Arena Simulation Research Articles

Efficiency and Simulation of Thailand's Chiang Mai University Model for COVID-19 Mass Vaccination Hub (CMU-MVH Model).

Mass vaccination is crucial for achieving herd immunity and controlling pandemics. Simulation models predict vaccination outcomes. This study evaluates efficiency and designs a tailored vaccination plan for Thailand. Data was derived from a COVID-19 Mass Vaccination Hub (MVH) in Chiang Mai, Thailand. It was taken between June 2021 and December 2021. The discreet event simulation model is developed in Arena Simulation Enterprise Suite version 14.0. The operational efficiency of Chiang Mai University Mass Vaccination Hub (CMU-MVH) was 1,073 vaccinations per 8 hours with 38 service staff. The average processing times (APT) were 2.5 minutes for the registration station, 12.2 minutes for the assessment station, 8.3 minutes for vaccination, and 28.2 minutes for observation. With 100% staff availability and staff utilization ranging from 0.5 to 0.7, the CMU-MVH could handle 180 to 230 vaccinees per hour or 1,227 to 1,527 vaccinees per day. Reduced staff availability leads to an increase in average processing time, especially when staff availability is lower or equal to 60%. The CMU-MVH could handle approximately a thousand vaccinations within 8 working hours. This capability could assist policymakers in developing more effective strategies and planning for future mass vaccinations. The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Queuing System Simulation to Optimize Waiting Time using the Quality Function Deployment Approach at KFC Pontianak

The aim of this research is to find the best scenario to optimize the queuing system so that it can reduce waiting time during customer service at KFC Pontianak. Queue systems are prevalent in public services. The research employs Quality Function Deployment (QFD) and Discrete Event Simulation (DES) methodologies. Alternatives generated are simulated using ARENA Simulation. 70 respondents participated in the KFC Pontianak customer questionnaire, comprising 48.6% females and 51.4% males aged between 18-45 years. The results of the questionnaire showed that 51.4% of respondents were dissatisfied with the speed of service at KFC Pontianak. Customer needs identified through QFD include service speed, order accuracy, ease of use, customer satisfaction, queue comfort, food quality, and payment integration. Analysis reveals three queue system scenarios, two of which propose improvements. The second scenario involves 2 cashiers and 2 self-service cashiers. Self-service allows customers to order by scanning a QR code integrated with the service provider's application. Arrival type employs an exponential distribution with an average of 61 seconds, unlimited max arrival, and first creation with a value of 0. In self-service, there is a value difference of 1 and a standard deviation of 0.2. Simulation results indicate that 51 customers choose cashier 1, 41 choose cashier 2, 39 opt for self-service cashier 1, and 53 prefer self-service cashier 2. The total successfully served customers are 94, with a success rate of 51%. In the third scenario involved 4 self-service cashiers only, the values of 1 and standard deviation of 0.2. The total number of successfully served customers is 173, with a success rate of 80%. In conclusion, this research offers valuable insights for optimizing KFC Pontianak's queue system, addressing customer dissatisfaction with service speed. The proposed scenarios, especially those involving self-service options, demonstrate potential improvements in customer satisfaction and operational efficiency.

Optimizing Restaurant Queue Management: A Simulation-Based Approach Using Arena Software

Examining the effectiveness of models in terms of utilization and waiting time is one of the anticipated benefits of analyzing queuing systems. This study uses Arena simulation software to examine the queue system of a particular restaurant. The primary objective is to assess and enhance the restaurant’s service efficiency through the modelling of customer arrivals, service procedures, and queue dynamics. Data on customer arrivals and service times were collected for the restaurant’s current system. The necessary expressions were developed from the observed data using the input analyzer. A conceptual model of the original queuing system was created, and two alternative Arena models were developed to reduce customer waiting times in the restaurant. The developed models were run to evaluate their performance. During a 24-hour simulation study, the average waiting time in the overall model was found to be 24.49 minutes, with a maximum of 48.69 minutes. The waiting time for server 1 was 25.30 minutes, for server 2 was 23.27 minutes, for server 3 was 25.11 minutes, and for server 4 was 22.30 minutes. The number of customers in line at server 1 was 12.65, at server 2 was 6.98, at server 3 was 8.29, and at server 4 was 8.25. Resource utilization was 57% for server 1, 35% for server 2, 27% for server 3, and 15% for server 4. By decreasing the queuing length and average waiting time in the restaurant, customer satisfaction can be increased, leading to a reduction in time wasted. The findings indicate significant potential for improving overall service quality and reducing client wait times. This research provides valuable insights for restaurant managers seeking to enhance customer satisfaction and operational efficiency.

Duration and Labor Resource Optimization for Construction Projects—A Conditional-Value-at-Risk-Based Analysis

The complexity and uncertainty of construction projects contribute to low efficiency in the construction industry. This research applied the Takt-time planning method to optimize the construction working process, and proposed a risk control framework based on Value at Risk (VaR) and Conditional Value at Risk (CVaR) approaches to explore and predict a project schedule and cost performance under different scenarios. This research selected a high-rise residential building project for a case study and collected 1672 productivity data samples. Arena Simulation models were established based on 90 combinations of labor assignments to assess Takt-time planning strategies’ impact on project performance in four scenarios. The VaR and CVaR evaluations at 75% and 90% confidence levels were compared to balance project benefits and risks. Without any overtime or additional workers, this research found a Takt-time planning method that can reduce the project duration by 20.2% and labor costs by 2.1% at the same time, using a labor assignment of 12 bar placers, 12 carpenters, and 5 pipefitters. The findings can assist construction managers to achieve a shorter duration, reduced cost, and safer work environment, which will be very effective and beneficial to improve project overall performance.

Queuing analysis and optimization of public vehicle transport stations: A case of South West Ethiopia region vehicle stations

Modern urban environments present a dynamically growing field where, notwithstanding shared goals, several mutually conflicting interests frequently collide. However, it has a big impact on the city's socioeconomic standing, waiting lines and queues are common occurrences. This results in extremely long lines for vehicles and people on incongruous routes, service coagulation, customer murmuring, unhappiness, complaints, and looking for other options, sometimes illegally. The root cause is corruption, which leads to traffic jams, stops and packs vehicles beyond their safe carrying capacity, and violates passengers' human rights and freedoms. This study focused on optimizing the time passengers had to wait in public vehicle stations. This applied research employed both data-gathering sources and mixed approaches. Then, 166 samples of key informants of transport stations were taken using the Slovin sampling formula. The time vehicles, including the drivers and auxiliary drivers ‘Weyala', had to wait was also studied. To maximize the service level at vehicle stations, a queuing model was subsequently devised ‘Menaharya’. Time, cost, and quality encompass performance, scope, and suitability for the intended purposes. The study also focused on determining the minimal response time required for passengers and vehicles queuing to reach their ultimate destinations within the transportation stations in Tepi, Mizan, and Bonga. A new bus station system was modeled and simulated by Arena simulation software in the chosen study area. 84% improvement on cost reduced by 56.25%, time 4 hours to 1.5 hours, quality, safety and designed load performance calculations employed. Stakeholders are asked to implement the model and monitor the results obtained.

Organic waste management based on supply chain management using arena simulation and macro ergonomics approach

In this modern era, simulation software such as Arena has become a valuable tool for designing, optimizing, and analyzing the flow of supply chains efficiently. The aim of this research is to describe and analyze the flow of waste supply chains using Arena software. The second objective is to analyze the behavior of the people of Semarang city regarding organic waste processing using a macroergonomics approach. This study employs a simulation approach by utilizing Arena software to model the flow of waste supply chains from collection, sorting, processing, to final disposal stages. Using Arena software, simulation results can be measured and objectively analyzed, serving as a basis for identifying improvements and enhancements in the waste supply chain. To manage organic waste in an area it is necessary to involve cognitive, psychological, organizational and environmental aspects. The strategy for managing organic waste in urban areas such as the Semarang area is to manage and ensure that organic waste has added value and sales value.

Productivity improvement through assembly line balancing by using simulation modeling in case of Abay garment industry Gondar

This study aims to balance the garment line of the polo shirt operation by utilizing line balancing techniques. These techniques are employed to enhance the efficiency and productivity of the Abay garment industry. Observational methods and stopwatch timing were employed to collect data on the processing times for each operation. Subsequently, the standard allowed minute was determined based on work measurement principles. To assess statistical significance and identify appropriate expressions for the existing simulation modeling, all collected data underwent statistical analysis using the Arena input analyzer. Moreover, Arena simulation software was employed in this research to simulate and evaluate the effectiveness of both the current and proposed polo shirt sewing line models. Building upon the existing model, alternative improved models were proposed. The alternative models yielded significant improvements in multiple performance metrics, including output, capacity utilization, waiting time in queues, and number of products waiting. These improvements indicate an increase in productivity resulting from the implementation of balanced production lines. The outcomes of the improved scenario included an increase in output from 288 to 381, a rise in line efficiency from 39.06 % to 55.64 %, and an enhancement in labor productivity from 54.25 % to 66 %. Additionally, the cost of labor was reduced by 15.63 %, while revenue experienced a notable increase of 30 %.

Analysis of Queuing Systems at McDonald's Outlets in Malang with an Arena Simulation Approach

Analysis of Queuing Systems at McDonald's Outlets in Malang with an Arena Simulation Approach

Improvement of Manufacturing Process Based on Value Stream Mapping: A Case Study

Value Stream Mapping (VSM) is a key tool in Lean Manufacturing (LM) that helps identify opportunities for process improvement. This research aims to propose an integrated method using LM tools (such as Kanban, VSM, Pareto chart, and Supplier Input Process Output Customer) and Arena simulation to improve the productivity of the production line through reducing lead time, inventory time, including Raw Material (RM) time and Work In Progress (WIP) time and enhancing Process Cycle Efficiency (PCE) ratio. To begin the process, a Pareto chart is employed to identify the main product of the organization. Subsequently, a current VSM is constructed to identify any waste in the production line. The Kanban tool is then used to propose appropriate remedies to improve the manufacturing process. To validate the efficiency of the production capacity in future VSM, Arena simulation is executed by determining Takt Time. Lastly, a future VSM is formulated based on the suggested improvements, and an appraisal is conducted to provide recommendations for prospective enhancements. A real case study of a furniture company in Vietnam is performed to demonstrate the effectiveness of the proposed method. The results reveal impressive benefits, including a 92% reduction in lead time and a corresponding 92% increase in PCE. Additionally, there is a substantial reduction of around 90% in WIP time, while RM time is completely eliminated, resulting in a 100% reduction. These findings highlight the efficacy of the proposed approach and the importance of VSM and other Lean tools in achieving process optimization.

Layout Design of Copra Factory Facilities in Small and Medium Industry Centers Using Systematic Layout Planning Method

This research was conducted on the layout of copra processing facilities. Copra is one of the products to be produced by the Small and Medium Industry Center in the Meranti Islands. The purpose of designing the layout of this copra factory facility is to provide a proposal in the form of a copra processing facility layout with the shortest material handling distance. The methods used in this study are Systematic Layout Planning (SLP) and Arena Simulation. The result of the SLP method is in the form of alternative layout proposals, which will be checked with a simulation model. This Arena simulation is carried out to see whether the production process of the resulting layout is good or not by implementing it into a conceptual model in the Arena software, which is then tested to see the disruptions that exist in the production process, such as the accumulation of raw materials at one of the stations (bottleneck). Based on data processing results, one alternative layout was selected with a material handling distance of 26.33 m from 3 existing alternatives. This selection is based on the smallest material handling distance obtained. Furthermore, testing the layout with the Arena software simulation model found that there was a disruption in the production process in the form of a buildup of raw materials at the smoking and drying station caused by the manual drying process using the scorching heat of the sun so that it takes 4-5 days for the drying process.

Simulation and Goal Programming Approach to Improve Public Hospital Emergency Department Resource Allocation

Efficient and effective operation of an emergency department is necessary. Since patients can visit the emergency department without making an appointment, the emergency department always treats a lot of critical patients. Moreover, the severity of the ailment determines which patients should be prioritized. Therefore, the patients are greatly impacted as a consequence of longer waiting times caused primarily by incorrect resource allocation. It frequently happens that patients leave the hospital or waiting area without treatment. Certainly, the emergency department’s operation can be made more effective and efficient by examining its work and making modifications to the number of resources and their allocation. This study, therefore, investigates the emergency department of a public hospital to improve its functioning. The goal of this research is to model and simulate an emergency department to minimize patient wait times and also minimize the number of patients leaving the hospital without service. A comprehensive simulation model is developed using the Arena simulation platform and goal programming is undertaken to conduct simulation optimization and resource allocation analysis. Hospital management should realize that all resources must be prioritized rather than just focusing on one or two of them. The case scenario (S3) in this study that implements goal programming with variable weights yields the most favorable results. For example, it is observed in this instance that the number of patients leaving the system without service drops by 61.7%, and there is also a substantial drop in waiting times for various types of patients.

Mitigating the Bullwhip Effect and Enhancing Supply Chain Performance through Demand Information Sharing: An ARENA Simulation Study

Mitigating the Bullwhip Effect and Enhancing Supply Chain Performance through Demand Information Sharing: An ARENA Simulation Study

Discrete-Event Simulation (DES) and Banker, Chames and Cooper Data Envelopment Analysis (BCC-DEA) Models in Improving the Allocation Officers in Outpatient Department

This study aims to propose an improvement model for the queuing system and determine the best and most appropriate allocation suggestion for officers at the outpatient department of a public clinic in Johor. In this study, Arena Simulation Software and Lingo Software were used. Discrete-Event Simulation (DES) and Banker, Chames, and Cooper Data Envelopment Analysis (BCC-DEA) models were used to determine the best improvement model across various alternatives. The Min-Max of officers was suggested as an improvement model. The mathematical formulation has been programmed and tested in the Lingo 19.0 software, and Decision-Making Units (DMU) would be suggested. After that, each DMUs were run in Arena Simulation Software. Then, the input and output of each DMUs were determined. The researcher used BCC Model Input-Oriented to reduce the input required to produce the optimal output. The mathematical formulation has been programmed again and tested in the Lingo 19.0 software. Based on the results, DMU is considered an efficient choice if the value θ_0 is one (θ_0= 1). DMU is considered an inefficient alternative if the value θ_0 is not one (θ_0 ≠ 1). The input-oriented BCC model needs to identify the most effective and efficient DMU because they have multiple DMUs that are rated as efficient. So, the Super Efficiency model was used to identify the most efficient and suitable DMU. The mathematical formulation has been programmed again and tested in the Lingo 19.0 software to identify the Super Efficiency model

Identification and fixing bottlenecks of a food manufacturing system using a simulation approach

In manufacturing systems, simulation modeling plays an important role in creating some changes instead of working on real systems. Manipulation in a real system is more costly than manipulation in a simulated model. In this research, we tried to use a simulation approach to recognize and minimize bottlenecks of a production line, which will decrease costs and improve productivity. To achieve our objectives, we chose a case and analyzed its production line. By using our case study strategy, we tried to collect our data and adapt a conceptual model of production processes drawing on an operation process chart (OPC). After that, we created a simulation model of the production processes by using the popular Arena simulation software 13.5. By running the Arena model, some bottlenecks were found. Ultimately, we proposed some solutions to obviate bottlenecks and reduce the total costs of production.

Using inventory related performance measures in the analysis of a production/inventory flexible manufacturing system

To survive in the ever-increasing competition in the market, manufacturing firms must adopt the latest technologies available. Flexible manufacturing systems (FMS) provide an effective solution to the problem, but its performance should be continually enhanced to remain competitive in the market. The aim of this work was to identify the effect of routing flexibility and system load conditions on the performance of FMS using both production and inventory related performance measures. ARENA simulation software was used to model and study the system. (R, r) inventory control policy was applied to the production/inventory system. Routing flexibility was found to have a significant effect on all the performance parameters, with maximum improvement of performance observed at increase of level from 0 to 1. It was further observed that the system load condition does not have a significant effect on any of the performance measure. The FMS showed slightly improved performance when the system was fully balanced. It can be concluded that the inventory related performance measures give comparable results to that of production related performance measures.

Modelling Analysis of a Four-Way Shuttle-Based Storage and Retrieval System on the Basis of Operation Strategy

In the context of sustainable development, this paper rationalises the outbound process of a four-way shuttle system with a focus on their modelling, performance evaluation and configuration using a parallel operation strategy to reduce resource waste, thus achieving sustainable development. The parallelism of the hoist and shuttle is innovatively incorporated into the four-way shuttle system, so the modelling content is divided into parallel and serial types. In the parallel operation strategy model, a separation–aggregation queueing network model is constructed, and the open-loop queueing network is innovatively solved using the maximum entropy method. In the serial operation strategy model, a semi-open-loop queuing network is constructed and solved using the geometric matrix method. By varying different parameters, the accuracy of the model is verified by Arena simulation with an error range of 10% or less, and the error of the system performance index calculation is reduced by 20% compared with the existing methods. Setting up 18 different sizes of shuttle systems provided a better performance than a single serial-operation strategy through the addition of parallel strategies, with an average reduction of 12.6% in the system response time and a minimum reduction of 1.8%. The conclusions of this paper were verified on the basis of an arithmetic case analysis.

The Evaluation and Improvement of the Production Processes of an Automotive Industry Company via Simulation and Optimization

Production delays are significant problems for the loss of goodwill of the customers and the loss of profits associated with them. The delays may accrue as a result of insufficient resource planning and poorly designed unsatisfactory procedures. In this study, a new mathematical model is proposed to optimize the production processes by minimizing production delays, and a simulation model is developed to test the alternative facility designs. The purpose is to increase customer satisfaction by ensuring that the products are delivered timely and preventing lost sales in an automotive company that manufactures garbage collectors by using real data. The mixed-integer programming problem related to the minimization of production delays is solved by the GAMS CPLEX 24.1.3 software. In this way, the total delay in the production area is minimized by the mathematical model to prevent labor and time loss. Accordingly, the alternative designs are investigated for the improvement of the production processes by using discrete system simulation. A system analysis is performed to determine the bottlenecks in the production processes by developing a simulation model via the ARENA simulation software. With the proposed facility layout alternatives, the delays are eliminated, the total production time is reduced, and an increase in production efficiency is observed.

Lean Service Model with Simulation in Arena to Improve Response Time of the Technical Service in A Peruvian SME

Lean Service Model with Simulation in Arena to Improve Response Time of the Technical Service in A Peruvian SME

Scheduling AIV transporter using simulation-based supervised learning: A case study on a dynamic job-shop with three workstations

Dynamic job shop scheduling consists of scheduling jobs dynamically with different routing on a set of machines. A feasible and quick solution can be computed using heuristics. One well-known heuristic in job shop problems is selecting the priority dispatching rule (such as giving priority to the job with the Shortest Processing Time called SPT). Nowadays, with the application of industry 4.0 technologies such as sensors, Intelligent robots, etc., workshop data are more accessible and can be exploited to find the appropriate dispatching rule depending on the state of the shop. This work proposes a data-driven methodology for scheduling an AIV (Autonomous Intelligent Vehicle) that supplies three workstations. Our approach is based on data collected from an Arena simulation model fed to a supervised learning algorithm. This one helps identify one among five dispatching rules for each scheduling decision.

Modeling and simulation of the furniture manufacturing and assembly process in the arena simulation software

The article describes issues related to creating discrete simulation models for the implementation of the furniture manufacturing and assembly process in a furniture company. The methodology of the manufacturing system analysis was presented, which is aimed to support the appropriate approach to the construction of simulation models. The scope of the work includes the technological identification of the furniture manufacturing and assembly process in real production conditions, on the basis of which the appropriate simulation model was built. The course of the process was analyzed in the Arena software on the basis of a computer simulation based on reports. As a result of the simulation of the manufacturing process with the use of information from report of usage, an area for improvement was located. The re-analysis of the material flow made it possible to propose a change in the input parameters for the simulation model in the indicated area. The results of the second simulation show significant changes in the effective use of workstations and increase in the efficiency of the production line. In practice, it can be the basis for introducing simulated changes in the production system.