The optimization of overhead hoist transport (OHT) systems in semiconductor manufacturing plays a crucial role in improving production efficiency. In this study, the development of a discrete event simulation model to analyze the physical and control characteristics of an OHT system is presented, focusing on building a modular simulation framework for evaluating operational strategies by applying various optimization techniques. Additionally, a step-by-step analysis is introduced to optimize OHT operation using the developed model. The simulation model is broadly divided into three parts according to their purposes. The physical system encompasses the physical entities such as the equipment and vehicles. The experimental frame comprises a generator, which triggers experiments, and a result analyzer. Finally, the system controller is structured hierarchically and consists of an upper layer, known as the manufacturing control system, and subordinate layers. The subordinate layers are modularly divided according to their roles and encompass a main controller responsible for OHT control and a scheduling agent manager for dispatching and routing based on SEMI commands. The proposed simulation model adopts a structure based on the discrete event systems specification (DEVS). Since the hierarchical system controller may face challenges such as computational overhead and adaptability issues in real-world implementation, the modular design based on DEVS is utilized to maintain independence between layers while ensuring a flexible system configuration. Through an exploratory analysis using the simulation model, we adopt a step-by-step approach to optimize the OHT operation. The optimal operation is achieved by identifying the optimal number of OHT units and pieces of equipment per manufacturing zone. The results of the exploratory analysis for the three scenarios validate the effectiveness of the proposed framework. Increasing the number of OHT units beyond 17 resulted in only a 0.08% reduction in lead time, confirming that 17 units is the optimal number. Additionally, by adjusting the amount of equipment based on their utilization rates, we found that reducing the amount of equipment from 12 to five in process E-1 and from seven to three in the OUT process did not degrade performance. The proposed simulation framework was thus validated as being effective in evaluating OHT operational efficiency and useful for analyzing key performance indicators such as OHT utilization rates. The proposed model and analysis method effectively model and optimize OHT systems in semiconductor manufacturing, contributing to improved production efficiency and reduced operational costs. Furthermore, this work can bridge the gap between theoretical modeling and practical complexities in semiconductor logistics.

The need for certification standards for new convergence products, such as a smart LED streetlight system, has been identified as a critical issue. This study proposes simulation modeling for smart LED streetlight systems and suggests three certification standards: the minimum time to initiate dimming-up, the duration of the dimming-up period, and the number of concurrently controlled streetlights. We utilized Relux to model streetlights and roads in terms of luminance levels, and used analytical formulas to compute the braking distances of oncoming vehicles. The two models were integrated into a smart LED streetlight system model using Simio. Simulation experiments were conducted with two objectives: to provide certification standards, and to apply and verify them in real-world cases. We experimented with 630 scenarios, modeling various dynamic situations involving roads and vehicles, and applied the model to two actual roads in the Republic of Korea to test its validity. The model was subsequently applied to roads for which traffic-volume data were available, to determine potential energy savings. The proposed simulation method can be applied to a smart LED streetlight system and to new products that lack certification standards. Furthermore, the proposed certification standards offer alternative approaches to operating streetlight systems more efficiently.

Demand-responsive transport (DRT) provides flexible ride-sharing by dynamically adjusting routes based on real-time user demand, making it suitable for complex urban mobility needs. This study proposes a modular simulation framework based on the DEVS (Discrete Event System Specification) formalism and introduces an “express service” strategy that enables direct trips without intermediate stops. The framework supports scenario-based analysis using key performance indicators (KPIs) and allows for flexible testing of operational strategies. Two experiments were conducted: the first validated the simulation model under varying demand and fleet conditions; and the second assessed the impact of the express service. Results showed that express passengers experienced significantly shorter waiting and riding times, while standard passenger service remained stable. The strategy also improved operational efficiency under constrained resources. This study contributes to a configurable simulation platform for evaluating differentiated DRT services and provides practical insights for adaptive service planning, especially in urban settings where tiered mobility solutions are increasingly needed.