Measuring and verification of energy savings by statistical learning in manufacturing environments

Autores: Noelia Osés Fernández Aritz Legarretaetxebarria Torrealda Marco Quartulli Igor García Olaizola Mikel Serrano

Fecha: 26.11.2015


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Abstract

Industry 4.0 methodological advancements based on continuous analytics and on the sensorization of manufacturing lines make it possible to design and develop integrated systems for measurement and verification of the impact of implemented energy conservation measures (ECM) in industrial plants. The pilot study presented here has focused on developing a model of the energy consumption of the injection machines in the plant to be used to calculate the adjusted baseline. The energy savings are calculated by comparing the post-ECM energy consumption to the adjusted baseline.

BIB_text

@Article {
title = {Measuring and verification of energy savings by statistical learning in manufacturing environments},
keywds = {

measuring and verification, adjusted baseline calculation


}
abstract = {

Industry 4.0 methodological advancements based on continuous analytics and on the sensorization of manufacturing lines make it possible to design and develop integrated systems for measurement and verification of the impact of implemented energy conservation measures (ECM) in industrial plants. The pilot study presented here has focused on developing a model of the energy consumption of the injection machines in the plant to be used to calculate the adjusted baseline. The energy savings are calculated by comparing the post-ECM energy consumption to the adjusted baseline.


}
isbn = {978-2-9548927-1-9},
date = {2015-11-26},
year = {2015},
}
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