Developing an ED Overcrowding Solution to Improve the Quality of Care

Overcrowding in the Emergency Department (ED) is one of the most important issues in healthcare systems. The lack of downstream beds can affect the quality of care for patients who need hospitalization after an ED visit.

This research proposes a generic simulation model as one of the ED overcrowding solutions to analyze patient pathways from the ED to hospital discharge. The model is adaptable for all pathologies and can include several hospitals within a healthcare network. To identify relevant pathways the research team conducts pathway analysis using Process Mining.

Logistics Network Analysis Model of E-Grocery Built with a Simulation Tool

The negative effects of traffic, such as air quality problems and road congestion, put a strain on the infrastructure of cities and high-populated areas. A potential measure to reduce these negative effects are grocery home deliveries (e-grocery), which can bundle driving activities and, hence, result in decreased traffic and related emission outputs.

This paper presents an agent-based simulation for logistics network analysis. The model built with a simulation tool assesses the impact of the e-grocery logistics network compared to the stationary one in terms of mileage and different emission outputs.

Patient Flow Management Policy Evaluation with Simulation Software

Healthcare is facing great challenges to make processes more efficient and meanwhile provide better service to patients. Management of the intensive care unit (ICU), which is one of the most critical departments in terms of patient status and patient flow, also tries to provide better service and reduce the mortality rate.

During COVID-19, effective and efficient management is of utmost importance. A patient flow model developed in AnyLogic simulation software allows a comprehensive evaluation of eleven different management policies for controlling ICU admissions when facing capacity shortages.

Data-Driven Predictive Modeling of Resource Utilization in Healthcare

The main objective of this paper is to provide a simulation-based decision-support tool for the healthcare industry. This tool will help the hospital management decide on resource utilization, in particular bed allocation, for the next few months. With it, hospitals could predict admissions and see how newly implemented policies impact the patient’s flow.

Simulating an Automated Breakpack System to Improve Warehouse Efficiency and Operations

This case study focuses on the simulation of a soon-to-be-implemented automation system within a Walmart Canada warehouse. This new system's aim is more efficient warehouse operations. Many stock-keeping units (SKUs) cannot be sent to retail stores in full case quantities. They are slow movers and would require individual stores to carry excessive inventory.

Breakpack is the process of breaking cases down to individual eaches (pieces) and combining them into mixed SKU cartons. Automating breakpack offers significant labor and quality savings, that are important to ensure efficient warehouse operations, but also a high degree of complexity.

Multi-agent Optimization of the Intermodal Terminal Main Parameters: Research Based on a Case Study

Due to numerous uncertainties such as bad weather conditions, frequent changes in the schedules of vessels, breakdowns of equipment, port managers are aiming at providing adaptive and flexible strategic planning of their facilities, especially intermodal terminals (dry ports).

This research shows that the combination of the agent-based modeling with other simulation approaches simplifies the process of designing simulation models and increases their visibility. The developed set of models allows the researchers to compute the balanced values of the parameters. Consequently, it helps achieve effective operation of a seaport – intermodal terminal system. The provided case study on one of the busiest ports in China proves the adequacy and validity of the developed simulation models.

Clinical Pathway Analysis using Process Mining and Predictive Modeling in Healthcare: an Application to Incisional Hernia

An incisional hernia (IH) is a ventral hernia that develops after surgical trauma to the abdominal wall, a laparotomy. IH repair is a common surgery that can generate chronic pain, decreased quality of life, and significant healthcare costs caused by hospital readmissions. The goal of this study is to analyze the clinical pathway of patients having an IH using a medico-administrative database and predictive modeling. Predictive modeling in healthcare is used, among other things, to understand the times of occurrence of complications and associated costs. It enables the simulation of what-if scenarios to propose an improved care pathway for patients who are the most exposed.

Tree and Network Product Structure Representations in Semiconductor Supply Chain Desing

Due to various production and market factors, flexibility is a key point in semiconductor manufacturing supply chain design. However, the increased complexity associated with this flexibility must be effectively managed to leverage the benefits that flexibility provides. The product structure is one of the main factors for enabling the desired result. Product structure representations in the supply chain design include linear, tree, and network. In this paper, the researchers explain the problem by a real case merger where risk and opportunities based on the choice of product structure representation in the supply chain design were relevant and no final solution initially was determined.

Work-In-Process Balancing Control in Global Fab Manufacturing Scheduling with Simulation Software

This paper addresses the problem of controlling the Work-In-Process (WIP) in semiconductor manufacturing by using a global scheduling approach and manufacturing scheduling software. A WIP balancing strategy is proposed to minimize the product mix variability in terms of throughput and cycle time. This strategy is enforced using a global scheduling optimization model which is formulated as a linear programming model. The global scheduling model is coupled with a generic multi-method simulation model built with manufacturing scheduling software for evaluation purpose.

Warehouse Optimization: Coordinated Control of Multi-zone Autonomous Vehicle Storage and Retrieval Systems, Conveyors, and Pick-up Operations

During recent years, Autonomous Vehicle Storage and Retrieval Systems (AVS/RS) have been widely applied in warehouse optimization to meet the increasing demand for rapid and flexible large-scale storage and retrieval tasks. This paper focuses on the operations control strategies with regard to the conveyor system, rack storage system, and pick-up system in order to maximize the system’s throughput capacity and minimize the storage/retrieval times of items. The study is based on a large-scale shoe manufacturer’s warehouse optimization and provides insights for system management.