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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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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