Economic and Production-Related Implications for Industrial Energy Efficiency: A Logistic Regression Analysis on Cross-Cutting Technologies
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Data
2022-02-01
Autores
Neves, Fábio de Oliveira [UNESP]
Ewbank, Henrique
Roveda, José Arnaldo Frutuoso [UNESP]
Trianni, Andrea
Marafão, Fernando Pinhabel [UNESP]
Roveda, Sandra Regina Monteiro Masalskiene [UNESP]
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Resumo
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.
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Economic and production-related indicators, Energy efficiency, Implications in the industrial sector, Logistic regression, Technological gap
Como citar
Energies, v. 15, n. 4, 2022.