Application of FlexSim software for developing cyber learning factory for smart factory education and training

Kim, Jun Woo; Park, Jin-Sung; Kim, Soo Kyun

doi:10.1007/s11042-019-08156-1

Cited by 10 publications

(3 citation statements)

References 18 publications

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“…(Baena et al, 2017;Schallock et al, 2018;Wienbruch et al, 2018). Kim et al (2020) proposes a cyber learning factory for operations management developed by applying 3D factory simulation software which can be used to train both operations managers of manufacturing companies and information systems architects of Information Technologies companies in a technical approach. According to Helming et al (2019), managers play a crucial role in leading the implementation and development of Industry 4.0 in a company.…”

Section: Theoretical Background Industry 40 and Trainingmentioning

confidence: 99%

Training for Industry 4.0: a systematic literature review and directions for future research

Cazeri

Santa-Eulalia

Serafim

et al. 2022

BJO&PM

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Goal: This study aims to identify, synthesize and classify the main features explored by current research encompassing training for Industry 4.0 and propose directions for future research. Design / Methodology / Approach: The methodological procedure was oriented by a systematic literature review (PRISMA) methodology and followed by content analysis. After a review of academic databases, 78 papers dealing with training for Industry 4.0 were included and classified based on topics related to the science of training and Industry 4.0. Results: Most of the studies in training for Industry 4.0 are oriented to undergraduate and graduate students (in an educational approach) or industrial employees (in an enterprise approach) and, in general, they explore technical, technological, and human oriented subjects. There is a lack concerning studies targeting managers who deal with Industry 4.0 and few studies consider content related to Industry 4.0 impact on business models, sustainability, corporate social responsibility, and other related concepts. Limitations of the investigation: The main limitation is related to the database selection criteria. Search in non-indexed databases, book chapters, and non-English language are not included in this study. Practical Implications: The findings presented in this paper are relevant for researchers and academics as they can serve as a guide for future research work. Consultants, professionals, and trainers can enhance their courses by including currently less explored content or target audiences. Originality/Value: No similar papers were found in scientific databases and this reinforces this manuscript's originality and contribution.

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Section: Theoretical Background Industry 40 and Trainingmentioning

confidence: 99%

Training for Industry 4.0: a systematic literature review and directions for future research

Cazeri

Santa-Eulalia

Serafim

et al. 2022

BJO&PM

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“…With the advent of the Industry 4.0 era, much attention is being paid to smart factory, which is implemented through integration of traditional manufacturing resources with modern information and communication technology (ICT) infrastructure. [1][2][3] The ultimate goal of smart factory is to strengthen the competitiveness of manufacturing system using ICT capabilities for handling digital data. 4 In other words, the primary role of modern ICT infrastructures in smart factory is to collect a wide range of digital data from manufacturing resources, and the collected data should be utilized 1 in a systematic way for effective operations management.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, advancement of technologies, such as wireless sensor networks and Internet of things (IoT), enable to collect digital data from physical objects in real time. 3,5 Nevertheless, many manufacturing companies still have significant trouble in collecting data suitable for them. Especially, it is difficult to collect and utilize appropriate data about movement of mobile resources, such as human operators, forklifts, and material handling equipment.…”

Section: Introductionmentioning

confidence: 99%

Indoor positioning-based mobile resource movement data management system for smart factory operations management

Park

Lee

Jimenez

et al. 2020

International Journal of Distributed Sensor Networks

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The primary role of modern information and communication technology infrastructures in smart factory is to collect a wide range of digital data from manufacturing resources; however, many manufacturing companies still have significant trouble in collecting data relevant for operations management. Especially, it is difficult to collect data about movement of mobile resources, such as human operators and material handling equipment. Moreover, managers of manufacturing companies often have significant troubles in utilizing the raw data collected by information and communication technology infrastructures due to its complexities and vast amount. To fill these gaps, this article proposes indoor positioning-based mobile resource movement data management system, which can be used to collect and process the mobile resource movement data flexibly. The indoor positioning technologies enable to track the positions of physical objects in real time; however, they generate time series data for 3D coordinates of object position not suitable for practical use. Therefore, this article aims to integrate the indoor positioning technology with a specialized user application, which allows the users to define what kinds of data should be collected and how the raw data should be transformed.

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Framework for Simulation Applications Based on the Digital Twin Concept and SCOR Methodology

Trautwein Neto,

Alcântara Castilho Venâncio,

Rocha Loures

et al. 2023

Lecture Notes in Mechanical Engineering

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Application of FlexSim software for developing cyber learning factory for smart factory education and training

Cited by 10 publications

References 18 publications

Training for Industry 4.0: a systematic literature review and directions for future research

Training for Industry 4.0: a systematic literature review and directions for future research

Indoor positioning-based mobile resource movement data management system for smart factory operations management

Framework for Simulation Applications Based on the Digital Twin Concept and SCOR Methodology

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