The Future of lean manufacturing and Six Sigma in AI chat-bots environment
The manufacturing industry has increasingly evolved to enhance efficiency, reduce waste, and optimize productivity. Lean Manufacturing and Six Sigma, is a widely adopted methodology whose purpose is to improve processes, reducing resource consumption and enhancing quality. In recent years, fast deve...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/441728 |
| Acceso en línea: | https://hdl.handle.net/2117/441728 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial intelligence Lean manufacturing Industry 4.0 Problem solving Lean manufacturing, Six Sigma, Artificial intelligence, AI chatbots, Problem solving, Industry 4.0 Intel·ligència artificial Producció ajustada Indústria 4.0 Solució de problemes Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
| Sumario: | The manufacturing industry has increasingly evolved to enhance efficiency, reduce waste, and optimize productivity. Lean Manufacturing and Six Sigma, is a widely adopted methodology whose purpose is to improve processes, reducing resource consumption and enhancing quality. In recent years, fast developments in Artificial Intelligence, particularly in the area of Large Language Models and other types of Generative AI, have started to transform many traditional practices. This dissertation analyses the possible effect of AI chatbots on the future of Lean practices in a digitally advanced industrial environment driven by AI technologies. The focus has been on the promise held out by such tools for process automation facilitation, assistance in real-time decision-making, and the provision of increased data insight access through natural language interfaces. By combining Machine Learning and data analytics with AI chatbots, problem-solving can be expedited, workflow effectiveness can be promoted, communication can be improved within the teams, and the culture of continuous improvement can be fostered. All that aside, though, while the promise is tremendous, there are still things to overcome for which businesses need to prepare. Cybersecurity, staff reluctance to new technology, and the cost of rollout can all be stumbling blocks. A balance between the promise and limitations of this paradigm being facilitated by AI is needed. This dissertation will attempt to explore the current uses of AI chatbots in LSS environments, assess their potential impact on the evolution of smart factories, and determine how they can be used to shape the future of Industry 4.0. |
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