Material requirements planning (MRP) is one of the main production planning approaches implemented in enterprise resource planning systems, and one that is broadly applied in practice. In this paper, a multi-stage and multi-item production system is simulated by considering random customers’ demands and other sources of uncertainty.
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.
In this paper, the researchers study the operations of an imaginary coffee shop with a focus on the barista’s actions. They also show how the sequence of actions affects the overall performance of the coffee shop by using reinforcement learning and simulation as its policy training environment. This model acts as a guiding example that shows the ease of applying RL in AnyLogic models using the Pathmind Library.
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.