A Robust Analytical Network Process for Biocomposites Supply Chain Design: Integrating Sustainability Dimensions into Feedstock Pre-Processing Decisions

Niloofar Akbarian-Saravi, Taraneh Sowlati () and Abbas S. Milani ()
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Niloofar Akbarian-Saravi: Composites Research Network-Okanagan Laboratory, School of Engineering, The University of British Columbia, Kelowna, BC V1V 1V7, Canada
Taraneh Sowlati: Industrial Engineering Research Group, Department of Wood Science, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada
Abbas S. Milani: Composites Research Network-Okanagan Laboratory, School of Engineering, The University of British Columbia, Kelowna, BC V1V 1V7, Canada

Sustainability, 2025, vol. 17, issue 15, 1-33

Abstract: Natural fiber-based biocomposites are rapidly gaining traction in sustainable manufacturing. However, their supply chain (SC) designs at the feedstock pre-processing stage often lack robust multicriteria decision-making evaluations, which can impact downstream processes and final product quality. This case study proposes a sustainability-driven multicriteria decision-making framework for selecting pre-processing equipment configurations within a hemp-based biocomposite SC. Using a cradle-to-gate system boundary, four alternative configurations combining balers (square vs. round) and hammer mills (full-screen vs. half-screen) are evaluated. The analytical network process (ANP) model is used to evaluate alternative SC configurations while capturing the interdependencies among environmental, economic, social, and technical sustainability criteria. These criteria are further refined with the inclusion of sub-criteria, resulting in a list of 11 key performance indicators (KPIs). To evaluate ranking robustness, a non-linear programming (NLP)-based sensitivity model is developed, which minimizes the weight perturbations required to trigger rank reversals, using an IPOPT solver. The results indicated that the Half-Round setup provides the most balanced sustainability performance, while Full-Square performs best in economic and environmental terms but ranks lower socially and technically. Also, the ranking was most sensitive to the weight of the system reliability and product quality criteria, with up to a 100% shift being required to change the top choice under the ANP model, indicating strong robustness. Overall, the proposed framework enables decision-makers to incorporate uncertainty, interdependencies, and sustainability-related KPIs into the early-stage SC design of bio-based composite materials.

Keywords: biocomposites; sustainability by design; pre-processing equipment selection; analytic network process; scenario analysis; optimization-driven sensitivity analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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