Good morning, good afternoon, everyone. Thank you for joining me today. I am excited to discuss how AI and robotics are changing the way we disassemble products, which is a crucial step in making our economy more sustainable. By improving how we take products apart, we can recover valuable materials, reduce waste, and better protect our environment. Let's start by understanding the complexity of modern products. Today's devices, such as smartphones, laptops, and even cars, are made from a mix of materials. These include plastics, metals, and rare elements, all of which are tightly packed together. For example, a single smartphone contains over 60 different elements. including precious metals like gold and silver, as well as rare earth enamel. These are critical for its electronics. Because these materials are so tightly integrated, it's hard to separate them once the product reaches the end of its life. The complexity often leads to valuable components being discarded, which not only causes economy losses, but also harms the environment by increasing waste. The challenge we face is how to effectively assemble these products to recover the materials inside. This is where AI and robotics come in. By making the assembly process more efficient, we can recover more materials and reduce the impact on the environment. The approach helps keep valuable materials in use and minimize the need of new raw material, which often require environmental damaging extraction processes. Thank you. Now let's talk about importance of efficient assembly. Research has shown that up to 80 percent of a product's environment impact is determined at the stage of design. This means that how we design products plays a huge role in their overall sustainability. But even with the best design, we will still need efficient assembly processes to reclaim and recycle materials effectively. Consider the example of electronic device. batteries. These batteries are made up of various valuable materials, including lithium, cobalt, and nickel. If we can efficiently disassemble these batteries, we can recover these materials and reuse them in new batteries or other products. These, this reduces the need for mining, which is often associated with significant environmental damage, such as habitat destruction and water pollution. To achieve this advanced AI robotics are essential. AI can analyze the structure and material composition of a material in real time, figuring out the best way to take it apart from damaging the material. Robotics guided by this AI can then execute the disassembly with precision, ensuring that each component is carefully removed. For instance, robots can be equipped with sensors that detect the type of material they are handling, allowing them to adjust their grip or cutting techniques to avoid damage. damaging the materials. This combination of AI and robotics makes it possible to recover more material with less waste. which is critical for moving toward a circular economy where products and material are reused as much as possible. Now, let's talk about AI and robotics in disassembly. Let's explore how, AI and robotics are transforming the disassembly processes, advanced AI system, particularly those based GPT are capable of analyzing complex product design and determining the most efficient way to disassemble them. For example, AI can help identify different types of screws, fasteners, and adhesives used in electronics, which are often difficult to remove without damaging the surrounding components with the help of machine learning algorithms. Robots can be trained to recognize these different elements and use the appropriate tools to remove them. This capability is crucial in industries like electronics recycling, where preserving the integrity of components such as circuit boards and processors is vital for their use. Industries that have adopted AI driven assembly have seen a significant increase in the retrieval of usable components. For instance, some companies reported a 30 percent increase in the amount of valuable materials they can recover. This aesthetics, it's a has real world implication for both economy and the environment. By recovering more materials, companies can reduce their reliance on new raw materials, which often come with high environment and financial cost. Another example in cycling of automotive parts where AI driven system can disassemble components like engine and transmission. with a level of precision that minimizes waste and maximize the recovery of metals such as aluminum and steel. These materials can then be modified down and reused in new products, reducing the need of energy intensive mining and processing. The impact of integrating AI and robotics into disassembling processes is substantial. These technologies not only reduce the environmental footprint of products, We use every day, but also support the broader goals of a circular economy. For example, companies that have implemented EINR's disassembly report up to a 50 percent improvement in metal recovery rates. This improvement has several important implications. First, it reduces the need for extracting new raw material, which is often associated with significant environmental degradation. Mining for materials like copper, gold, and lithium, for example, can lead to deforestation, soil erosion, and water pollution. Second, better material recovery means that more of these materials can be reused in new products. reducing the overall demand for virgin materials. This is not only conserves natural resources, but also lowers the carbon footprint associated with the production of new materials. For instance, recycling aluminum saves up to 95 percent of the energy required to produce new aluminum from raw bauxite. AI also helps improve the sorting of materials during the disassembly processes. ensuring that the cycling products are higher quality. For example, AI systems can identify and separate different type of plastic based on their chemical composition, ensuring that recycled plastics are pure enough to be used in high quality applications such as automotive or construction industry. Despite this advancement, we still face several challenges in current assembly practices. One major challenge is high rate of resources wastage with inefficient recycling methods. Traditional recycling methods, such as shredding, often mix materials together, making it difficult to separate them for use. This combination can significantly reduce the value of recycled materials. For example, when electronics are shredded, metals and plastic can become mixed together, making it difficult to separate them later. ha. This not only reduces the efficiency of recycling processes, but also results in more materials being sent to landfills. Additionally, many products are not designed with disassembly in mind, which make the recycling process even harder. For instance, some products use glue and adhesive that make it nearly impossible to separate components without damaging them. EIN Robotics offers solutions to these problems by automatically. processes and using intelligent separate materials more efficiently. For example, AI can optimize the order in which components are removed, ensuring that valuable materials are recovered without being missed or contaminated. In addition, robots can be equipped with advanced tools that can carefully cut or unscrew components without damaging the material, further improving the quality of recovered material. To see how these technologies work in practice, let's look at some real world examples. In one case study, it is cycling. The robots were equipped with additional vision systems and machine learning algorithms that allowed them to identify and remove valuable components such as processors, memory chips, and batteries with great precision. This led to a 40 percent increase in the recovery of valuable materials, which were then sold back to manufacturing for use in new products. Another example comes from the automotive industry, where an AI guided systems are used to disassemble electric vehicle batteries. The system was able to carefully separate the different materials, including lithium, cobalt, and nickel, with minimal contamination. This not only reduced the cost of recycling, but also ensured that the recovered materials were of high enough quality to be used. in new batteries. This type of closed loop recycling system is essential for reducing the environmental impact of battery production and supporting the growth of the electric vehicle market. These cases study shows that how AI and robotics are not just theoretically concept, they are practically solutions that are already making a difference in the real world. By adopting these technologies, companies can improve their sustainability effort, and they can while also benefiting economically from the recovery and reuse of valuable materials. Looking to the future, AI enhanced assembly is set to play an even bigger role in making manufacturing and recycling more sustainable. As these technologies continue to advance, they will be able to handle a wide range of products and materials more efficiently. For example, future AI systems Could analyze the composition of material in real time, allowing even more precise disassembly. This could be particularly useful in industries like electronics, where the rapid race of technological change means the new materials and designs are constantly being introduced. Additionally, advance in robotics could lead to the development of new tools and technologies for disassembly products that are currently too complex or labor intensive to recycle efficiently. Ultimately, the goal is to create a circular economy where methods are continuously used and basis minimize the vision of sustainable future is within our reach. Thanks to the advancement in AI and robotics by continuing to innovate and integrate these technologies, we can build a world where economic growth and environmental responsibility go hand in hand. Thank you for your attention. I hope this presentation has given you a better understanding. how AI and robotics can help us achieve a more sustainable future. I am happy to answer any question you may have. Thank you.