In this paper, researchers focus on the real-time management of turnaround operations, and assess the relative merits and limitations of so-called dispatching rules.
The aircraft turnaround process consists of "ground handling operations" that are required to set an aircraft ready for its subsequent departure. This work focuses on enhancing the planning and real-time allocation of apron operations that are used to turn around an aircraft between two consecutive flights.
Simulation is one of the most used approaches to analyze semiconductor manufacturing systems. However, most simulation models are designed for single-use applications and study a limited set of problems that are not reusable afterwards. This paper proposes a generic, data-driven simulation model to evaluate and analyze a wide range of problems arising in modern semiconductor manufacturing systems.
This paper introduces a simulation study of interventions to ensure a stable supply of a generic medicine in Norway. A hybrid simulation modeling framework is proposed to evaluate the effect of alternative supply chain shortage interventions in response to various disruptions to support national decision making with respect to preparedness planning and emergency response.
Urban logistics is becoming increasingly important due to the global rise of e-commerce with home deliveries of small but frequent orders from consumers. The introduction of self-collection delivery systems is an innovation for last mile delivery operations in urban areas and brings new benefits. This paper introduces the application of hybrid modeling approach for the self-collection delivery costs optimization and estimation of future demand based on several socio-economic parameters.
Environmental sustainability is among the key concerns of our time. This study uses a multimethod simulation model to assess the impact of different e-grocery fulfillment strategies alongside the entire supply chain on sustainability metrics.
This paper proposes a simulation-based decentralized planning and scheduling approach to improve the performances of a job-shop production system, compliant with a semi-heterarchical Industry 4.0 architecture. To this extent, to face the increasing complexity of such a scenario, a parametric simulation model able to represent a wide number of job-shop systems is introduced.
In many industrial manufacturing companies, energy has become a major cost factor. Energy aspects are included in the decision-making system of production line planning and control to reduce manufacturing costs. For this priority, the simulation of production line processes requires not only the consideration of logistical and technical production factors but also the integration of time-dependent energy flows. A hybrid (multimethod) simulation shows the complex interactions between material flow and energy usage in production close to reality. This paper presents a simulation approach combining System Dynamics, Discrete-Event and Agent-Based Simulation for energy efficiency analysis in production, considering the energy consumption in the context of planning and scheduling operations.
Klein Mechanisch Werkplaats Eindhoven (KMWE) is a precision manufacturing company situated in the Netherlands and recently relocated to a new location known as the 'Brainport Industries Campus' (BIC). This move allowed KMWE to improve the performance of its manufacturing facility by investing in vertical automated storage and retrieval systems (AS/RSs). However, these decisions needed to be made under input uncertainties since the move to BIC and modernization of existing equipment would cause changes in operating parameters inside the facility.
In this study, the researchers show how hybrid simulation modelling was used in production planning optimization, in particular to assess the impact of input uncertainties (such as operator productivity, vertical storage height) on the throughput performance of TSC.
Emergency Room (Emergency Department) overcrowding is a pervasive problem worldwide, which impacts both performance and safety. Staff are required to react and adapt to changes in demand in real-time, while continuing to treat patients.
This paper employs a case study to propose a hybrid application of discrete-event simulation (DES) and time-series forecasting across multiple centers in an urgent care network as one of the emergency room overcrowding solutions. It uses seasonal ARIMA time-series forecasting to predict overcrowding in a near-future moving-window (1-4 hours) using data downloaded from a digital platform (NHSquicker). NHSquicker delivers real-time wait-times from multiple centers of urgent care in the South-West of England. Alongside historical distributions, this data loads the operational state of a real-time discrete-event simulation model at initialization.