Discrete simulation software ranking — A top list of the worldwide most popular and used tools

Real-life applications during the teaching process are a desirable practice in simulation education. However, access to real cases imposes some difficulty in implement such practice, especially when the classes are large. This paper presents a teaching case for a computer simulation course in a production engineering undergraduate program. The motivation for the teaching case was to provide students with a realistic manufacturing case to stimulate the learning of simulation concepts and methods in the context of industrial engineering. The case considers a virtual factory of skateboards, which operations include parts manufacturing, final assembly and storage of raw materials, work-in-process and finished products. Students should model and simulate the factory, under push and pull production strategies, using any simulation software available in the laboratory. The teaching case, applied in the last two years, contributed to motivate and consolidate the students' learning of discrete-event simulation. It proved to be a feasible alternative to the previous practice of letting students freely choose a case for their final project, while keeping the essence of project-based learning approach.

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“…Each student team then decides which software to use. For a complete survey on simulation software, see Dias et al (2016).…”

Section: Methodsmentioning

confidence: 99%

The Skateboard Factory: a teaching case on discrete-event simulation

Mesquita

Mariz

Tomotani

2017

Prod.

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“…Moreover, it is an efficient tool to search for optimal solution and evaluate the obtained results. Different DES tools have been used in literature.in this context, [44] compared these tools to identify the most popular and used ones. In fact, the ARENA commercial software has been the most popular and used tool for modeling and analyzing various complex MSs.…”

Section: Publications Related To Simulation Approachmentioning

confidence: 99%

Improvement opportunities of a Simulation/Expert System Approach for Manufacturing System Sizing: A review and proposal

Imen¹,

Masmoudi²,

Elleuch³

et al. 2019

Adv. sci. technol. eng. syst. j.

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Manufacturing System (MS) sizing is a crucial task to complete in order to obtain the desired MS performance and efficiency. It involves selecting the required number of resources from each used type in a given planning horizon. In fact, different approaches coupling simulation/optimization tools have been developed to solve this issue and evaluate the MS performance. One of these approaches is the Simulation Expert System Approach (SESA). Unfortunately, the application domain of this approach is limited in sizing only the production resources (machines and labor) but neglects the material handling system (MHS) components. Moreover, omitting the transferring problem is not viable in the real world due to its importance in each shop floor. Thus, the aim of this paper is to describe the evolution of SESA, then, to check if the simulation optimization tools used in SESA are still relevant. This paper also investigates the importance of incorporating MHS in this approach and finally proposes some improvement opportunities for SESA including the tackling of the MHS fleet sizing problem. In fact, the wide literature review performed in this research indicates that SESA is still a pertinent approach but it must be improved. Therefore, it is expected that SESA improvement opportunities proposed in this work will greatly assist industrialists in enhancing the overall MS performance, providing a significant productivity increase and a minimization of the total production costs.

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“…Its technical support was also lacking. This situation resulted in initial software review of available competing packages, and selection of FlexSim software, which already was offering, among other improvements, the following features [1,4]:…”

Section: Simulation Softwarementioning

confidence: 99%

Evolution of an Integrated, Project-Based Logistics Engineering Curriculum

Pasek

Pawlewski

2019

PCEEA

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This paper describes the evolution of content and teaching practices of an innovative undergraduate curriculum developed for a new Logistics Engineering degree program. Originally proposed and implemented in 2010, the bi-level curriculum follows European directives and complies with the Bologna Process. Over the years the content and teaching practices were continuously reviewed and modified to stay in sync with teaching practices of design and entrepreneurship, progress simulation technologies, and student responses. Since the initial introduction of the curriculum many advances in various relevant areas have taken place and consequently the content of the curriculum had to be updated. For example, Lean Startup Method using Business Model Canvas has replaced business plans in teaching entrepreneurship. Similarly, as general softwarebased simulation tools have grown in complexity, teaching them requires more time and becomes time-impractical. A simpler approach based on limited-instruction tools tailored for product assembly, but built on these general simulation platforms, offers a more effective practical solution.

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Discrete simulation software ranking — A top list of the worldwide most popular and used tools

Cited by 55 publications

References 4 publications

The Skateboard Factory: a teaching case on discrete-event simulation

The Skateboard Factory: a teaching case on discrete-event simulation

Improvement opportunities of a Simulation/Expert System Approach for Manufacturing System Sizing: A review and proposal

Evolution of an Integrated, Project-Based Logistics Engineering Curriculum

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