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<p>Artificial intelligence (AI) is an emerging technology that has been widely used in the field of manufacturing. In this paper, we explore the integration of AI in sustainable manufacturing using TRIZ S-curve analysis and insights from a Delphi survey of industry experts.In this paper, we explore the integration of AI in sustainable manufacturing using TRIZ S-curve analysis and insights from a Delphi survey of industry experts. The results underscore the need for a multidisciplinary approach to match artificial intelligence innovations with sustainable development goals, guaranteeing not only efficiency but also inclusivity and long-term society impact with the more general objectives of sustainable development and responsible innovation.The results underline the need for a multidisciplinary approach to match artificial intelligence innovations with sustainable development goals, guaranteeing not only efficiency but also inclusivity and long-term society impact with the more general objectives of sustainable development and responsible innovation. The key themes emerged: democratisation of AI, ethical AI deployment, and alignment with the Sustainable Development Goals (SDGs). The paper proposes actionable strategies to overcome barriers to adopting artificial intelligence in manufacturing, such as the need for internal data science expertise and ethical considerations, ultimately contributing to sustainable industry practices.</p>

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Leveraging AI and TRIZ for sustainable innovation in advanced manufacturing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月2日

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  • Muhammad Saqib Iqbal,
  • Zulhasni Abdul Rahim,
  • Qudrattullah Omerkhel,
  • Hamza Iftikhar,
  • Muhammad Fawad Khan

摘要

Artificial intelligence (AI) is an emerging technology that has been widely used in the field of manufacturing. In this paper, we explore the integration of AI in sustainable manufacturing using TRIZ S-curve analysis and insights from a Delphi survey of industry experts.In this paper, we explore the integration of AI in sustainable manufacturing using TRIZ S-curve analysis and insights from a Delphi survey of industry experts. The results underscore the need for a multidisciplinary approach to match artificial intelligence innovations with sustainable development goals, guaranteeing not only efficiency but also inclusivity and long-term society impact with the more general objectives of sustainable development and responsible innovation.The results underline the need for a multidisciplinary approach to match artificial intelligence innovations with sustainable development goals, guaranteeing not only efficiency but also inclusivity and long-term society impact with the more general objectives of sustainable development and responsible innovation. The key themes emerged: democratisation of AI, ethical AI deployment, and alignment with the Sustainable Development Goals (SDGs). The paper proposes actionable strategies to overcome barriers to adopting artificial intelligence in manufacturing, such as the need for internal data science expertise and ethical considerations, ultimately contributing to sustainable industry practices.