Arena Simulation Model Research Articles

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.

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.

Investigation on Various Optimizing Strategies used to Reduce Time Delay in Production Activities of Manufacturing Industries in Nigeria

This paper is seeks to investigated the problem of time delay in the production activities of manufacturing industries in Nigeria. This research work is focused on how to identify the root causes of time delay and its solutions in the production activities of manufacturing industries in Nigeria. This also involves identifying the research gaps that need to be pursued further to better understand time delay and the limitations associated with them. The research has identified the works of literature that discusses challenges and limitations of time delay and minimize its effect in production activities. Due to the increase in industries application, there is significant interest in an efficient simulation and optimization of strategies to reduce time delay in production activities. A manufacturing industry (Support system (SS) LTD) work process route sheet is used to demonstrate how the factors using the arena simulation model to detect the causes and effect of time delay and how it can be reduced or eliminated. The use of case studies in the report has identified real-life challenges and opportunities that help to solve the problem of time delay in production activities manufacturing industries in Nigeria using Dangote Cement and Mantrac Nig. Ltd as case studies.

Arena Simulation of Spare Parts Inventory Management: A Case of A Telecom Managed Service Provider

Telecommunications and utilities companies, among other large service organisations, confront a slew of decision-making challenges, many of which are connected to the management of a variety of different resources. The management of spare parts and inventories is one of the most difficult resource management concerns that an organisation has to deal with on a regular basis. Their prompt availability may have a significant influence on the overall quality of the service and the level of client satisfaction. The purpose of the study was to assess the Spare Parts Inventory Management of XYZ company operating within the Ghanaian telecommunication ecosystem. Data on demand and inventory stock level was collected from the procurement department of XYZ company. The study adopted the use of the Arena Simulation model to analyze data collected from the XYZ company. The results of the analysis indicated that the procurement department is unable to meet the spare parts demand of the Passive department where the average order received from the department in a day is 6.08. Based on the findings of the study, it is recommended that the procurement department put in measure to receive and process orders in time. The reason for the delay in processing orders could be the less poor inventory management practices of the company. The study recommends that systems be adopted to track the inventory level of the company. Due to the stochastic nature of the demand from the passive department, the company should be proactive in the management of the demand by keeping the right stock level in order to meet the demand of the department in order to reduce the long down time. Key words: Spare parts, inventory, Arena Simulation, telecommunication DOI: 10.7176/EJBM/14-12-10 Publication date: June 30 th 2022

SIMULATION MODELLING AND ANALYSIS FOR IMPROVING THE PERFORMANCE OF PRODUCTION CASE STUDY: JORDANIAN VEHICLES MANUFACTURING COMPANY

Modelling and analysing production lines are crucial for the research community and designers interested in increasing production utilisation and reducing costs. This paper aims to model and analyse a real production process of a Jordanian vehicles manufacturing company and improve production line resource utilisation using ARENA simulation software. The methodology used is simulation modelling to develop a new production line design. Performance measures are obtained from data given by the company management and direct observation of the production line. A suggested modified Arena simulation model is developed for the production line processes based on the collected data. Verification and validation analysis of the proposed model is done. Results show that the proposed model’s performance is better than the current one in terms of; overall total processing time, the overall waiting time, the overall work in process, and the overall utilisation.

BİR ELEKTRONİK FİRMASINDAKİ İŞÇİ ATAMALI MONTAJ HATTI DENGELEME PROBLEMİNE MATEMATİKSEL PROGRAMLAMA VE BENZETİM MODELLEME TABANLI BİR ÇÖZÜM YAKLAŞIMI

This study deals with the problem of the assignment of workers to the stations and the balancing of the assembly line in an electronics company. The approach used to solve this problem consists of two stages. In the first stage, a mathematical model is presented which takes into account the information about which jobs the workers can and cannot do, whether the workers are present during the assignment to the stations, which equipment/ equipments the jobs should be done with, and the stations where these equipments are located and the various assignment constraints related to the jobs. As a result of this model being solved with LINGO optimization software, information about which jobs and workers are assigned to which stations is obtained. In the second stage, the assembly line which is arranged using the information obtained from the first stage, in order to test whether the assembly line reaches the desired production target under real life constraints, ARENA simulation model which takes into consideration the factors such as conveyor movement between stations, intermediate inventory areas and stochastic variability in operation times that could not be considered in the present mathematical model is presented.

Implementing Lean Six Sigma in a Kuwaiti private hospital

PurposeThe purpose of this paper is to use Lean Six Sigma (LSS) to reduce patient waiting time in a Kuwaiti private hospital obstetrics and gynaecology clinic.ApproachThe define, measure, analyse, improve and control methodology was used. The “define” stage involved identifying patients’ needs, system capabilities and project objectives. The “measure” stage assessed the system’s current state through data collection on waiting times. Dunnett’s test, control charts and process capability analysis were used to ensure data accuracy. In the “analyse” stage, an Ishikawa diagram and Pareto chart were constructed, showing that overbooking appointments, doctors’ unscheduled breaks and doctors not arriving on time were the root causes of the problem. The “improve” stage used an Arena simulation model to represent current and improved system status. The proposed solutions were implemented and monitored in the “control” stage.FindingsA sigma-level improvement of 300 per cent (0.5–2.0) was realized for appointment patients on Saturdays, with a 67 per cent reduction in waiting time. For walk-ins, the sigma level improved by 288 per cent (0.8–3.1), with a 55 per cent reduction in waiting time. For weekday appointments, the sigma level improved by 111 per cent (0.9–1.9), with a 63 per cent reduction in waiting time. For walk-ins, the sigma level improved by 69 per cent (1.6–2.7), with a 46 per cent reduction in waiting time. A cost–benefit analysis estimated the present project value at $656,459, leading to a total of $5,820,319 in savings by 2025.Originality/valueThis paper fulfils the need for process improvement, increasing patients’ satisfaction and hospitals’ profitability using LSS.

Performance Prediction and Evaluation Based on the Variability Theory in Production Lines Using ARENA Simulation

The level of performance is an important aspect of the design and control in a production line. Particularly, the level of performance of variable production line (VPL) is one of the most important influential factors in deciding production line’s flexibility. The majority of the existing solution methods for performance prediction and evaluation problems of VPL assume that the processing times, time between failures and repair times are deterministic or exponentially distributed, which could not be applied to all the problems in real cases. This paper relaxes these restrictions by proposing an ARENA simulation model for performance prediction and evaluation based on the variability theory in Factory Physics. The variable properties of time interval between product arrivals and VPL are simulated, which combining with the coefficients of variations, are presented. Through the simulation, how the variable factors influence the performance of VPL is demonstrated. The methodology in this paper can be applied to effectively predict and evaluate the performance in VPL in various production scenarios before implementing them in reality.

Modern Hypermarket Receiving Yard Utilization: The Implementation of a Simulation Model

Objective - This research is a direct observation of initial queuing, using data that is categorised into two clusters: the number of people queuing at busy hours, and processing times in the same circumstances. Methodology/Technique - The raw data was converted for use in the Poisson distribution test, as well as the Kolmogorov-Smirnov exponential distribution options. An arena simulation model was also applied to identify the vendor's waiting time and to analyse receiving yard utilization. The average waiting time according to the Poisson distribution, the average serving time per vendor by an exponential distribution, and the number of receiving yards, are all essential factors effecting the utilization of receiving yards. Findings - The study compares the length of queues, serving times, arrival rate, and time in the system using dual and single receiving yard systems. However, the utilization rate on a two receiving yards system is less than the rate on single receiving yard system. As the aim of this study is to identify the utilization rate of the receiving yard, a single receiving yard operation is more representative of modern hypermarkets, and more efficient in terms of resource efficiency. Novelty - This study depends fully on the homogeneous operating hours of the retailers' receiving yards, the type of vehicle used by vendors to unload merchandises, procedures on moving the products to the inspections phase, a generalization of the products delivered by the vendors and the size of the modern hypermarkets business itself. Type of Paper: Empirical. Keywords: Receiving Yard Utilization; Hypermarket Receiving Yard; Queuing Simulation. JEL Classification: M1, M10, M19.

An analytical model for continuous flow transporters of AMHSs with multi-loop conveyors and priority rules

To quickly and efficiently estimate the performance of continuous flow transporters of automated material handling systems with multi-loop conveyors and priority rules of wafer lots in wafer fabrication systems, the M/M/1/K queuing model and non-pre-emptive priority M/G/1 queuing model with multi-class customers were introduced to analyse the queuing features of the continuous flow transporters. An analytical model is presented for a spine layout of continuous flow transporters which are configured with conveyors and crossovers. In the modelling procedure, a spine layout with crossovers and an outer loop was set up to make differentiated routes. Priority rules of wafer lots were implemented by controlling the outer loop, inner loop and crossovers to access. A case of a 300 mm wafer fabrication with 24 intrabays was applied to validate the analytical model. The performance of the analytical model has been compared with that of an Arena simulation model. Experimental results show that in most cases the relative errors can be controlled to be smaller than 5%. It indicates that the model perform well in performance analysis for continuous flow transporters of automated material handling systems.

Level of Service Analysis Based on Maximum Number of Passengers in Waiting Room of Railway Passenger Station Using Arena Simulation

The level of service is an important aspect of the operation and management at a railway passenger station. Particularly, the level of service in waiting room (LOSWR) is one of the most important influential factors in deciding passengers’ satisfaction. This paper proposes a model for finding the LOSWR based on the maximum number of passengers, and an Arena simulation model that simulates passengers’ aggregation behaviors in the waiting room is presented for analyzing the LOSWR. Through the simulation, we demonstrate how the passenger advanced arrival time and the accompany rate influence the maximum number of passengers and the LOSWR. In addition, the simulation also illustrates the effect utilities and the priority of different measures that can be used to improve the LOSWR. In detail, the simulation results demonstrate that the passenger advanced arrival time and advanced check-out time have much stronger effect utilities on the maximum number of passengers and the LOSWR than other discussed factors. The simulation suggests that the Arena is an effective simulation platform for analyzing complex passengers-related behaviors at railway passenger station.

Workers and Machine Performance Modeling in Manufacturing System Using Arena Simulation

This paper deals with the workers and machine performance measurements in manufacturing system. In simulating the manufacturing system, discrete event simulation involves the modeling of the system as it improves throughput time and is particularly useful for modeling queuing systems. In modeling this system, an ARENA simulation model was developed, verified, and validated to determine the daily production and potential problem areas for the various request levels in the case company (Ethiopia Plastic Factory). The results obtained show that throughput time in the existing system is low because of occurrence of bottlenecks, and waiting time identified. Therefore, some basic proposals have been drawn from the result to raise awareness of the importance of considering human and machine performance variation in such simulation models. It presents some conceptual ideas for developing a worker manager for representing worker and machine performance in manufacturing systems simulation models. The company workers’ and machine performance level is raised by identifying the bottle neck area. They were recommended to amend the main basic bottle necks identified.

Modeling and Performance Analysis of Manufacturing Systems in Footwear Industry

This study deals with modeling and performance analysis of footwear manufacturing using arena simulation modeling software. It was investigated that modeling and simulation is a potential tool for modeling and analysis of manufacturing assembly lines like footwear manufacturing because it allows the researcher to experiment with different variables and controls the manufacturing process without affecting the real production system. In this study Arena simulation software is employed to model and measure performance of existing manufacturing systems of footwear. A footwear assembly plant producing a moccasin model shoe in Ethiopia with a total number of 19 major parts to be assembled on two consecutive assembly lines (stitching and lasting) were selected for the model. Furthermore, 39 and 37 activities were identified for stitching and lasting production line respectively. For each activity, 15 numbers of observations have taken using stopwatch. All the collected data are statistically analyzed using arena input analyzer for statistical significance and determination of expressions to be used in simulation modeling. A standard validated simulation model was developed and run for 41 replications. The result shows that the stitching assembly line is operating with a line balance efficiency of 58.7% and lasting assembly line 67.6%. In the course of action, about four major problems were identified and solved with five proposed scenarios of which the best scenario results in improvement of assembly line balance efficiency of 93.5 and 86.3% for stitching and lasting respectively. This Arena Simulation Model has considered the production resources like machineries, employees and processing time; activity precedence relationships; and production methods in developing and testing scenarios. It can be applied to other complex manufacturing industries wishing to analyze and improve the performance of the production systems.Keywords: Modeling Simulation Performance Analysis Footwear Manufacturing

시뮬레이션을 이용한 DDoS공격 대응기술 효과성평가방법

본 논문은 시뮬레이션을 이용한 DDoS공격 대응기술의 효과성을 평가하기 위한 방법을 제시한다. 미국 국가표준기술연구소(NIST: National Institute of Standards and Technology)에서 제시한 보안목표에 따라 효과성평가모형을 계층적으로 표현하였다. 보안목표, 보안통제, 성과지표에 해당하는 요인들의 가중치 계산을 위해 계층적 분석(AHP: Analytic Hierarchy Process)을 적용하고, 최하위계층인 성과지표의 기능점수계산을 위해 Arena시뮬레이션모델을 구현하였다. 탐지 및 차단 알고리즘은 네트워크 L4, L7계층 공격에 대한 임계치설정, 시그니쳐기반탐지, 행동(통계)기반탐지 기술을 복합적으로 검증하였다. 제안된 효과성평가모형은 조직마다 상이한 보안목표와 위협에 따라 다르게 설계될 수 있으므로 새로운 보안위협에 대한 대응방안이나 대응기술의 효과성을 평가할 수 있는 방법으로 활용될 수 있다. This paper suggests Effectiveness Evaluation Methods of DDoS attacks countermeasures model by simulation. According to the security objectives that are suggested by NIST(National Institute of Standards and Technology), It represents a hierarchical Effectiveness Evaluation Model. we calculated the weights of factors that security objectives, security controls, performance indicator through AHP(Analytic Hierarchy Process) analysis. Subsequently, we implemented Arena Simulation Model for the calculation of function points at the performance indicator. The detection and protection algorithm involve methods of critical-level setting, signature and anomaly(statistic) based detection techniques for Network Layer 4, 7 attacks. Proposed Effectiveness Evaluation Model can be diversely used to evaluate effectiveness of countermeasures and techniques for new security threats each organization.

Management System Models to Support Decision-making for Micro and Small Business of Rural Enterprise in Thailand

This paper is concerned with an application of discrete-event simulation (DES) modeling of the dynamic supply chain and analysed the One Tambon One Product (OTOP) strategy and management policies in Thailand. Arena simulation models using the rapid-prototype conceptual models is currently presented under development and as tools for planning and support decisionmaking of management policies based on the knowledge created by supply chain simulation (SCS) experimental. The network cluster models considered is comprised of six-stage: suppliers, manufacturers, warehouses, wholesalers, retailers and the customer. In our instance, we evaluate supply chain production and the impact of lead time reductions.

Predicting the economics of X-ray inspection technology in sweet onion packinghouses using simulation modelling

To determine the feasibility of using x-ray technology for internal defect removal, a discrete-event simulation model was developed with the capability to vary inspection machine configuration and placement and associated economic impact. To evaluate the profitability of X-ray inspection, the results of the simulation model were also used to estimate the unit cost (UC) and selling price per box of the inspected onions. A fundamental assumption of this work is that the increase in quality resulting from the X-ray inspection would command a higher market value as reflected by sales price. An Arena simulation model was developed based on data from two packinghouse time studies, from 2005 to 2006 onion X-ray inspection and sample measurements (4 cultivars each year) and from published cost estimates of sweet onion production and packing. The model results indicated the feasibility of incorporating three and four X-ray inspection units at 0.25 m s −1 belt speed under the simulated conditions to obtain realistic throughput rates. Estimated costs per 18.14 kg box of X-ray inspected onions ranged from US $9.00 to US $15.00 while the estimated selling price ranged from US $11.35 to US $25.34, depending on farm yield, the quality of incoming crop and the gross profit margin goals. The methods could be readily extended to other commodities destined for the fresh market; however, the results would be commodity and site specific.

Optimising and simulating the assembly line balancing problem in a motorcycle manufacturing company: a case study

In this paper, we present a real life assembly line balancing problem for a motorcycle manufacturing company. Results from the initial situation in the company are compared to those provided by a heuristic method and by a novel neighbourhood search method. An ARENA simulation model is developed to test the different proposals. The model was validated by comparing the simulation results from the initial company scenario with the real operation results. Consequently, the extension to the developed proposals allows us to select an adequate assembly line for the company, resulting in a greater productivity level and a more balanced line with respect to the operation times in the stations and the activity of the workers. The company has subsequently implemented our proposed schedule, obtaining remarkable improvements in its productivity.

The impact of integrating return components planning with purchasing decisions on purchasing performance

PurposeThe purpose of this research is to apply a simulation experiment to investigate the impact of new components purchasing and used components recovery strategies on multiple performance measures. The research compares the effectiveness of these strategies, given different levels of uncertainty for the return flow from the contingency perspective.Design/methodology/approachThe experimental design is implemented using an ARENA simulation model. Simulation results are used to test the proposed research model. Multivariate analysis of variance is used for data analysis.FindingsThe results demonstrate that while a proactive purchasing strategy reduces total system cost, it also negatively affects service level. While there are some general conclusions, it is equally important to make decisions under specific business contexts.Practical implicationsThe primary implication is that a firm has to align its purchasing strategy and recovery strategy with its business strategy. Given the tradeoff on multiple performance dimensions, the business strategy guides the selection of the appropriate purchasing and recovery strategy.Originality/valueThis paper demonstrates that using multiple performance measures is necessary to accurately assess cost and service trade‐offs related to a proactive purchasing strategy. Considering a wide range of circumstances, this paper suggests that the contingency perspective is a valid approach for investigating closed‐loop supply chains.

A simulation study to increase the capacity of a rusk production line

This study was conducted in a food processing company on its Rusk production line. The goal of the study was to increase the production rate of the line to meet the continuously increasing demand on its product within the existing limited space in the plant. The production line was thoroughly studied and analyzed. Several bottlenecks that were causing sever congestions in different areas on the production line were found. An Arena Simulation model was developed and used to resolve all bottlenecks found on the line and a simulation experiment consisting of seven different scenarios was conducted to search for a good feasible solution to increase the production rate. The changes made in the production line resolved all bottlenecks, improved utilization of all production equipment, eliminated all congestions and most of the queues at all production stations. An increase of about 50% in production and a decrease of 11.4% in average total production time for a box of Rusk in the system were achieved. The capital investment required to implement the new improvements can be paid back in a period of 35 days from the expected profit that would be realized from the additional increased quantity produced. The changes that were made on the production line to achieve the above improvements were adding two new machines, replacing three other old machines, modifying two other machines and decreasing the time of one of the processes, without affecting the quality of the product.

COMPREHENSIVE DESIGN OF AN ORDER PICKING LINE BY SIMULATION

Successful order picking is necessary for fast order shipment to the customer. This paper presents a methodology for a complete analysis to design a picking line. This investigation considered a global view of the line: station layout, storage policy, picking policy, replenishment process and sorting solution. Size and number of the stations to be installed were also investigated. Arena simulation model was developed. The developed methodology resulted in solutions that clearly are better in performance: number of orders and units served, number of staff required, length of the conveyor needed, single picker utilization and total time in the system.