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Hello World but in VR

By :

The mission was simple- create some interactive objects and also a futuristic environment. I stood at the crossroads, uncertain where to begin, so the first thing that I did was open YouTube and type-” how to build your first game in VR”. After watching a couple of videos, one thing was definite-” Oculus “. Oculus is the hardware used for most VR applications. So, I went ahead and placed an order for the Oculus which took around 15 days to get delivered. The unboxing felt like I had the key to the future, and now what? I ended up playing some games to understand how VR works and also just playing games.


Imagination part I

Then, I got a call from my manager-” Vignesh, Where is my metaverse?” 

The burgeoning weight of expectations compelled me to set aside gaming and delve into development. So, hopped onto my laptop which at times was a little specced out. Nevertheless, I started to do some research on how to build VR apps on YouTube, Oculus development page, Unity development page, and a few others. The information was quite overwhelming at the beginning and most of it bounced over my head. Took some time to understand the terminologies used in game engines, effective workflows, and finally how to import 3D models from Blender. I made some test Models in Blender with some free source files “sketchfab.com” because that was the fastest way to run a trial in Unity and Blender. Once I got the free resources, I tried to export it to Unity but for some reason, it was not working. So you guessed it right, YouTube became my refuge, and YES I found the solution. The feeling of successfully importing the 3D file to Unity was like I had accomplished 70% of the task but in reality, it was just 10%. There were a lot more things to figure out, like UV unwrapping, texturing, baking, emission materials, and baking animation which I still need to discover. A month’s time had already passed and I had made no major progress just as I grappled with this, a message from my manager appeared:“ Vignesh, when can I see the metaverse??”



Imagination part II

This is when I realized I needed to learn faster and work more efficiently and by chance I ended up on this amazing YouTube channel called Dilmer Valecillos where he teaches and explains VR development fundamentals and also shares the source code for some tutorials. That’s when I came across Oculus Interaction SDK. SDK (Software development kit) is a framework which apps and software are built upon. Thankfully Oculus development site provides their SDK which helps to develop games for Oculus. Having all the necessary knowledge and resources for development, I began to create 3D models in Blender, import them to Unity, and use the interaction SDK to make the models interactable. 

ALL was fine until I had to install the game into Oculus. The game would simply not install on Oculus. So I did some research and found that I had to change some settings in Unity for it to install.

Finally, I donned the Oculus on eagerly waiting for the game to start, when the loading screen disappeared I could see the environment created in VR but I wasn’t able to move or interact with the objects. This was a huge setback after spending nearly 4 months learning different tools and software needed for the development.


OK! Reality

This setback ushered in introspection and I realized my focus was not on learning the software extensively so, made a plan with the guidance of my manager to focus on one tool at a time and to understand it at the fundamental level. The tools were Blender and Unity, I previously had some experience in 3D so Blender was a bit easier to learn compared to Unity which has coding and I don’t know how to code. The fear of coding was hindering my learning curve in Unity but I figured not everything requires coding. Also, my fellow colleague was kind enough to help me out with coding. We decided that I would be focusing on creating 3D environments and some basic interaction on Unity and Rabi would do the coding. So, we set sail and within a few weeks we were ready to finally show the prototype to our manager. We tried our best to get it as expected but it was far from that and it needed more creative inputs, quality renders, and intuitive interactions. These were a few key pieces of feedback we got from presenting the prototype to the manager.

These experiences will undoubtedly shape my growth as a VR developer and provide valuable insights that extend beyond the world of virtual reality. I hope it resonates with many aspiring people who venture into the world of virtual reality.

P.S. The Project Metaverse is still ongoing.

About the Author: Vignesh is a creative visual designer and quirky art director! With a heart full of innovation, he crafts designs that tell vibrant stories and leave lasting impressions. Beyond design, he’s an adrenaline junkie seeking excitement in life.

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Will AI Be the Future’s Definition of Sustainable Manufacturing?

Governments worldwide are implementing strict energy and emission policies to drive sustainability and efficiency in industries:

  • China’s Dual Control Policy (since 2016) enforces strict limits on energy intensity and usage to regulate industrial consumption.
  • The EU’s Fit for 55 Package mandates industries to adopt circular economy practices and cut emissions by at least 55% by 2030.
  • Japan’s Green Growth Strategy incentivizes manufacturers to implement energy-efficient technologies through targeted tax benefits.
  • India’s Perform, Achieve, and Trade (PAT) Scheme encourages energy-intensive industries to improve efficiency, rewarding those who exceed targets with tradable energy-saving certificates.

These policies reflect a global push toward sustainability, urging industries to innovate, reduce carbon footprints, and embrace energy efficiency.

What’s driving the world to impose these mandates in manufacturing?

This is because the manufacturing industry is at a crossroads. With environmental concerns mounting, the sector faces some stark realities. Annually, it generates 9.2 billion tonnes of industrial waste—enough to fill 3.7 million Olympic-sized swimming pools or cover the entire city of Manhattan in a 340-foot layer of waste. Manufacturing also consumes 54% of the world’s energy resources, roughly equal to the total energy usage of India, Japan, and Germany combined. And with the sector contributing around 25% of global greenhouse gas emissions, it outpaces emissions from all passenger vehicles worldwide.

These regulations are ambitious and necessary. But here’s the question: Can industries meet these demands without sacrificing profitability?

Yes, sustainability initiatives are not a recent phenomenon. They have traditionally been driven by the emergence of smart technologies like the Internet of Things (IoT), which laid the groundwork for more efficient and responsible manufacturing practices.

Today, most enterprises are turning to AI in manufacturing to further drive efficiencies, lower costs while staying compliant with regulations. Here’s how AI-driven manufacturing is enhancing energy efficiency, waste reduction, and sustainable supply chain practices across the manufacturing landscape.

How Does AI Help in Building a Sustainable Future for Manufacturing?

1. Energy Efficiency

Energy consumption is a major contributor to manufacturing emissions. AI-powered systems help optimize energy usage by analyzing production data, monitoring equipment performance, and identifying inefficiencies.

  • Siemens has implemented AI in its manufacturing facilities to optimize energy usage in real-time. By analyzing historical data and predicting energy demand, Siemens reduced energy consumption by 10% across its plants. 
  • In China, manufacturers are leveraging AI-driven energy management platforms to comply with the Dual Control Policy. These systems forecast energy consumption patterns and recommend adjustments to stay within mandated limits.

Impact: AI-driven energy management systems not only reduce costs but also ensure compliance with stringent energy caps, proving that sustainability and profitability can go hand in hand.

2. Waste Reduction

Manufacturing waste is a double-edged sword—it pollutes the environment and represents inefficiencies in production. AI helps manufacturers minimize waste by enhancing production accuracy and enabling circular practices like recycling and reuse.

  • Procter & Gamble (P&G) uses AI-powered vision systems to detect defects in manufacturing lines, reducing waste caused by faulty products. This not only ensures higher quality but also significantly reduces raw material usage.
  • The European Union‘s circular economy mandates have inspired manufacturers in the steel and cement industries to adopt AI-driven waste recovery systems. For example, AI algorithms are used to identify recyclable materials from production waste streams, enabling closed-loop systems. 

Impact: AI helps companies cut down on waste while complying with mandates like the EU’s Fit for 55 package, making sustainability an operational advantage.

3. Sustainable Supply Chains

Supply chains in manufacturing are vast and complex, often contributing significantly to carbon footprints. AI-powered analytics enable manufacturers to monitor and optimize supply chain operations, from sourcing raw materials to final delivery.

  • Unilever uses AI to track and reduce the carbon emissions of its suppliers. By analyzing data across the supply chain, the company ensures that partners comply with sustainability standards, reducing overall emissions.
  • In Japan, automotive manufacturers are leveraging AI for supply chain optimization. AI algorithms optimize delivery routes and load capacities, cutting fuel usage and emissions while benefiting from tax incentives under Japan’s Green Growth Strategy.

Impact: By making supply chains more efficient, AI not only reduces emissions but also builds resilience, helping manufacturers adapt to global disruptions while staying sustainable.

4. Predictive Maintenance

Industrial machinery is a significant source of emissions and waste when it operates inefficiently or breaks down. AI-driven predictive maintenance ensures that equipment is operating at peak performance, reducing energy consumption and downtime.

  • General Electric (GE) uses AI-powered sensors to monitor the health of manufacturing equipment. These systems predict failures before they happen, allowing timely maintenance and reducing energy waste.
  • AI-enabled predictive tools are also being adopted under India’s PAT scheme, where energy-intensive industries leverage real-time equipment monitoring to enhance efficiency. (Source)

Impact: Predictive maintenance not only extends the lifespan of machinery but also ensures that energy-intensive equipment operates within sustainable parameters.

The Road Ahead

AI is no longer just a tool—it’s a critical partner in achieving sustainability. By addressing challenges in energy usage, waste management, and supply chain optimization, AI helps manufacturers not just comply with global mandates but thrive in a world increasingly focused on sustainability.

As countries continue to tighten regulations and push for decarbonization, manufacturers that embrace AI stand to gain a competitive edge while contributing to a cleaner, greener future.

Mantra Labs helps manufacturers achieve sustainable outcomes—driving efficiencies across the shop floor to operational excellence, lowering costs, and enabling them to hit ESG targets. By integrating AI-driven solutions, manufacturers can turn sustainability challenges into opportunities for innovation and growth, building a more resilient and responsible industry for the future.

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