An integrative production-delivery system with mobile additive manufacturing and truck-drone delivery considering optimal printing sequence and preferred delivery time window

Mobile additive manufacturing (MAM) involves deploying 3D printing in moving vehicles and has recently garnered significant attention from academia and industry. However, no prior work integrates MAM with truck-drone delivery systems to support daily operations, despite the benefits to supply chain management. This paper fills this gap by integrating these technologies, considering customer delivery time windows and optimal printing sequences. A mixed-integer linear programming model is proposed to establish this innovative mechanism. Both exact (CPLEX) and heuristic (Lagrangian relaxation algorithm) approaches are utilized and compared to solve the model. Computational studies validate the model and solution methods across various problem sizes (small, medium, and large), showing the superior performance of Lagrangian relaxation in optimality gap and CPU time. The model is then applied in a case study using the Lagrangian relaxation algorithm. Results indicate that drone flight range and printing job complexity significantly impact cost performance and on-time delivery. Beyond achieving timely and cost-effective customer satisfaction, this system offers insights into supply chain resilience, enabling companies to enhance service quality and reduce inventory dependence through on-demand spare part production via MAM technology.