Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods

Some (non)manufacturing industries are becoming more energy efficient, but many of them are losing cost-effective energy-savings opportunities, namely, by lack of knowledge or underestimation of good engineering and management practices as well as guidance on techniques or tools for that purpose. Th...

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Main Authors: Nuno Costa, Paulo Fontes
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/12/18/7603
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spelling doaj-6ef0762573f94a4c955edf9499e64ede2020-11-25T03:16:31ZengMDPI AGSustainability2071-10502020-09-01127603760310.3390/su12187603Energy-Efficiency Assessment and Improvement—Experiments and Analysis MethodsNuno Costa0Paulo Fontes1Instituto Politécnico de Setúbal/ESTSetubal, CINEA, UNIDEMI, 2900-001 Setúbal, PortugalInstituto Politécnico de Setúbal/ESTSetubal, CINEA, UNIDEMI, 2900-001 Setúbal, PortugalSome (non)manufacturing industries are becoming more energy efficient, but many of them are losing cost-effective energy-savings opportunities, namely, by lack of knowledge or underestimation of good engineering and management practices as well as guidance on techniques or tools for that purpose. This study points out that Design of Experiments is a tool that cannot be ignored by managers and other technical staff, namely, by those who have the responsibility to eliminate energy waste and promote energy-efficiency improvement in industry, mainly in energy-intensive manufacturing industries. A review on Design of Experiments for physical and simulation experiments, supported on carefully selected references, is provided, since process and product improvement at the design and manufacturing stages increasingly rely on virtual tests and digital simulations. However, the expense of running experiments in complex computer models is still a relevant issue, despite advances in computer hardware and software capabilities. Here, experiments were statistically designed, and several easy-to-implement yet effective data analysis methods were employed for identifying the variables that must be measured with more accurate devices and methods to better estimate the energy efficiency or improve it in a billets reheating furnace. A simulation model of this type of furnace was used to run the experiments and the results analysis shows that variables with practical effect on the furnace’s energy efficiency are the percentage of oxygen in the combustion gases, the fuel flow in the burners, and the combustion air temperature.https://www.mdpi.com/2071-1050/12/18/7603computer experimentssustainabilityfurnacesimulationscreeningfactorial design
collection DOAJ
language English
format Article
sources DOAJ
author Nuno Costa
Paulo Fontes
spellingShingle Nuno Costa
Paulo Fontes
Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods
Sustainability
computer experiments
sustainability
furnace
simulation
screening
factorial design
author_facet Nuno Costa
Paulo Fontes
author_sort Nuno Costa
title Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods
title_short Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods
title_full Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods
title_fullStr Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods
title_full_unstemmed Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods
title_sort energy-efficiency assessment and improvement—experiments and analysis methods
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2020-09-01
description Some (non)manufacturing industries are becoming more energy efficient, but many of them are losing cost-effective energy-savings opportunities, namely, by lack of knowledge or underestimation of good engineering and management practices as well as guidance on techniques or tools for that purpose. This study points out that Design of Experiments is a tool that cannot be ignored by managers and other technical staff, namely, by those who have the responsibility to eliminate energy waste and promote energy-efficiency improvement in industry, mainly in energy-intensive manufacturing industries. A review on Design of Experiments for physical and simulation experiments, supported on carefully selected references, is provided, since process and product improvement at the design and manufacturing stages increasingly rely on virtual tests and digital simulations. However, the expense of running experiments in complex computer models is still a relevant issue, despite advances in computer hardware and software capabilities. Here, experiments were statistically designed, and several easy-to-implement yet effective data analysis methods were employed for identifying the variables that must be measured with more accurate devices and methods to better estimate the energy efficiency or improve it in a billets reheating furnace. A simulation model of this type of furnace was used to run the experiments and the results analysis shows that variables with practical effect on the furnace’s energy efficiency are the percentage of oxygen in the combustion gases, the fuel flow in the burners, and the combustion air temperature.
topic computer experiments
sustainability
furnace
simulation
screening
factorial design
url https://www.mdpi.com/2071-1050/12/18/7603
work_keys_str_mv AT nunocosta energyefficiencyassessmentandimprovementexperimentsandanalysismethods
AT paulofontes energyefficiencyassessmentandimprovementexperimentsandanalysismethods
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