Settings Auto-scroll Welcome to this latest in a talk session. Today, we'll be looking at the rise of artificial intelligence and machine learning in industrial manufacturing. Exploring why users should be implementing today on what benefits they'll see. We'll also take a look at some of the emerging trends and sweet spot applications for the technology To help me with this, I'm joined by three industry experts who are actively involved in this exciting and fast evolving topic. Perhaps I could ask each of you to introduce yourselves and give us a bit of background on your involvement in the industry. Kathy? Thank you for having me team. My name is Cassier. I'm the principal group peer manager for the industry solution engineering group with Microsoft. Responsible engaging, strategic customer and the partner in Asia to accelerate digital transformation journey through Microsoft Industry and AI technology. In past ten years, I have been working with the many leading high-tech your energy utility company and also automotive venture on smart manufacturer project and helping them to build their build up their commercial models. Thanks, Cathy. Paul. Thanks, Tim. I'm Paul Turner, president and chief operating officer at raven dot ai. My background is in manufacturing. I have a thirty year career, specifically focused on driving productivity improvements on the factory floor through people process and technology. I have a PhD that's in AI in manufacturing, I have over fifty publications in the field, including patents, academic journal publications and industry white papers, and I've been promoting and delivering the adoption of AI in manufacturing since the early nineteen nineties. Thanks, Paul. And finally, Willie. Thank you, Tim. Hello, everyone. I'm Willie. I've been working in the digital transformation and mom manufacturing for over a decade. I had been working with the FastCon, the world's largest EMS company, and also spread headed digital and automation initiative for the traditional footwear and textile company. Now I'm an Advantech leading the team to design and develop the I factory worst applications. Thanks to all of you for joining us. I'd like to start our discussion by briefly understanding where we are today. For sure, there's a lot of noise in the industry about AI and the benefits it can bring. And there seems to be a lot of activity in this area. So what is the current status of AI in manufacturing? Yeah. Before we dive into the AI topic, It's crucial to highlight the foundation role of IoT and industrial four point zero in the modern manufacturing implement is the technology provides the first one up to dates and precise data. The second one we see is the opportunity to identify the relation between the process, machine, and also logistics. The third one, the capability to foresee issues and take action earlier ensuring the smoother operation, safer condition, and also preventive maintenance. Building on this, many factories have studies with a proactive maintenance approach. However, the increasing number of maintenance managers are now learning tools predict maintenance. This not only offers better control over machinery. But also dramatically cuts on a maintenance cost. All that is true. We are getting very good at collecting analysis that's among of the data. But user are still having the problem with the next phase. Which is actually taking action. They all they have all that actionable information, but somehow They still don't believe the technology and feel they still need to engage their senior consultant extensively to figure out what to do next. AI actually provides a copilot for manufacturers that provides immediate insight, meaning their Paradai Asper can focus exclusively on solution and the process improvement greater than performing best among of the analysis. And the reasoning. It offers trust a device to empower human to cope with the situation. We wear urgency and the complexity by. This helps organizations to take action much more quick quickly and with a greater confidence. Which also increase agility, and we we see spring out the audio benefit that we are going to talking about later. I agree, Kathy. I I also think that, the ecosystem itself is something that needs to be right before manufacturers can really leverage the power of artificial intelligence. Over recent years, Literally hundreds of manufacturers, and a plethora of vendors have initiated pilot projects that have failed to scale. So industry for I IoT digital transformation, they haven't yet delivered the productivity improvements that a full scale adoption would facilitate. From my experience, the reasons for this are numerous, but some of the challenges of being, an inability to scale beyond the pilots of pilot purgatory, previous experiences of failed projects where people have got burned and therefore there's a lack of trust. Some approaches have taken, like, an AI is the answer. So what's the problem? So it's technology looking for a problem. But also what I've seen is that not having an ecosystem that's able to support both standardization for scale and speed but also flexibility and adaptability to meet the individual needs of each manufacturing facility, that that's a challenge. And getting this wrong can either lead to bespoke and highly customized projects that are unprofitable to support, maintain, and scale, or at the other end of the spectrum, a one size fits all approach, which tends not to be received at all well by factory floor workers who think, you know, they're they're particular manufacturing facility is is unique and has unique requirements. But Raven, we promote this idea of a best of breed ecosystem where each individual vendor focuses on its strengths and then integrates and collaborates seamlessly with other parts of the ecosystem. And what we found is that with a sensible blend of partners, manufacturers can create an industry for architects that's both fit for scale, but also adaptability, meaning that the right data gets to the right people at the right time with the right context. Okay. So we know there are some very good proof points out there that demonstrate different ways that AI can provide manufacturers with tangible benefits. Be it through improved inspection, better material, and energy consumption, more agile manufacturing, and so on. It seems clear that those organizations who do integrate AI into their processes will gain a competitive advantage over later adopters, And so now is the time to be implementing.