TY - GEN
T1 - The Cost of Quality in Circular Economy
T2 - 12th International Conference on Control, Decision and Information Technologies, CoDIT 2026
AU - Yahiaoui, Niama
AU - Trochu, Julien
AU - Chaabane, Amin
AU - Larbi, Rim
AU - Jabbarzadeh, Armin
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - The management of Construction, Renovation, and Demolition (CRD) waste faces challenges due to low material sortability and limited effectiveness of manual sorting, which lead to impurity rates and financial losses. This study proposes the integration of Industry 4.0 technologies, AI-driven computer vision and robotic sorting into a Reverse Logistics Network Design (RLND) under uncertainty. We develop a two-stage stochastic Mixed-Integer Quadratically Constrained Program (MIQCP) to model the nonlinear relationship between investment and sorting efficiency, using a cost of quality function to reflect diminishing returns. To address the non-convexity of the model, a McCormick linearization approach is employed with Gurobi optimizer. Results from a case study in Quebec demonstrate that AI-enabled sorting improves effective recycling rates from a baseline of 0.47-0.58 to 0.72-0.85. However, this transition results in an 11.1% reduction in short-term profitability. These results illustrate the cost of quality required to guarantee the high-purity recycled materials necessary for a sustainable circular economy.
AB - The management of Construction, Renovation, and Demolition (CRD) waste faces challenges due to low material sortability and limited effectiveness of manual sorting, which lead to impurity rates and financial losses. This study proposes the integration of Industry 4.0 technologies, AI-driven computer vision and robotic sorting into a Reverse Logistics Network Design (RLND) under uncertainty. We develop a two-stage stochastic Mixed-Integer Quadratically Constrained Program (MIQCP) to model the nonlinear relationship between investment and sorting efficiency, using a cost of quality function to reflect diminishing returns. To address the non-convexity of the model, a McCormick linearization approach is employed with Gurobi optimizer. Results from a case study in Quebec demonstrate that AI-enabled sorting improves effective recycling rates from a baseline of 0.47-0.58 to 0.72-0.85. However, this transition results in an 11.1% reduction in short-term profitability. These results illustrate the cost of quality required to guarantee the high-purity recycled materials necessary for a sustainable circular economy.
KW - Circular economy
KW - Construction waste
KW - Cost of quality
KW - McCormick linearization
KW - MIQCP
KW - Reverse logistics
KW - Stochastic optimization
UR - https://www.scopus.com/pages/publications/105047833417
U2 - 10.1109/CoDIT70676.2026.11630888
DO - 10.1109/CoDIT70676.2026.11630888
M3 - Contribution to conference proceedings
AN - SCOPUS:105047833417
T3 - 12th 2026 International Conference on Control, Decision and Information Technologies, CoDIT 2026
SP - 2730
EP - 2735
BT - 12th 2026 International Conference on Control, Decision and Information Technologies, CoDIT 2026
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 13 July 2026 through 16 July 2026
ER -