Greening the Code : energy-efficient software practices for digital sustainability in smart industrial systems energy-conscious algorithm design for predictive maintenance in industry 4.0.

Abstract

This thesis investigates how energy-conscious algorithm design can contribute to sustainable predictive maintenance in Industry 4.0. Using a systematic literature review of academic databases, the study reviews approach to algorithmic optimization, trade-offs between accuracy and energy use, and practical examples from industry.

The results suggest that efficient algorithms can reduce the digital carbon footprint while maintaining reliability, though challenges such as standardization and performance trade-offs persist. The study concludes that integrating energy-aware design principles into predictive maintenance can advance both industrial efficiency and digital sustainability.