Optimising Outpatient Pharmacy Staffing to Minimise Patients Queue Time using Discrete Event Simulation

Background: To remain relevant in the customer-oriented market, hospitals must pay attention to the quality of services and meet customers' expectations from admission to discharge stage. For an outpatient customer, pharmacy is the last unit visited before discharge. It is likely to influence patient satisfaction and reflect the quality of hospital's service. However, at certain hospitals, the waiting time is long. Resources need to be deployed strategically to reduce queue time. Objective: This research aims to arrange the number of staff (pharmacists and workers) in each station in the pharmacy outpatient service to minimise the queue time.Methods: A discrete simulation method is used to observe the waiting time spent at the pharmacy. The simulation run is valid and effective to test the scenario. Results: It is recommended to add more personnel for the non-compounding medicine and packaging to reduce the waiting time by 22.41%Conclusion: By adding personnel to non-compounding and packaging stations, the system performance could be improved. Cost-effectiveness analysis should be done to corroborate the finding. Keywords: Discrete Event Simulation, Hospital, Outpatient Service, Pharmacy Unit, System AnalysisBackground: To remain relevant in the customer-oriented market, hospitals must pay attention to the quality of services and meet customers' expectations from admission to discharge stage. For an outpatient customer, pharmacy is the last unit visited before discharge. It is likely to influence patient satisfaction and reflect the quality of hospital's service. However, at certain hospitals, the waiting time is long. Resources need to be deployed strategically to reduce queue time. Objective: This research aims to arrange the number of staff (pharmacists and workers) in each station in the pharmacy outpatient service to minimise the queue time.Methods: A discrete simulation method is used to observe the waiting time spent at the pharmacy. The simulation run is valid and effective to test the scenario. Results: It is recommended to add more personnel for the non-compounding medicine and packaging to reduce the waiting time by 22.41%Conclusion: By adding personnel to non-compounding and packaging stations, the system performance could be improved. Cost-effectiveness analysis should be done to corroborate the finding. Keywords:Discrete Event Simulation, Hospital, Outpatient Service, Pharmacy Unit, System Analysis

CONTROL MODEL FOR GROUND CREW SCHEDULING PROBLEM AT SMALL AIRPORTS: CASE OF SERBIA

Present-day airline industry is quite a competitive field and crew scheduling represents one of the crucial problems due to significant impact on the airline’s cost. The crew scheduling problem is based on the assignment of crew members to operate different tasks of route. The main goal of this paper is to provide an analysis and a solution to one of the biggest problems detected on a small airport in the Serbia - the problem of ground crew scheduling. The paper presents the main characteristics, goals and limitations of a real-life problem identified at this small airport. In order to solve the problem, we developed a dynamic discrete simulation model. The model is developed in a spreadsheet environment of Microsoft Excel. Some of the main limitations found in the development of the model are strong constraints and multiple goals. The model presented in the paper is designed as a useful management tool for smaller airports and is aimed at the improvement of operative processes.

Production Line Virtualization Process Using Plant Simulation Tool

The constant changes in the world generate demands for improvements in processes, either by reducing costs or increasing capacity. One of the most used methods today for process optimization is Discrete Simulation. This research presents a discrete simulation application, using the Tecnomatix Plant Simulation software to simulate a production line in the Manaus Industrial Pole. Mathematical modeling made it possible to understand the parameters involved in the production process and worked as a guide for the production line's composition in the Plant Simulation environment. The production line modeled in Plant Simulation used real input data obtained in two months of production in 2020. The results obtained showed that the modeling reached the objective of virtualizing the production process, once that the differences between the simulation and the real process were at most 1.07%.

Simulation modeling of the dynamics of competitive interaction between manufacturers of light-engine aircraft equipment in the conditions of volumetric competition

Enterprises of the domestic light-engine aircraft industry are in tough competition both in the domestic and foreign markets. To minimize the risks associated with strategic interaction with participants in these markets, enterprises should form their production programs based on a comprehensive analysis of the competitive environment. Determination of the optimal equilibrium values of the output volumes for each participant does not provide information on the dynamics of the interaction of competitors. In this regard, in order to describe the dynamics of market relations, it becomes necessary to develop a dynamic simulation model for the development of the light aircraft market. The paper considers a dynamic model of the problem of choosing a production program by enterprises producing light aircraft equipment in the duopole market, using a discrete simulation computer model. This model is represented by several algorithms generated in the Simulink software package (Matlab), using the library of standard operators of this package. This model allows to determine the trajectories of changes in the equilibrium values of quantities, prices and gross income. Also, using this model, it is possible to assess the influence of the costs incurred by enterprises on the implementation of the production program, on the results of market interaction, to determine the most significant parameters and, on this basis, to form a decision on the choice of a competitive strategy.

Discrete simulation analysis of COVID-19 and prediction of isolation bed numbers

Background The outbreak of COVID-19 has been defined by the World Health Organization as a pandemic, and containment depends on traditional public health measures. However, the explosive growth of the number of infected cases in a short period of time has caused tremendous pressure on medical systems. Adequate isolation facilities are essential to control outbreaks, so this study aims to quickly estimate the demand and number of isolation beds. Methods We established a discrete simulation model for epidemiology. By adjusting or fitting necessary epidemic parameters, the effects of the following indicators on the development of the epidemic and the occupation of medical resources were explained: (1) incubation period, (2) response speed and detection capacity of the hospital, (3) disease healing time, and (4) population mobility. Finally, a method for predicting the number of isolation beds was summarized through multiple linear regression. This is a city level model that simulates the epidemic situation from the perspective of population mobility. Results Through simulation, we show that the incubation period, response speed and detection capacity of the hospital, disease healing time, degree of population mobility, and infectivity of cured patients have different effects on the infectivity, scale, and duration of the epidemic. Among them, (1) incubation period, (2) response speed and detection capacity of the hospital, (3) disease healing time, and (4) population mobility have a significant impact on the demand and number of isolation beds (P <0.05), which agrees with the following regression equation: N = P × (−0.273 + 0.009I + 0.234M + 0.012T1 + 0.015T2) × (1 + V).

Design of Comminution Plants in the Ceramic Industry Using a Simulation-based Optimization Approach

In many cases, the design process of a structural ceramic comminution plant typically consists of an ‘expert designer’ who makes decisions using intuitive criteria to select commercial equipment. This paper proposes a simulationbased optimization approach to help decisionmaking. The complexity of the problem lies in selecting the model and amount of equipment for each stage at the lowest cost while simultaneously satisfying a previously fixed production and granulometry. The proposed approach is based on a genetic algorithm to generate solutions and facilitate the optimization process, together with discrete simulation to evaluate the performance of the comminution process according to its service level. To evaluate the algorithm, different problems, whose parameters are based on the requirements of the ceramic industry, are solved and analyzed.

Proposal of Improvement for a Textile Finishing Company in the Medellin city Through of Discrete Simulation

The textile industry in Colombia is a source of employment for more than 200.000 people and more than 50% of this production is undertaken in Medellin. Modeling and improving textile processes allow this economic line to be competitive internationally. In this paper, we make a description about the use of discrete event simulation in a textile finishing company through the presentation of the results of four scenarios, which finally shows the potential of discrete simulations in productive environments and its high impact when modelling part of reality without the necessity of experimenting with the real system. The method used in this paper is summarized in three major stages: the first one is the simulation methodology, the second one is the data to support the simulation, and the final stage is an analysis of the results with the comparison of the four scenarios. The simulation was statistically validated and verified with the real behaviors of the company and it is executed by using software tools such as EasyFit®, Microsoft Excel® and Simul8®.

Discrete Simulation of Vibratory Roller Compaction of Field Rockfills

Vibratory roller compaction is a well-known method in improving the mechanical properties of field rockfills. However, the meso mechanism of rockfill densification under vibratory roller compaction has not been understood clearly. This paper presents a discrete numerical method to simulate the vibratory roller compaction of field rockfills. Firstly, rockfill particles were modeled by irregular and stochastic clusters, which can be breakable. In addition, the segregation of field rockfills was replicated in a practical manner. Then, a new model of the vibratory roller was presented, in which the frame inertia was considered. Finally, the developed method was applied to simulate the vibratory roller compaction of field rockfills in the Shui Buya Project. Results show that (1) the numerical simulations of vibratory roller compaction of field rockfills agree well with the field experiments; thus, the feasibility and rationality of the developed simulation method are verified; (2) the dynamic response of field rockfills under vibratory roller compaction can be predicted by the presented numerical method with calibrated model and parameters; (3) the new roller model with frame inertia considered is much more accurate than the roller models in early studies. Thus, the developed discrete numerical method can be further adopted to explore the meso mechanism of rockfill densification under vibratory roller compaction in the future.