Case Study of Modelling the Logistics Chain in Production

Pekarčíková, Miriam; Trebuňa, Peter; Markovič, Jaromír

doi:10.1016/j.proeng.2014.12.125

Cited by 18 publications

(11 citation statements)

References 1 publication

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“…In the second part, inspired by research findings [16][17][18][19][20][21], interactive virtual training for a drilling operation was created. The training was created in the Unity 3D game engine and several sets of the HTC Vive Pro display device were used for full immersion into VR, using the experience and knowledge of the authors in the field of virtual and augmented reality [22][23][24].…”

Section: Methodsmentioning

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: Methodsmentioning

confidence: 99%

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

et al. 2021

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“…The cost of automated production was lower than labour costs, and it brought a new phenomenon, now known as reshoring. Businesses began to move their production capacity from countries with cheap labour to their parent countries [10]. A good example is large corporations from the US (Intel, General Motors, General Electric).…”

Section: Changing Of Business Priorities Of Factoriesmentioning

confidence: 99%

Modeling and Simulation of Processes in a Factory of the Future

et al. 2020

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Current trends in manufacturing, which are based on customisation and gradually customised production, are becoming the main initiator for the development of new manufacturing approaches. New manufacturing approaches are counted as the application of new behavioural management patterns that calculate the retained competencies of decision-making by the individual members of the system agent; the production becomes decentralised. The interaction of the members of such a system creates emergent behaviour, where the result cannot be accurately determined by ordinary methods and simulation must be applied. Modelling and simulation will, therefore, be an integral part of the planning and control of the processes of factories of the future. The purpose of the article is to describe the use of modelling and simulation processes in factories of the future. The first part of the article describes new manufacturing concepts that will be used in factories of the future, with a description of modelling and simulation routing in the frame of Industry 4.0. The next section describes how simulation is used for the control of manufacturing processes in factories of the future. The included subsection describes the implementation of this suggested pattern in the laboratory of ZIMS (Zilina Intelligent Manufacturing System), with an example of a metamodeling application and the results obtained.

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“…• high costs for overtime work; formation of request queues (possible loss of profit due to queues). Between the extreme variants, there is a number of possible variants of dimensioning the vehicle fleet that are associated with the different daily costs of transportation [12,13]. Of the possible variants, it is necessary to choose the optimal variant -the one with the lowest daily costs for transportation.…”

Section: Analysis Of the Solutionmentioning

confidence: 99%

Fleet Optimization Based on the Monte Carlo Algorithm

Lampa¹,

Samolejová²

2020

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With the development of computers and software products, there is now greater use of quantitative methods in industrial enterprises when making managerial decisions. One of the most applicable solutions to computer simulation algorithms is the Monte Carlo method. The application of the Monte Carlo algorithm lies in finding a relation between the individual variables, which are the solutions to the problem and represent the characteristics of random processes reproducible on computers. The aim of this article is to show the application of simulations from the Monte Carlo algorithm using the example of optimising vehicle fleet capacity so that the total daily costs spent on transporting goods are minimal.

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Case Study of Modelling the Logistics Chain in Production

Cited by 18 publications

References 1 publication

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

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

Modeling and Simulation of Processes in a Factory of the Future

Fleet Optimization Based on the Monte Carlo Algorithm

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