Efficient scheduling and resource allocation in dental prosthesis supply chains are critical for improving patient outcomes and reducing turnaround times. Traditional workflows often suffer from delays due to fragmented routing, clinic bottlenecks, and limited visibility across production stages. To address these challenges, we develop a mixed-integer linear programming (MILP) model that jointly optimizes patient scheduling, routing decisions, and capacity constrained resource allocation in a digitally enabled, 3D printing-based prosthesis workflow. The model incorporates patient routing decisions (direct-to-lab vs. via-clinic), lab capacity constraints, material availability, and fixed delivery delays. The model minimizes lead time while enforcing fairness through worst-case constraints and deterministic delivery assumptions. Results from a baseline scenario involving 850 patients across a 45-day planning window show that the optimized system achieves balanced lab utilization, equitable lead time distribution, and full satisfaction of routing constraints. Comparative analysis highlights the significant advantage of direct-to-lab workflows over clinic-mediated routes. Scenario-based sensitivity analyses reveal the impact of routing strategies, inventory thresholds, and delivery penalties on system performance. The study demonstrates how simulation-informed optimization can guide strategic planning in healthcare logistics, offering a reproducible and adaptable framework for real-world deployment.

@article{janetkwakye-2026-1718,
  title={Optimizing Patient Scheduling and Resource Allocation in a 3D Printing-Enabled Dental Prosthesis Supply Chain: A Mixed-Integer Linear Programming Approach},
  author={Janet  Kwakye and Hansuk  Sohn},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2026},
  volume={19},
  number={1},
  pages={93--113},
  doi={10.31387/oscm0640509}
}

Janet  Kwakye, Hansuk  Sohn (2026). Optimizing Patient Scheduling and Resource Allocation in a 3D Printing-Enabled Dental Prosthesis Supply Chain: A Mixed-Integer Linear Programming Approach. Operations and Supply Chain Management: An International Journal, 19(1), 93-113. https://doi.org/10.31387/oscm0640509