Economic and Production-Related Implications for Industrial Energy Efficiency: A Logistic Regression Analysis on Cross-Cutting Technologies

Fábio De Oliveira Neves,Sandra Regina Monteiro Masalskiene Roveda,Andrea Trianni,José Arnaldo Frutuoso Roveda,Henrique Ewbank,Fernando Pinhabel Marafão

doi:10.3390/en15041382

Fábio De Oliveira Neves, Sandra Regina Monteiro Masalskiene Roveda + Show 4 more

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https://doi.org/10.3390/en15041382

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Abstract

Increased industrial energy efficiency (EE) has become one of the main environmental actions to mitigate carbon dioxide (CO2) emissions, contributing also to industrial competitiveness, with several implications on the production system and cost management. Unfortunately, literature is currently lacking empirical evidence on the impact of energy efficiency solutions on production. Thus, this work primarily aims at investigating the economic and production-related influence on the reduction in industrial energy consumption, considering the cross-cutting technologies HVAC, motors, lighting systems and air compressor systems. The analysis is performed using data from previous studies that characterized the main EE measures for the cross-cutting technologies. Four logistic models were built to understand how costs and production influence energy efficiency across such cross-cutting technologies. In this way, motivating industries to implement measures to reduce electrical consumption, offering an economic cost–benefit analysis and optimizing industry processes so that the reduction in electricity consumption adds to industrial energy efficiency were the aims of this study. The results of this work show through the adjusted indicators that senior management is mainly responsible for energy savings. The operational measures of each piece of equipment can be oriented in the industry towards a specific maintenance process for each technology, becoming an active procedure in industrial productions to obtain EE. Additionally, maintenance planning and control is essential to the reliability of the reduced energy consumption of cross-cutting technologies. This article concludes with managerial implications and suggestions for future research in this field.

Highlights

Introduction iationsThe increase in greenhouse gas emissions related to the increased energy demand is one of the main global socio-environmental concerns and is calling for increased energy efficiency capable of reducing costs and protecting the environment [1,2]
It is possible to have an overview of the unique characteristics of EEMs that industrial decision-makers consider a clear opportunity to face the implementation of measures that reduce energy consumption
The best adjusted logistic regression models, after selecting the indicators, went through the steps detailed in Section 3.2 (F Test, error estimate, and p value), Section 3.3 (Anova, Akaike information criterion (AIC), McFadden’s Pseudo-R2, and Accuracy) and Section 3.4, as Table 3 shows

Summary

Introduction

The increase in greenhouse gas emissions related to the increased energy demand is one of the main global socio-environmental concerns and is calling for increased energy efficiency capable of reducing costs and protecting the environment [1,2]. The challenge is to make constant economic growth follow technological development, which supplies the ever-increasing demand for energy. In 2020, it was responsible for 38% (156EJ) of the total global final energy use, representing an average increase of 1% in energy consumption in the period 2010 to 2019, in some regions, as a result of COVID-19, there was a 1.6%. Efficient energy consumption is necessary for improving environmental and financial indicators [5,6], leading to an energy improvement in operations and maintenance of the work environment [7,8]. Improving energy consumption becomes an Licensee MDPI, Basel, Switzerland

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