Factory eco-efficiency modelling: data granularity and performance indicators

Date

2017-03-20

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Journal Title

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Volume Title

Publisher

Elaevier

Department

Type

Article

ISSN

2351-9789

Format

Free to read from

Citation

Aanand Davé, Peter Ball, Konstantinos Salonitis, Factory Eco-Efficiency Modelling: Data Granularity and Performance Indicators, Procedia Manufacturing, Volume 8, 2017, pp479-486

Abstract

Eco-efficiency is becoming an increasingly important performance measure. Currently manufacturers rely on reactive methods such as auditing for assessment. There are still significant theoretical and practical barriers including a lack of knowledge regarding the selection and composition of appropriate data granularities, model quality to improve decision making, and split incentives between facilities and manufacturing asset management. The purpose of this paper is to show the application of an eco-efficiency modelling framework in the case of a fast-moving consumer goods factory. The framework composes resource and production data. These are analysed with respect to three data granularity factors, asset subdivision, time-step, and resource magnitude. Modelling is used to represent asset eco-efficiency across available subdivisions using performance indicators.

Description

Software Description

Software Language

Github

Keywords

Factory, Eco-efficiency, Modelling, Data Granularity Framework, Data Composition, Simulation

DOI

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