Factory eco-efficiency modelling: framework application and analysis

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dc.contributor.author Davé, Aanand
dc.contributor.author Salonitis, Konstantinos
dc.contributor.author Ball, Peter D.
dc.contributor.author Adams, Mark
dc.contributor.author Morgan, David
dc.date.accessioned 2016-08-05T15:19:21Z
dc.date.available 2016-08-05T15:19:21Z
dc.date.issued 2016-02-19
dc.identifier.citation Aanand Davé, Konstantinos Salonitis, Peter Ball, Mark Adams and David Morgan. Factory eco-efficiency modelling: framework application and analysis. Procedia CIRP, Volume 40, 2016, pp214-219. 13th Global Conference on Sustainable Manufacturing – Decoupling Growth from Resource Use en_UK
dc.identifier.issn 2212-8271
dc.identifier.uri http://dx.doi.org/10.1016/j.procir.2016.01.105
dc.identifier.uri https://dspace.lib.cranfield.ac.uk/handle/1826/10241
dc.description.abstract Eco-efficiency is becoming an increasingly important organisational 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 data granularity, model results quality 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 furniture-manufacturing 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. This paper contributes to industrial sustainability literature by applying a factory eco-efficiency modelling framework in a comparative study of the case company's cursory and detailed data. Facility, utility and manufacturing assets are modelled and analysed from logged data granularity factors. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution 4.0 International (CC BY 4.0) You are free to: Share — copy and redistribute the material in any medium or format, Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
dc.subject Factory en_UK
dc.subject Eco-efficiency en_UK
dc.subject Modelling en_UK
dc.subject Data Granularity Framework en_UK
dc.subject Data Composition en_UK
dc.subject Simulation en_UK
dc.title Factory eco-efficiency modelling: framework application and analysis en_UK
dc.type Article en_UK

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