Assessing Energy Efficiency and Cost Optimization through Data Analytics: A Case Study of CEAT Tyres Manufacturing Plant, Butibori Nagpur

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@article{1716429,
      author = {Suraj Roshan Humane, Dr. Vetrickarthick Rajarathinam, Prof. Nitin Prakash},
      title = {Assessing Energy Efficiency and Cost Optimization through Data Analytics: A Case Study of CEAT Tyres Manufacturing Plant, Butibori Nagpur},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {1897-1907},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716429.pdf},
      abstract = {This study investigates the effectiveness of data analytics in improving energy efficiency and achieving cost optimization at the CEAT Tyers Manufacturing Plant, Butibori (Nagpur), reflecting the operational realities of energy-intensive manufacturing in India. A descriptive and analytical research design was employed, combining primary survey data from plant personnel with secondary evidence from internal energy reports and sustainability documentation. Quantitative analysis was conducted using descriptive statistics and regression modelling through MS Excel and SPSS to examine the influence of analytics adoption on energy and cost outcomes. The results indicate that greater use of analytics tools such as dashboards, trend tracking, and predictive maintenance is associated with improved energy performance and lower avoidable wastage. Regression findings confirm a statistically significant positive impact of analytics utilization on energy efficiency (β = 0.48, p < 0.01) and cost optimization outcomes (β = 0.36, p < 0.05). The study strengthens the view of analytics as a capability for operational sustainability, and it recommends embedding real-time monitoring and analytics-driven decision routines to support continuous improvement in Indian manufacturing plants.},
      keywords = {Data Analytics, Energy Efficiency, Cost Optimization, Specific Energy Consumption (SEC), Sustainable Manufacturing.},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716429}
  }