A framework for sustainable product development using Generative AI
Sandbhor, Amit (2024)
2024
Master's Programme in Business and Technology
Johtamisen ja talouden tiedekunta - Faculty of Management and Business
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Hyväksymispäivämäärä
2024-12-20
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-2024121711322
https://urn.fi/URN:NBN:fi:tuni-2024121711322
Tiivistelmä
This thesis addresses two particularly important and pressing issues in the field today, which are sustainable product design and Generative AI. It recognizes an immediate demand for the inclusion of sustainability in the process of developing products, leveraging what generative AI allows to create more efficient and sustainable results. It investigates ecological sustainability, product development, and generative AI, which are three interrelated themes of research that could form a theoretical work of how these pieces can come together to shape the tomorrow of sustainable innovation.
Research has previously investigated the application of generative AI at distinct phases of the product development process, from design ideation to manufacturing optimization, and for the design sustainability principles in product development. However, there has been insufficient research on how Gen AI can be deployed strategically to integrate ecological sustainability in product development. This research aims to fill this gap by providing a detailed understanding of how Gen AI can be used to reduce environmental impact, increase material optimization, and foster circularity of products.
This study employs a literature review and expert interviews as the main methods to assess the potential applications of generative AI in sustainable product development. Specifically, the example of aircraft galleys in the aerospace sector with which there are strict regulatory standards and environmentally conceptual challenges. The research will give an example of how AI based design and life cycle management can decrease the carbon footprint and waste generation in products development process.
Even though generative AI can help improve sustainability, there is still much to learn about either or how to apply what we know. There are the limitations of the present AI tools, the requirement of the manufacturing for more sophisticated sustainability considerations, as well as the balancing of ecological goals and in commercial development as the challenge. This thesis identifies these gaps and suggests future research directions as well as tries to suggest ways in which generative AI can be used for effective application in sustainable product development.
Research has previously investigated the application of generative AI at distinct phases of the product development process, from design ideation to manufacturing optimization, and for the design sustainability principles in product development. However, there has been insufficient research on how Gen AI can be deployed strategically to integrate ecological sustainability in product development. This research aims to fill this gap by providing a detailed understanding of how Gen AI can be used to reduce environmental impact, increase material optimization, and foster circularity of products.
This study employs a literature review and expert interviews as the main methods to assess the potential applications of generative AI in sustainable product development. Specifically, the example of aircraft galleys in the aerospace sector with which there are strict regulatory standards and environmentally conceptual challenges. The research will give an example of how AI based design and life cycle management can decrease the carbon footprint and waste generation in products development process.
Even though generative AI can help improve sustainability, there is still much to learn about either or how to apply what we know. There are the limitations of the present AI tools, the requirement of the manufacturing for more sophisticated sustainability considerations, as well as the balancing of ecological goals and in commercial development as the challenge. This thesis identifies these gaps and suggests future research directions as well as tries to suggest ways in which generative AI can be used for effective application in sustainable product development.