Material Flow Optimization through E-Kanban System Simulation

Pekarčíková, Miriam; Trebuňa, Peter; Kliment, Marek; Rosocha, Ladislav

doi:10.2507/ijsimm19-2-513

Cited by 25 publications

(18 citation statements)

References 14 publications

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“…It is important to keep participants immersed and entertained while providing knowledge in a comprehensible form [2]. However, as digital evolution continues [3], it is imperative to ensure students can transfer learnt skills into practical use.…”

Section: Introductionmentioning

confidence: 99%

3D Interactive Learning Environment as a Tool for Knowledge Transfer and Retention

et al. 2021

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The article deals with the design of virtual reality (VR) interactive training as a teaching method and its effect on knowledge transfer and retention of students. The first part presents the methodology of the VR interactive training design. The second part utilizes the created interactive training for a case study to evaluate its effect on the teaching process and to examine the potential of VR interactive training as a sustainable teaching method. The study took place at the Department of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina. Volunteers were divided into two groups. The first group used VR interactive training as a teaching method, while the second group used the conventional method. Both groups then underwent tests. The main goal was to evaluate the effect of the VR interactive training on the teaching process in comparison to the conventional method while trying to identify the key elements of the VR interactive training design and its influence on knowledge transfer and retention in a sustainable learning environment. At the start of the case study, four hypotheses were formed, questioning the effect of interactive training on knowledge transfer and retention in the long and short term, and its overall influence on the teaching process. Obtained data were then used to evaluate these hypotheses.

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Section: Introductionmentioning

confidence: 99%

3D Interactive Learning Environment as a Tool for Knowledge Transfer and Retention

et al. 2021

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“…++++++ [49,50] Real-time capability It is the ability of a device or system to collect and analyze data as well as to respond instantaneously to a command, event, or input. ++++++++ [51,52] Modularity It determines which independent and interlocking subsystems build the system based on their functionality. +++ [53,54] Interoperability It is the ability of systems to exchange information of unambiguous meaning.…”

Section: Name Description Effect On Optimization Examplesmentioning

confidence: 99%

Industry 4.0‐Driven Development of Optimization Algorithms: A Systematic Overview

et al. 2021

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The Fourth Industrial Revolution means the digital transformation of production systems. Cyber-physical systems allow for the horizontal and vertical integration of these production systems as well as the exploitation of the benefits via optimization tools. This article reviews the impact of Industry 4.0 solutions concerning optimization tasks and optimization algorithms, in addition to the identification of the new R&D directions driven by new application options. The basic organizing principle of this overview of the literature is to explore the requirements of optimization tasks, which are needed to perform horizontal and vertical integration. This systematic review presents content from 900 articles on Industry 4.0 and optimization as well as 388 articles on Industry 4.0 and scheduling. It is our hope that this work can serve as a starting point for researchers and developers in the field.

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“…Ištoković et al [21] present a simulationoptimization approach to optimize total production cost in HFS. Pekarcikova et al [22] in their paper proposed the introduction of Kanban logic in material flow control to improve machine productivity, machine efficiency and processing time.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021

Teh. vjesn.

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Planning the order and size of batches is an extremely complex task especially if these tasks are related to production companies in a real environment. This research deals with the problem of determining the entry order and size of product batches in order to optimize inter-operational waits, in the form of waiting in queues for processing and waiting due to the setting-up of the workplace. In real environment, these waits represent a large share of the time spent in the production of a unit of product in a hybrid flow shop. This problem is almost impossible to be solved with analytical models because they may require many simplifying assumptions. Therefore, a simulationoptimization approach is used to solve this problem. Discrete event simulation allows greater flexibility in the representation of the real production system, while the integrated optimization tool, a genetic algorithm, serves to find the optimal solution relatively quickly. To ensure simpler production management, batch size is defined as a fixed value with the exception of a different first or last batch which represents the difference to the required production volume. Therefore, two optimization cases are presented in the paper. Although both cases show improvements, the case when a different batch is the first batch shows better results. In that case, the share of setup time in the total production time of the product unit was reduced from 4% to 3%, and the share of waiting time in the queue for processing was reduced from 76% to 32%.

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Material Flow Optimization through E-Kanban System Simulation

Cited by 25 publications

References 14 publications

3D Interactive Learning Environment as a Tool for Knowledge Transfer and Retention

3D Interactive Learning Environment as a Tool for Knowledge Transfer and Retention

Industry 4.0‐Driven Development of Optimization Algorithms: A Systematic Overview

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

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