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

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

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Critical Factors of the Application of Nanotechnology in Construction Industry by Using Anp Technique Under Fuzzy Intuitionistic Environment

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