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Akbariansaravi, Niloofar

University of British Columbia

Biocomposites have become a significant sustainable alternative in green engineering. The production of biocomposites relies on strategic decisions regarding biomass collection and size reduction during pre-processing within the supply chain. This dissertation aims to evaluate different biomass collection and pre-processing equipment configurations in a case study of hemp-based biocomposites supply chain in Saskatchewan, Canada, to identify the most sustainable operational options. A novel sustainable decision-making framework is proposed in three phases, integrating economic, environmental, social (job opportunity), and technical considerations. The first phase employs a Techno-Economic Analysis tool to quantify the economic criteria of pre-processing scenarios, including Mean Net Present Value derived from Monte Carlo simulations, Net Present Value under Risk, and selling price ranges. The selling price is identified as the most influential factor, contributing 72%-78% to Net Present Value fluctuations. In the second phase, environmental impacts of the scenarios are assessed using an attributional Life Cycle Assessment tool. The cultivating and harvesting stage, linked to the use of biomass, fertilizers, and diesel fuels, is identified as a critical contributor to the environmental impact in all the important impact categories. Additionally, the social dimension is evaluated by estimating potential job creation associated with this biocomposite supply chain. Technical factors are captured by gathering industrial expert insights on product quality, system reliability, and Technology Readiness Levels (this dataset in particular included an Unreliability Factor). The outputs from the first two phases are used as the inputs for the third phase, for which an Analytic Network Process model is employed with interdependencies among criteria and alternatives. To assess the robustness of the alternatives’ rankings from the Analytic Network Process model, a sensitivity analysis using Non-Linear Programming is developed. Ultimately, the proposed framework effectively selects best hemp pre-processing equipment (namely half-screen hammer mill and round baler) by introducing sustainable metrics. Incorporating “interdependencies” among criteria and alternatives enhances the solution's robustness for decision-makers, as validated by the sensitivity model compared to the conventional Analytical Hierarchy Process. This Analytic Network Process-based supply chain framework could be adapted to various biocomposite contexts and production regions by modifying input data, broadening its impact.

Text

2025-01-16

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/90134

Mechanical Engineering

University of British Columbia

UBCO

http://creativecommons.org/licenses/by-nc-nd/4.0/