This thesis work presents a new integrated framework to connect the economic, environmental and social factors, and to analyze sustainability performance of the system by balancing these factors. Sustainable manufacturing systems should be profitable and environmentally friendly while being safe both physically and socially for everyone in the system. This thesis work highlights the main aspects and requirements of sustainability, which are related to manufacturing systems, demonstrating that there are other aspects of sustainability in general that are not reflective on manufacturing. This work also highlights many useful assessment indices of manufacturing sustainability, which makes quantification, and then comparison and optimization of system performance possible. A comparative study on the existing sustainability assessment tools is performed to classify these tools based on appropriateness to manufacturing systems and limitations by reviewing the significant research work in system modeling for assessing and optimizing manufacturing sustainability. The review has revealed that the triple bottom line TBL factors, economic, social and environmental, are difficult to evaluate and optimize simultaneously due to the complex nature of manufacturing systems and the wide variety of processes and type of the system. Furthermore, the review has demonstrated that there is significant research gap in considering social sustainability for overall sustainability characterization. The consideration and the integration of social sustainability with other factors make this framework unique and more functional. Three case studies have been conducted to understand the applicability of this novel framework. The first case study reveals the difficulties associated with achieving social sustainability as most of the parameters in social sustainability are intangible in nature that’s why it is difficult to optimize the parameters associated with social sustainability. The last two case studies are analyzed to evaluate the sustainability in oil and gas industry with the help of fuzzy interference modelling. Fuzzy interference modelling is the core unit of decision making and mathematical reasoning of the sustainability assessment simulation, when the outcomes are uncertain. The modelling is built with the help of triangle membership functions to fuzzify the variables. Fuzzy rules like ‘IF THEN’ along with operators “OR” or “AND” then come into play for generating necessary decision rules. In this work, these decision rules aggregately simulate and generate the overall sustainability assessment results for case studies 2 and 3. All case studies strongly demonstrate the pragmatic and facile application of the proposed framework to assess the overall sustainability in continuous manufacturing context. Finally, the scope of future research work is also presented for the proposed novel framework.
University of Minnesota M.S.E.M. thesis. June 2018. Major: Mechanical Engineering. Advisor: Tarek Al-Geddawy. 1 computer file (PDF); v, 114 pages.
An Assessment and Simulation Methodology of Sustainability in Manufacturing System.
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