Application of TestBed 4.0 Technology within the Implementation of Industry 4.0 in Teaching Methods of Industrial Engineering as Well as Industrial Practice

Kliment, Marek; Pekarčíková, Miriam; Trebuňa, Peter; Trebuna, Martin

doi:10.3390/su13168963

Cited by 12 publications

(4 citation statements)

References 26 publications

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“…The automotive HVAC manikin features a system that includes a carbon epoxy body mould with surface-mounted sensors that measure air velocity, temperature, radiant heat flux, and relative humidity. The sensors are protected to ensure that the manikin is not damaged during loading and positioning [3,4,10]. The HVAC manikin for automobiles ("Automotive HVAC Manikin") is designed so that it can be easily inserted into any vehicle.…”

Section: Hvac Automotive Manikinsmentioning

confidence: 99%

Thermal sensation models for environmental parameters testing

Kralikova¹,

Lumnitzer²

2023

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Currently, there are various complex models that are used to predict the thermal load, or thermal comfort of the employee with different scales for evaluating the feeling of warmth or of cold, with the help of which it is possible not only to speed up the evaluation of the thermal load but also to make it more precise. With the help of thermal manikins, it is possible to simulate human reactions to heat and humidity conditions. The article deals with the possibilities of using thermal manikins as a useful aid in measuring heat exchange between the environment and the human body, testing thermal stress, etc. These tools will then be available for use by the industry to develop more efficient thermal comfort systems.

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Section: Hvac Automotive Manikinsmentioning

confidence: 99%

Thermal sensation models for environmental parameters testing

Kralikova¹,

Lumnitzer²

2023

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“…The literature shows the diversity of Industry 4.0 technologies. This collection includes, among others, (1) big data and analytics [20][21][22][23], (2) autonomous robots [24], (3) simulations [25][26][27][28][29][30], (4) horizontal and vertical system integration [31,32], (5) Internet of Things-IoT [31], (6) cyber-security [33,34], (7) the cloud, (8) additive manufacturing, (9) augmented reality, (10) artificial intelligence [35], (11) mobile technologies, and (12) RFID and RTLS technologies [12,30,[36][37][38][39][40][41][42]. Each solution could be independently implemented as a separate project for the organisation.…”

Section: Literature Reviewmentioning

confidence: 99%

Determining the Level of Use of the Industry 4.0 Solutions in the COVID-19 Pandemic Era: Results of Empirical Research

Michna

Kruszewska

2022

Sustainability

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Changes in the world’s situation and the need to be competitive and less dependent on the global economy lead to improvements in many organisations. Together with business model transformation, using the latest technologies such as augmented reality, autonomous robots, mobile technologies, big data, cloud computing, and others known as an Industry 4.0 pillars, enterprises are changing the industry status quo. These technologies are widely described and studied in the literature, mainly on the example of large production companies. In order to fill the gap, this article had two objectives. The first objective was to investigate the usage of Industry 4.0 technologies in the time of the COVID-19 pandemic. The second one was to verify the strength of the impact of selected barriers on the level of implementation of individual I4.0 technologies and influence of cooperation during technology implementation. To achieve the objectives of the article, quantitative research was conducted. Data from 125 anonymous survey participants were collected in October 2021 and analysed using a statistical tool. The study results revealed that the term Industry 4.0 is known among industry employees. Surveyed organisations are using I4.0 technologies and still planning to implement them in a wider range despite the pandemic situation. Moreover, the most often-cited barriers in the literature on the subject are costs or employees’ acceptations, too-individualised customer requirements, or insufficient standardisation, which affect the implementation of Industry 4.0 solutions with strengths varying from low to moderate intensity. The information in this paper may be of use to Industry 4.0 solution providers or collaborative and partnership organisations.

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“…These systems exhibit a high degree of flexibility and responsiveness, enabling seamless adjustments to changing production requirements. A pivotal tool in the design and analysis of such systems is the creation of a comprehensive digital model [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Digital Model Approach for Adaptive Manufacturing Systems

Grznár,

Burganová,

Mozol

et al. 2023

Applied Sciences

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In the current global economy, where rapid changes and constantly shifting market demands define the competitive landscape, adaptive manufacturing systems become essential for businesses striving to remain relevant and efficient. In the context of this growing need, this study focuses on planning as a part of adaptive manufacturing system. This methodology provides a systematic framework that spans from foundational groundwork to meticulous verification and validation phases. By employing advanced simulation techniques, seamless data integration, and process optimization, this methodology ensures the smooth realization of robust and efficient adaptive manufacturing systems. A detailed case study on competency islands showcases the versatility of this approach, demonstrating its efficacy in enhancing manufacturing agility and overall performance. As a significant contribution to the field of smart manufacturing, this methodology offers a structured blueprint for the realization of adaptive manufacturing systems.

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Application of TestBed 4.0 Technology within the Implementation of Industry 4.0 in Teaching Methods of Industrial Engineering as Well as Industrial Practice

Cited by 12 publications

References 26 publications

Thermal sensation models for environmental parameters testing

Thermal sensation models for environmental parameters testing

Determining the Level of Use of the Industry 4.0 Solutions in the COVID-19 Pandemic Era: Results of Empirical Research

A Comprehensive Digital Model Approach for Adaptive Manufacturing Systems

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