Academic articles

Simulated-Based Analysis of Recovery Actions under Vendor-Managed Inventory Amid Black Swan Disruptions in the Semiconductor Industry: a Case Study from Infineon Technologies Ag

Through simulation modeling, this research highlighted the interactions of key system parameters in a disruption phase under different scenarios. A multi-period, multi-echelon serial supply chain was studied with agent-based and discrete-event simulation.

Energy-Efficient Semiconductor Manufacturing: Establishing an Ecological Operating Curve

The semiconductor industry is facing pressure to reduce its extensive energy consumption, which requires transparency on the relationship between energy efficiency and original planning objectives. This paper aims to develop an extension to the existing Operating Curve concept by investigating the effect of utilization on energy efficiency. It uses the results of discrete-event simulation on a fab level to verify the novel concept.

Data-Driven Simulation for Production Balancing and Optimization: a Case Study in the Fashion Luxury Industry

As widely reported in the literature, the leather luxury accessories industry is characterized by a highly fragmented supply chain. Frequent changes in the production mix had to be managed, often requiring the re-optimization or even re-design of production flows. The objective of this paper was to propose a data-driven simulation model for production balancing and optimization in this sector.

Applying a Hybrid Model to Solve the Job-Shop Scheduling Problem with Preventive Maintenance, Sequence-Dependent Setup Times, and Unknown Processing Times

The job-shop scheduling problem was considered with sequence-dependent setup times and preventive maintenance constraints. A hybrid model combining discrete-event simulation and an optimization algorithm in Python was applied to simulate the production process and solve the job-shop problem.

Simulation Model of a Multi-Hospital Critical Care Network

A discrete event simulation model was developed for a network of eight major intensive care units (ICUs) as well as high-acuity units (HAUs) in British Columbia, Canada. The simulation model will be used to develop strategies for managing the combined impacts of COVID-19 and seasonal influenza without the need for extensive public health interventions to limit transmission.

A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics

Demands for health care are becoming overwhelming for healthcare systems around the world regarding the availability of resources, particularly in emergency departments (EDs). This paper provides a case study of the Uppsala University Hospital, where a data-driven simulation model was designed to examine the current state of the patient flow and to investigate potential logistics solutions for improving that flow through a novel strategy.

Applying Simulation to Estimate Waiting Times and Optimize the Booking Size for Oversea Transportation Vessels

This study investigates a different source of uncertainty, which is the waiting time for the next vessel that is scheduled on a specific route, connecting two international ports. The aim of this research was to determine the booking size for vessels in oversea delivery to minimize transportation costs. The simulation model and all the respective processes included in the oversea supply chain were developed in AnyLogic with a discrete-event paradigm.