In this paper, researchers used a discrete event simulation to evaluate the performance of outlier correction methods and extended the forecast generation process to increase forecast accuracy.
In this paper, researchers used a discrete event simulation to evaluate the performance of outlier correction methods and extended the forecast generation process to increase forecast accuracy.
This article introduces an innovative approach of risk and opportunity management to help managers in their decision-making processes. The proposed “physics of decision” approach enables managers to deal with the considered system’s performance trajectory by viewing and assessing the impact of potentialities (risks and opportunities).
The storage of electrical energy is becoming increasingly important to satisfy the demand through renewable energy sources. In this paper, a continuous and discrete simulation of a pumped thermal energy storage (PTES) system are compared with respect to their computational time and accuracy.
In this paper, researchers developed a discrete event simulation model of a Dutch phone and subscription retailer's queueing system. The goal of simulation modeling was to learn what improvements can be suggested to reduce the waiting time in shops.
This article focuses on the simulation model that was developed for Sibanye-Stillwater’s underground platinum mining operations in Nye, MT. The model was designed to help the mining company understand how bottlenecks move through their operations, to help identify which resources are constraining underground mining production increases, and to understand where capital investments are needed in backfill operations.
The Predictive Maintenance technique offers a possibility to improve productivity in semiconductor manufacturing. Current research on Predictive Maintenance mainly focuses on its technical implementation. By applying discrete-event simulation, the research team provide results on how maintenance strategies can help optimize machine operations, and how the technique contributes to an overall improvement of productivity in wafer fabrication.
In this work, the researchers undertake a root-cause enabling Vendor Managed Inventory performance measurement approach to assign responsibilities for poor performance. Additionally, the work proposes a solution methodology based on reinforcement learning for determining optimal replenishment policy in a VMI setting. Using a simulation model as a training environment, different demand scenarios are generated based on real data from Infineon Technologies AG and compared based on key performance indicators.
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.