Good afternoon. We welcome you to a virtual tour of the factory of the future. I am Srini and I will be your virtual tour guide for the second year in A running. At IDC is Manufacturing Summit. I had the connected plant in Industry 4.0 business for TCS Global. In the last couple of years. We have been seeing some very interesting developments. Especially around the interaction and learning between humans and machines. On one hand, we're using. Extensively. AI based tools for the discovery of medicines, especially vaccines. And on the other hand, we see an increasing use of humans showing remarkable resilience as well as self healing capabilities when it comes to the recovery from the pandemic. Businesses have also shown blocker of adaptability when it comes to this great turbulence in our business environment. And they have been able to leverage digital tools to ensure business continuity as well as disaster recovery. So we are seeing a resurgence in global demand on one hand. As has been indicated by the PMI, which is soaring in almost all regions of the world. And on the other hand, we are also seeing a big disruption in the supply chain. So when we see this contrast. There is a question that comes to our mind as to what is it that we can do better. And the attention therefore comes naturally back into the plant. How do we make our plant systems more resilient, more adaptable? And capable of withstanding this turbulence, which we can expect to be far more frequent than ever before in the days to come. The economic necessity of this demand is actually driving a lot of innovation in which the way the plants are going to operate. In fact, we are now seeing the early emergence of what is being called as lights out manufacturing. If you see the demands placed on the plant today, some of which we have depicted on the screen here in front of you. There is a clear evidence that plants are expected to behave more and more like humans. The human system is very interesting. It is endowed with a lot of extraordinary capabilities, especially spontaneity in response, autonomous action, and last but not the least, intuition. Knowledge, cognition and learning are core to the way the human systems respond. Two, external threat as well as changes in the external environment. And there's a lot of learning for us in manufacturing systems from the point of view of resiliency and adaptability. We at TCS all this as neural manufacturing. The factories are actually coming to life with a being of sense, perceive and act. This inspiration is driving her significant transformation in manufacturing. How is this neural manufacturing concept different from smart manufacturing, which is already in play across the globe? We added two dimensions to the concepts of smart manufacturing number 1 A Virtual command control concept, pretty much representing the human brain. And how it drives the various organs in synchronization? And the second a data like store very much like the convolution in the brain where all this cognition, learning, knowledge storage happens. By combining these with the physical world, we were able to conceptualize a brand new architecture which could deliver many of these capabilities, and these will only accelerate as the tools built around haptics and other senses. Evolve further. Let's take a look at few simple opportunities that are there in front of us today. Let's take a new product introduction. Working in remote. You would be able to launch the product into production. And before you do that and encounter bottlenecks, the digital thread brings all the necessary data into the digital twin. And with the help of digital manufacturing technology, you can simulate the plant, understand the bottlenecks, remove the bottlenecks and be ready. This allows a lot of cost saving and time saving as you prepare for production. Take the next example, self healing. Let's take a machine that breaks down during production. Now this is different from your already built up capabilities around predictive or prescriptive diagnostics. These are incidents that happen in real life. And while you do the data and knowledge mining on how to set right that system, there are opportunities for self heal in being built into the machines as well as an alternate available wherein the line also leverages alternate paths of production in order to keep the plant running. If there is an external disturbance, which is what we are experiencing across, the resiliency comes into question. And here the ability of the planning systems to understand the capacity inside this stores and the ecosystems which is supporting the plant and be able to replan either alternate products or alternate production routes or alternate sources of supply. So all of these today do take a lot of time because of human intervention if we were able to pull this off virtually with the help of. The data that we are collecting, we should be able to see a lot more autonomous action being driven inside the plants. This is how the plant would therefore start looking like. There are physical systems. Which we all work. These are the smart machines, the virtual systems, which are what we see as digital twins and digital threads. But then there are data systems, and that's what we call as the neural data fabric. This pulls all the information together and in conjunction with the central command center, we'll be able to drive the ecosystems which are dependent or responding to the demands of this plant. In recent times we've worked on complex problems on the supply side, for example. Helping our suppliers respond to changes in the market almost in tandem. Or on the demand side, delivering on time in full or perfect orders as we would like to call it and inside the plant by being able to repeatedly, continuously respond to changes in production plans and schedules. When we look at how that architecture would evolve. It would look something like this. A capabilities layer. A service orchestration layer built around this neural data, a collaboration layer where all the workers and the partners would work and a consumption layer where the data is used, let's say the decision makers inside the plant or the suppliers. So this is how we see a layered approach. Of cognitive behavior being developed inside plant operations. One thing that one has to keep in mind is no plant. Is ever the same as another plant. So when it comes to manufacturing, one size never fits all. So while we have automation, cloud capabilities, cognitive systems, smart machines, you have to choose what's best for your manufacturing operations and for that plant. You can go all the way from level 1 to Level 5, but what's most important is number 1, the business and operating model that you are choosing and number 2. Is your investment because you shouldn't run out of CapEx after all this is business funded and therefore we need to prove that there is a return on investment. So while everybody would be would be wanting to be at level 5. Pragmatism dictates that you choose the level which is most optimal for what you are setting out to do. Well, the road map, pretty simple. First, build that visionary architecture for yourself, suited to your business goals. Start putting the capabilities in place and then deploy one feature at a time. Realize the benefits, reinvest the results, outcomes. And then you will see the plant gradually stepping up to becoming the factory of the future that we all envisage which demonstrate. The ability to be lights out or which is neural in nature. Just to conclude. Who we are we are TCS one of the largest global IT service firms. With a dominant position in the engineering services business and industrial IoT, we'd be happy to. Receive your questions as well as we welcome you to participate in the virtual booth that we have here at the conference. Thank you and back to IDC.