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Adoption of industry 4.0 technologies for decarbonisation in the steel industry: self-assessment framework with case illustration

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Abstract

The study aims to identify, assess, and prioritise barriers to adopting industry 4.0 technology for decarbonisation in the steel industry. It also develops a barrier intensity index of industry 4.0 technologies for decarbonisation. The barriers to industry 4.0 technologies are identified through literature review and semi-structured interviews, and then it is classified into three major categories using technological organisational and environmental theory. The fuzzy Delphi method has been used to finalise these barriers. Then, three major categories of barriers and 21 sub-barriers are prioritised using the best–worst method. The study proposes a self-assessment framework for assessing the intensity of barriers by applying the Graph Theory Matrix approach. This framework is illustrated with the help of an Indian case of steel manufacturing organisation. The findings of the study indicate that a lack of supportive infrastructure followed by a lack of real-time control system and longer learning time due to poor knowledge transfer are the significant barriers to the adoption of industry 4.0 technologies for decarbonisation in the steel industry. Using the proposed self-assessment framework, a steel manufacturing organisation can analyse its position, identify gaps, and work on potential areas of improvement. Insights from this study can help in attaining sustainable development goals (13) i.e., climate action and net zero economy goal.

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Notes

  1. Transforming the Steel Industry May Be the Ultimate Climate Challenge | BCG available at: https://www.bcg.com/publications/2022/steel-industry-carbon-emissions-challenge-solutions

  2. Sustainable Energy for All (SEforALL) Strategic Direction (Detailed) (un.org) available at: https://www.un.org/millenniumgoals/pdf/SEFA.pdf (Accessed on 15th March, 2023)

  3. https://www.un.org/sustainabledevelopment/climate-change/.

  4. https://news.un.org/en/story/2020/03/1059061.

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Acknowledgements

The research work reported in this paper has been funded by Indian Council of Social Science Research (ICSSR), Major Project (02/13568/GN/2021-22/ICSSR/RP/MJ), New Delhi

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  1. Production Operations Management and QT, Institute of Rural Management Anand (IRMA), Anand, Gujarat, India

    Ruchi Mishra

  2. Management Development Institute (MDI), Gurgaon, India

    Rajesh Kr Singh

  3. Operations Management Area, School of Business Administration, Penn State Harrisburg, Harrisburg, USA

    Angappa Gunasekaran

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Appendix

Appendix

(See Tables A1, A2, A3, A4, A5, A6, A7, A8, A9).

Table A1 Experts' profile for FDM
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Table A2 Experts' profile for BWM
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Table A3 BO Vectors barriers to industry 4.0 technologies adoption
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Table A4 BO vectors for technological category of factors
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Table A5 BO vectors for organization category of factors
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Table A6 BO vectors for environment category of factors
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Table A7 OW vectors for three categories of factors
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Table A8 Optimal weights for three categories
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Table A9 Optimal weights for Technological category of factors
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Mishra, R., Singh, R.K. & Gunasekaran, A. Adoption of industry 4.0 technologies for decarbonisation in the steel industry: self-assessment framework with case illustration. Ann Oper Res (2023). https://doi.org/10.1007/s10479-023-05440-0

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