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Towards Leveraging Artificial Intelligence for Sustainable Cement Manufacturing: A Systematic Review of AI Applications in Electrical Energy Consumption Optimization

Author

Listed:
  • Olurotimi Oguntola

    (Systems Engineering Department, Colorado State University, Fort Collins, CO 80523, USA)

  • Kwaku Boakye

    (Systems Engineering Department, Colorado State University, Fort Collins, CO 80523, USA
    Heidelberg Materials Inc., Irving, TX 75062, USA)

  • Steve Simske

    (Systems Engineering Department, Colorado State University, Fort Collins, CO 80523, USA)

Abstract

Cement manufacturing is known for its significant energy consumption and environmental footprint. As the world strives for sustainability, optimizing electrical energy consumption (EEC) in cement manufacturing is essential for reducing operational costs and minimizing the industry’s environmental impact. This systematic review aims to synthesize and analyze existing scholarly works and industry reports on methods and approaches for EEC optimization in cement production. It examines papers published between 1993 and 2023 in academic databases, scholarly journals, and industry publications to identify open questions and areas where future research may be needed. While challenges remain, continued research and innovation are key to further advancements in energy efficiency in cement production. With the advent of Industry 4.0 digitalization and advancements in data analytics and industrial Internet of Things (IIoT), artificial intelligence (AI) can be leveraged to optimize EEC. This study is a review of the applications of artificial intelligence to EEC optimization in industries that have heavy demand for electric power to highlight the value of directing research to its applications in cement manufacturing. The study posits that with digitalization, applying artificial intelligence to extract operational insights from the data collected from embedded sensors and meters at the plant presents the most cost-effective, high-return, and low-risk opportunity to optimize EEC in cement manufacturing.

Suggested Citation

  • Olurotimi Oguntola & Kwaku Boakye & Steve Simske, 2024. "Towards Leveraging Artificial Intelligence for Sustainable Cement Manufacturing: A Systematic Review of AI Applications in Electrical Energy Consumption Optimization," Sustainability, MDPI, vol. 16(11), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4798-:d:1408882
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    References listed on IDEAS

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    1. Olurotimi Oguntola & Steven Simske, 2023. "Continuous Assessment of the Environmental Impact and Economic Viability of Decarbonization Improvements in Cement Production," Resources, MDPI, vol. 12(8), pages 1-20, August.
    2. Atmaca, Adem & Kanoglu, Mehmet, 2012. "Reducing energy consumption of a raw mill in cement industry," Energy, Elsevier, vol. 42(1), pages 261-269.
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    Cited by:

    1. Antonius Setyadi & Sundari Soekotjo & Setyani Dwi Lestari & Suharno Pawirosumarto & Alana Damaris, 2025. "Trends and Opportunities in Sustainable Manufacturing: A Systematic Review of Key Dimensions from 2019 to 2024," Sustainability, MDPI, vol. 17(2), pages 1-34, January.
    2. Saime Taphasanoğlu & Muhammet Raşit Cesur & Elif Cesur, 2024. "A Precise Energy Consumption Model for Computer Numerical Control Machines: A Hybrid Approach," Sustainability, MDPI, vol. 16(23), pages 1-22, December.

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