Dissertation Defence: Developing a Multicriteria Feasibility Assessment Model for Hemp-based Biocomposite Supply Chains incorporating Techno-Economic, Environmental, and Social Measures: A Case Study

Niloofar Akbariansaravi, supervised by Dr. Abbas S. Milani and Dr. Taraneh Sowlati, will defend their dissertation titled “Developing a Multicriteria Feasibility Assessment Model for Hemp-based Biocomposite Supply Chains incorporating Techno-Economic, Environmental, and Social Measures: A Case Study” in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mechanical Engineering.

An abstract for Niloofar Akbariansaravi’s dissertation is included below.

Examinations are open to all members of the campus community as well as the general public. Registration is not required for in-person exams.

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ABSTRACT

Bio-based materials, particularly 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. Although prior research has concentrated on sustainability assessments related to material and supplier selection, often highlighting mechanical and economic properties, there has been limited focus on evaluating pre-processing decisions from a sustainability perspective.

This dissertation aims to evaluate different biomass collection and pre-processing equipment configurations through a case study in Saskatchewan, Canada, to identify the most sustainable operational options within a hemp-based biocomposites supply chain. To achieve this goal, a novel sustainable decision-making framework is proposed in three phases, that integrate economic, environmental, social, 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 range. In the second phase, environmental impacts of the scenarios are assessed using an attributional Life Cycle Assessment tool. 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 (ANP) model is employed with interdependencies among criteria and alternatives. To assess the robustness of the alternatives’ rankings from the ANP model, a sensitivity analysis using Non-Linear Programming model is developed. This model identifies minimal changes in criteria weights needed to alter rankings of each alternative. Results show that the proposed framework effectively selects best hemp pre-processing equipment (namely hammer mills and balers) by introducing sustainable metrics. Incorporating “interdependencies” among criteria and alternatives enhances the solution’s robustness, as validated by the sensitivity model compared to the conventional Analytical Hierarchy Process. Ultimately, this ANP-based supply chain framework could adapt to various biocomposite contexts and production regions by modifying input data, broadening its impact.