps organisations transform into data native companies. It helps mitigate unplanned downtimes, optimise supply chain routes and avoid the scope for over-engineering. It enables industries to create new products and services at a greater scale. The nature of jobs is evolving exponentially over the period. The penetration of technology and its upgrades are the new normal. Therefore, training and upskilling people are most important. Digital twins are coming in handy in helping workers to go through this transformation throughout their lifecycle, right from the onboarding till they retire. For instance, providing a fail-safe immersive environment for new workers to get familiarised with their work and offer real-time guidance while they are at task.

The digital twin is an aggregation of multiple technologies. It will take five to ten years for its full-scale deployment and adoption. I recommend that one should ‘think big, start small, fail quickly, scale fast’ with an agile mindset and the right culture for change.

Done right, the multiple interoperable digital twins can drive value for both systems and people - Nicolas Waern, Strategy & Innovation Leader, Digital Twin Implementation Specialist, WINNIIO

It’s important that any digital twin initiative considers the aspect of robustness, usefulness & attractiveness and that of interoperability, scalability, which infers a level of composability. Any vendor initiative today will need to be able to respond to how their approaches/solutions adhere to that of AI/ML initiatives, and how they cater to the future of distributed intelligence. Done right, the multiple interoperable digital twins can drive value for both systems and people, getting them on a shared reality for all. This leads to smart decisions faster, based on understandable data sources, providing a foundation for future AI initiatives at scale. In the absolute sense, digital twins will make the training of workers obsolete because it can lead to lights-out factories and robots at the manufacturing lines. But in the interim process, if the digital twin has a reality-based visual/virtual interface, it can improve seamless knowledge transfers between people, irrespective of age, domain, background or skill-set. And it can capture knowledge within the organisation like no other tool before it.

Any company would like to do a digital twin exercise to get an idea of the benefits - Prof R Jayaraman, Head, Capstone Projects, Bhavan's SPJIMR

Since the elements of digital twin are tightly knit with Industry 4.0 types of initiatives, like AI, Big Data and 3D Printing, any company would like to do a digital twin exercise to get an idea of the benefits as well as the cost of switching over to digital. One of the benefits of a digital twin is the realisation of six sigma plus quality at high speed and consistency. Digital operations are largely self-governing and can be programmed to give high-quality output. Workers training will be needed in working with sensors, mimic boards, AI and Machine Learning. This means that the education levels of workers will have to go up. Currently, such training is limited to a few officers in a company.

I absolutely agree where Gartner says organisations will implement digital twins simply at first, then evolve them over time, improving their ability to collect and visualise the right data, apply the right analytics and respond effectively to business objectives. This is because there is a steep learning curve in handling technologies like IoT, AI, ML, cloud computing and so on. Apart from possible high investments, disruption to normal production could be costly in terms of lost sales and lower quality till stabilisation. There are several companies in India that have done this.

Digital twins will certainly help businesses learn more, do more and achieve more with less - Sandeep Shukla, Global COE Head- Advance Manufacturing, Engineering TATA Technologies

The digital twin helps identify, differentiate and adopt the best of the best processes & practices to improve the entire value chain. It is going to be a bedrock for all upcoming manufacturing industries – discrete and continuous – in order to have a deep insight of the current state, help make informed decisions in order to improve on it, and more importantly, to have a concrete plan for new product launches in an efficient, effective and agile way. Digital twins not only allow one to learn from mistakes but also have great potential to learn from the best practices across the value chain to strive for simply excellence. It also helps to create a healthy competitive culture. It certainly is and will help businesses and operators to learn more, do more and achieve more with less.

Image Gallery

  • Anshul Agarwal

    Founder & CEO

    XR Central

  • Hudson George Thomas

    Digital Manufacturing Consultant

    Mercedes Benz Research & Development India

  • Rafiq Somani

    Area Vice President – India and South Asia Pacific

    Ansys

  • Sunil Palrecha

    Chief Digital Officer

    Wissen Technology

  • Suresha Parashivamurthy

    Manager – Artificial Intelligence & Machine Learning

    Faurecia India

  • Vijayakumar Kempuraj

    Digital Twin Lead

    Ford Business Solution

  • Nicolas Waern

    Strategy & Innovation Leader, Digital Twin Implementation Specialist

    WINNIIO

  • Prof R Jayaraman

    Head, Capstone Projects

    Bhavan's SPJIMR

  • Sandeep Shukla

    Global COE Head- Advance Manufacturing, Engineering

    TATA Technologies

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