Analyzes IoT energy monitoring effects on efficiency in textile workshops, suggesting human behavior drives improvements.
The textile industry faces dual pressures to enhance operational efficiency while meeting global circular economy targets. While the Internet of Things (IoT) presents a solution, quantitative impact analyses often lack rigor in data normalisation and fail to account for the human element. This study quantitatively analyses the impact of a real-time IoT energy monitoring system (SEMWOSH) on energy efficiency and estimated carbon footprint, while explicitly investigating the human-centric behavioural mechanisms driving these changes. A 12-month pre-post intervention design was employed in a vocational textile workshop. Energy data were normalized using a Production Factor (PF) index to control for workload. Semi-structured interviews with operators and managers were conducted to explain quantitative trends. Normalized analysis revealed a significant operational efficiency improvement of 1.85% in the post-implementation period. Qualitative findings indicate this improvement was driven by the "Observer Effect," where data transparency triggered self-regulation among operators and proactive decision-making by managers. This study confirms that human-centric IoT systems effectively bridge digitalization with circularity. The novelty of this research lies in isolating the behavioural component of energy efficiency, demonstrating that data visibility alone—without mechanical upgrades—can serve as a catalyst for sustainable manufacturing.
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Ahmad Darmawi (2025) studied this question.
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