Konferenzbeiträge

During the pandemic specialty physicians are working as frontline workers due to hospital overcrowding and a lack of providers. This places them as a high-risk target of the epidemic. Within these specialties, anesthesiologists are one of the most vulnerable groups as they come in close contact with the patient's airway.

An agent-based simulation model was developed using AnyLogic software to test various staffing policies within the anesthesiology department of the largest healthcare provider in Upstate South Carolina.

Hospital planning teams are always concerned with optimizing staffing and scheduling decisions in order to improve hospital performance, patient experience, and staff satisfaction. A multi-method approach including data analytics, modeling and simulation, machine learning, and optimization is proposed to provide a framework for smart and applicable solutions for staffing and shift scheduling. Factors regarding patients, staff, and hospitals are considered in the decision. This framework is piloted using the Emergency Department(ED) of a leading university hospital in Dublin.

This paper promotes a unique system dynamics-discrete event simulation hybrid modelling framework. The way the hybrid model is developed is intended to simplify the modelling process and make the framework flexible to a variety of situations. In the current study, the framework is used to investigate the success possibility of introducing within-shift job rotation in the plant and its optimal frequency. The intention is to reduce worker exhaustion and by so doing increase productivity and manufacturing throughput.

This research proposes and tests an integrated framework for bottom-up simulation of performance in construction projects. The proposed framework conceptualizes construction projects as systems-of-systems in which the abstraction and micro-simulation of dynamic behaviors are investigated at the base-level consisting of the following elements: human agents, information, and resources.

Agent-based modeling (ABM) has gained great popularity in recent years, especially in application areas where human behavior is important, because it opens up the possibility of capturing such behavior in great detail. Hybrid models which combine ABM with discrete-event simulation (DES) are particularly appealing in service industry applications.

This paper presents a comprehensive simulation project in the area of an automotive supplier. The company produces car styling serial and original accessory parts made from plastic for internal and external applications in passenger cars. For the foaming division, which is identified as the bottleneck, different personnel and qualification scenarios, set-up optimizations and lot-sizing strategies are compared with the current situation. Key performance measures reported are inventory, tardiness and service level. The changes in organizational costs (e.g. employee training, additional employees, etc.), due to the scenarios, are not considered and are traded off with the logistical potential by the company itself. Results of the simulation study indicate that a combination of an additional fitter during night shift, minor reductions of set-up times and reduced lot-sizes leads to an inventory reduction of ~10.6% and a service level improvement of ~8% compared to the current situation.