Study a review of an academic paper on intralogistics optimization for a high-mix, low-volume production line. See why multimethod modeling is ideal for Industry 4.0 and which fleet configurations maximize utilization in both single-product and mixed-product scenarios.
As public transportation grows in popularity, congestion in multi-line subway hubs has become a major concern. This study presents a simulation model utilizing AnyLogic software to evaluate the performance of a subway transfer station in New York City by addressing challenges of inefficient passenger flow management. Leveraging the NYC turnstile usage data, the simulation incorporates passenger flow modeling to analyze movement patterns, identify bottlenecks, and evaluate potential solutions.
Explore how a training facility at Auburn University is teaching students and professionals lean manufacturing by assembling LEGO® cars. Through a multi-phase plan, the facility is evolving into a hub for digital manufacturing and Industry 4.0 technologies, with a focus on small and medium manufacturers (SMMs). The current phase involves creating an agent-based digital twin model to simulate and optimize assembly line processes.
This paper explores the automation of healthcare process modeling using process mining and simulation for Chronic Obstructive Pulmonary Disease (COPD) clinical pathways. By integrating AnyLogic’s agent-based simulation with real-world hospitalization data, the study is able to validate process-mined models. This approach optimizes patient flow analysis and supports data-driven decision-making in healthcare process automation.
This paper illustrates an emergency response simulation for out-of-hospital cardiac arrest (OHCA) incidents using agent-based modeling and GIS integration. The authors applied AnyLogic simulation software to evaluate dispatch strategies and responder deployment, with the goal of improving survival rates and enhancing urban emergency response efficiency.
This paper presents a framework that combines simulation with mathematical optimization to plan the supply of raw materials for producing specialty chemicals. A real-world use case was introduced to validate the developed framework, demonstrating the application of simulation in chemical industry logistics.
Efficient material replenishment in assembly plants can be optimized using autonomous mobile robots. This research analyzes the Tiger Motors assembly line at Auburn University, where a Stretch RE1 robot is integrated into the production process. A multimethod simulation model combining discrete-event and agent-based simulation modeling in AnyLogic evaluates different replenishment strategies. It identifies the most effective approach based on payload capacity, travel optimization, and real-time demand response.
This paper presents a tool for logistics optimization of Less-Than-Truckload terminals addressing rising service demands and shipment volumes. The tool enables efficient layout planning and resource allocation for small and medium-sized enterprises through automatic model generation and customizable simulation models.