Multi-objective optimal design of sustainable products and systems under uncertainty

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dc.contributor.authorAfshari, Hamid
dc.contributor.examiningcommitteeKuhn, David (Mechanical Engineering) Leung, Carson (Computer Science) Zeng, Yong (Information Systems Engineering, Concordia University)en_US
dc.contributor.supervisorPeng, Qingjin (Mechanical Engineering)en_US
dc.date.accessioned2016-12-15T16:05:57Z
dc.date.available2016-12-15T16:05:57Z
dc.date.issued2016en_US
dc.date.issued2016en_US
dc.date.issued2016en_US
dc.date.issued2015en_US
dc.date.issued2016en_US
dc.date.issued2016en_US
dc.date.issued2015en_US
dc.date.issued2014en_US
dc.date.issued2013en_US
dc.degree.disciplineMechanical Engineeringen_US
dc.degree.levelDoctor of Philosophy (Ph.D.)en_US
dc.description.abstractSustainable approaches have been extensively proposed in product, process and system levels. However, a lack of applicable solutions for these methods is identified in the existing research. This research considers uncertainties affecting sustainable systems and comprehensively discusses the need for the optimal design in product and system levels under uncertainty. Based on the economic, social and environmental requirements of a sustainable product, and uncertainties in engineering systems, two innovative methods are proposed. The methods, including agent-based modeling (ABM) and Big Data, quantify effects of users’ preference changes as a significant uncertainty source in a product design process. The effect of quantified uncertainties on the product sustainability is then evaluated, and solutions to reduce the effects are developed. Through a novel control engineering method, uncertainties are modeled in the design process of a product. Using two mathematical models, the cost and environmental impacts in the design process are minimized under users’ preference changes. The models search for an optimal number of iterations in the design process to achieve a sustainable solution. The methods have been extended to model and optimize the sustainable system design under uncertainties. Design of Eco-Industrial Parks (EIPs) is a practical and scientific solution to achieve sustainable industries. To improve the feasibility of flow exchanges between industries in an EIP under several uncertainties, this research provides a perspective analysis for establishing flow exchanges between industries. The sources of uncertainties in the EIPs are then comprehensively studied, and research gaps are highlighted. Finally, models to optimize flow exchanges between industries are presented and the validity of models is evaluated using real data. A major is including all sustainability pillars in the proposed approach. The research addresses users’ preferences to highlight the role of individuals in the society. Moreover, the economic and environmental objective functions have been considered for optimal decision making in the design process. This research underlines the role of uncertainty studies in the sustainable system design. Multiple classifications, perspective analysis, and optimization objectives are presented to help decision makers with the optimal design of sustainable systems under uncertainties.en_US
dc.description.noteFebruary 2017en_US
dc.identifier.citationAfshari H, Farel R, Peng Q, “Improving the Resilience of Energy Flow Exchanges in Eco-Industrial Parks: Optimization under Uncertainty”, Accepted paper in the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems. December 2016.en_US
dc.identifier.citationAfshari H, Peng Q, Gu, P, 2016, “Design Optimization for Sustainable Products under Users’ Preference Changes”, The ASME Journal of Computing and Information Science in Engineering. doi:10.1115/1.4033234.en_US
dc.identifier.citationAfshari H, Peng Q, 2016, “Reducing Effects of Design Uncertainties on Product Sustainability”, Cogent Engineering (Taylor and Francis), 3: 1231388.en_US
dc.identifier.citationAfshari H, Peng Q, 2015, “Modeling and Quantifying Uncertainty in the Product Design Phase for Effects of User Preference Changes”, Industrial Management & Data systems, 115(9):1637 - 1665.en_US
dc.identifier.citationAfshari H, Farel R, Peng Q, 2016, “Need for Optimization under Uncertainty: Designing Flow Exchanges in Eco-Industrial Parks”, Proceeding of the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2016, Charlotte, NC, USAen_US
dc.identifier.citationAfshari H, Farel R, Gourlia J-P, Peng Q, 2016, “Energy symbioses in Eco-Industrial Parks: Models and Perspectives”, Proceedings of the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2016, Charlotte, NC, USAen_US
dc.identifier.citationAfshari H, Peng Q, 2015, “Using Big Data to Minimize Uncertainty Effects in Adaptable Product Design”, Proceedings of the International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2015, Boston, MA, USAen_US
dc.identifier.citationAfshari H, Peng Q, 2014, “Modeling Evolution of Uncertainty in Sustainable Product Design”, Proceedings of the International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2014, Buffalo, NY, USAen_US
dc.identifier.citationAfshari H, Peng Q, Gu P, 2013,“An Agent-based Technique to Investigate Customers’ Preference in Product Lifecycle”, Proceedings of the ASME 2013 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2013, Portland, Oregon, USAen_US
dc.identifier.urihttp://hdl.handle.net/1993/31959
dc.language.isoengen_US
dc.publisherAmerican Society of Mechanical Engineering (ASME)en_US
dc.publisherAmerican Society of Mechanical Engineering (ASME)en_US
dc.publisherTaylor and Francisen_US
dc.publisherEmerald Publishingen_US
dc.publisherAmerican Society of Mechanical Engineering (ASME)en_US
dc.publisherAmerican Society of Mechanical Engineering (ASME)en_US
dc.publisherAmerican Society of Mechanical Engineering (ASME)en_US
dc.publisherAmerican Society of Mechanical Engineering (ASME)en_US
dc.publisherAmerican Society of Mechanical Engineering (ASME)en_US
dc.rightsopen accessen_US
dc.subjectProduct Design, Sustainability; Optimization under uncertainty; Eco-industrial Parksen_US
dc.titleMulti-objective optimal design of sustainable products and systems under uncertaintyen_US
dc.typedoctoral thesisen_US
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