PDCA-Based Methodology for the Evaluation of Energy Efficiency in the Industrial Sector

Reducing energy consumption and improving energy efficiency are essential objectives in the productive sector to ensure economic growth and reduce emissions. However, some energy management models do not include tools such as the balanced scorecard (BSC) and energy-based key performance indicators (KPIs). These tools help organisations make decisions and support continuous improvement actions. To address this gap, this study developed a methodology to facilitate the implementation of an Energy Management System. Specifically, this system evaluates the energy performance of processes within the abrasives industry, using KPIs based on energy efficiency. The proposed model, based on the Deming Cycle (PDCA, Plan-Do-Check-Act), consists of three stages: first, profiling and planning; second, implementation and maintenance; and third, surveillance. To support these stages, the main KPIs of energy typology were determined using AHP. Following this, the KPIs were prioritised based on energy efficiency. The results indicate that the company’s highest priority is meeting international goals, followed by reducing production costs and avoiding energy-related penalties. The energy baseline developed through regression analysis yielded a coefficient of 0.7794 and a specific consumption of 0.0345 kWh per manufactured piece for electricity alone, which increases by 107.25% when all energy sources used in the process are included. Within this context, the key indicators for monitoring energy efficiency strategies were established, demonstrating that model-assisted energy management not only supports the identification of improvement opportunities and internal control of production parameters but also provides a robust framework for evaluating, measuring, reporting, and improving energy efficiency targets.

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Publication Details

Journal
Applied Sciences
Published
2025-11-26
DOI
https://doi.org/10.3390/app152312530
Primary Topic
Energy Efficiency and Management
Type
article
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article

PDCA-Based Methodology for the Evaluation of Energy Efficiency in the Industrial Sector

Paúl Taboada-González, Quetzalli Aguilar-Virgen, Luis Eduardo Vargas-Gurrola, Silvia María Balderas-López
Applied Sciences
Energy Efficiency and Management
article

PDCA-Based Methodology for the Evaluation of Energy Efficiency in the Industrial Sector

Paúl Taboada-González, Quetzalli Aguilar-Virgen, Luis Eduardo Vargas-Gurrola, Silvia María Balderas-López
article en

Abstract

Reducing energy consumption and improving energy efficiency are essential objectives in the productive sector to ensure economic growth and reduce emissions. However, some energy management models do not include tools such as the balanced scorecard (BSC) and energy-based key performance indicators (KPIs). These tools help organisations make decisions and support continuous improvement actions. To address this gap, this study developed a methodology to facilitate the implementation of an Energy Management System. Specifically, this system evaluates the energy performance of processes within the abrasives industry, using KPIs based on energy efficiency. The proposed model, based on the Deming Cycle (PDCA, Plan-Do-Check-Act), consists of three stages: first, profiling and planning; second, implementation and maintenance; and third, surveillance. To support these stages, the main KPIs of energy typology were determined using AHP. Following this, the KPIs were prioritised based on energy efficiency. The results indicate that the company’s highest priority is meeting international goals, followed by reducing production costs and avoiding energy-related penalties. The energy baseline developed through regression analysis yielded a coefficient of 0.7794 and a specific consumption of 0.0345 kWh per manufactured piece for electricity alone, which increases by 107.25% when all energy sources used in the process are included. Within this context, the key indicators for monitoring energy efficiency strategies were established, demonstrating that model-assisted energy management not only supports the identification of improvement opportunities and internal control of production parameters but also provides a robust framework for evaluating, measuring, reporting, and improving energy efficiency targets.

Applied SciencesVol. 15(23)
Universidad Autónoma de Baja California (MX), Instituto Tecnológico de Tijuana (MX)
Openalex Percentile: Top 73%
Energy Efficiency and Management
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