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Improving Supply Chain Sustainability Using Artificial Intelligence: Evidence from the Manufacturing Sector

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Industry 4.0 Technologies: Sustainable Manufacturing Supply Chains

Abstract

Businesses and governments worldwide are implementing measures to tackle the significant sustainability challenges in the manufacturing sector, including environmental, health and safety and productivity related. As the sector moves toward Industry 4.0, Artificial Intelligence (AI) is viewed as a promising solution to address these challenges. However, current knowledge on these technologies and their interplay with the triple bottom line (TBL) sustainability dimensions is scattered and unclear. This study seeks to bridge this gap by creating a comprehensive AI implementation framework consisting of application, data and computation layers. The AI applications are categorized into virtualization, forecasting, automation and intelligent environment, while the computation layer comprises machine learning, deep learning, computer vision and natural language processing. These in turn use multimedia, time-series manufacturing, product parameter, sensor and location-based data inputs. Moreover, the framework assesses the impact of AI technologies on enhancing TBL sustainability, covering environmental, social and economic aspects. This novel and comprehensive framework, which is not seen in the previous literature, can support the development of policy interventions and support systems to promote AI adoption in the manufacturing sector, while also achieving TBL sustainability goals.

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Author information

Authors and Affiliations

  1. Business School, Middlesex University Dubai, Dubai, United Arab Emirates

    Sreejith Balasubramanian

  2. Business School, Middlesex University London, London, UK

    Vinaya Shukla

  3. Business School, Birmingham University Dubai, Dubai, United Arab Emirates

    Linsy Kavanancheeri

Authors
  1. Sreejith Balasubramanian
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  2. Vinaya Shukla
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  3. Linsy Kavanancheeri
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Corresponding author

Correspondence to Sreejith Balasubramanian .

Editor information

Editors and Affiliations

  1. Department of Production Engineering, National Institute of Technology Tiruchirapalli, Trichy, India

    Vimal K E K

  2. Department of Mechanical Engineering, National Institute of Technology Patna, Patna, India

    Sonu Rajak

  3. Faculty of Business, Law and Social Sciences, Birmingham City University, Birmingham, UK

    Vikas Kumar

  4. Business Systems and Operations, Faculty of Business and Law, University of Northampton, Northampton, UK

    Rahul S. Mor

  5. Water, Environment and Climate Change Centre, Royal Scientific Society, Amman, Jordan

    Almoayied Assayed

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Balasubramanian, S., Shukla, V., Kavanancheeri, L. (2024). Improving Supply Chain Sustainability Using Artificial Intelligence: Evidence from the Manufacturing Sector. In: K E K, V., Rajak, S., Kumar, V., Mor, R.S., Assayed, A. (eds) Industry 4.0 Technologies: Sustainable Manufacturing Supply Chains . Environmental Footprints and Eco-design of Products and Processes. Springer, Singapore. https://doi.org/10.1007/978-981-99-4894-9_4

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  • DOI: https://doi.org/10.1007/978-981-99-4894-9_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-4893-2

  • Online ISBN: 978-981-99-4894-9

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