University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Sustainability indicators for industrial ovens and assessment using Fuzzy set theory and Monte Carlo simulation

Pask, F, Lake, P, Yang, A, Tokos, H and Sadhukhan, J (2016) Sustainability indicators for industrial ovens and assessment using Fuzzy set theory and Monte Carlo simulation Journal of Cleaner Production.

[img] Text
Sustainability indicators for industrial ovens v18 REVISED.docx - Accepted version Manuscript
Restricted to Repository staff only until 12 October 2017.
Available under License : See the attached licence file.

Download (180kB)
[img]
Preview
Text (licence)
SRI_deposit_agreement.pdf
Available under License : See the attached licence file.

Download (33kB) | Preview

Abstract

Industrial ovens play a significant role in many manufacturing and process industries. Despite the desire to enhance sustainability throughout this sector, research looking to improve the sustainability of industrial ovens is in its infancy. This paper presents seven sustainability indicators to assess potential oven investment; these include system air flow, production efficiency, operating costs, quality, capital investment, toxicity and employment opportunity. The indicators are straightforward, can be scored with readily available data and have been weighted by industrial experts. A hybrid multi-criteria approach using Fuzzy set theory and Monte Carlo simulation has been developed to help evaluate the sustainability of alternative improvement options. The approach is required as previous methodologies only present desirability as a singular figure; and therefore decision makers are not provided with sufficient information on associated risk. The presented approach incorporates uncertainty throughout, and gives option desirability in terms of mean, standard deviation and variance. The risks using this method are better understood and can significantly aid industrial decision makers. The sustainability indicators and hybrid approach have been demonstrated using a case study in the manufacturing industry; to identify the most sustainable way to increase cure conversion within an oven. Amongst the three options: increasing oven size, increasing oven temperature and new product formulation, increasing oven temperature shows the highest desirability, while new product formulation though has a lower desirability has the highest certainty. Furthermore, a cumulative desirability distribution plot gives a basis to select option that is aligned with the business's risk strategy.

Item Type: Article
Subjects : Environment
Authors :
AuthorsEmailORCID
Pask, FUNSPECIFIEDUNSPECIFIED
Lake, PUNSPECIFIEDUNSPECIFIED
Yang, AUNSPECIFIEDUNSPECIFIED
Tokos, HUNSPECIFIEDUNSPECIFIED
Sadhukhan, JUNSPECIFIEDUNSPECIFIED
Date : 12 October 2016
Identification Number : https://doi.org/10.1016/j.jclepro.2016.10.038
Copyright Disclaimer : © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords : Sustainability indicators, Fuzzy set theory, Monte Carlo simulation, Industrial ovens, Manufacturing
Depositing User : Symplectic Elements
Date Deposited : 28 Oct 2016 07:29
Last Modified : 28 Oct 2016 07:29
URI: http://epubs.surrey.ac.uk/id/eprint/812648

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800