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Proposal of the risk assessment model of vehicle construction systems' safety under the conditions of Industry 4.0
 
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Department of Transport and Logistics, Institute of Technology and Business in České Budějovice, Faculty of Technology, Czech Republic
 
These authors had equal contribution to this work
 
 
Submission date: 2024-02-02
 
 
Final revision date: 2024-03-07
 
 
Acceptance date: 2024-03-14
 
 
Publication date: 2024-03-28
 
 
Corresponding author
Ondrej Stopka   

Department of Transport and Logistics, Institute of Technology and Business in České Budějovice, Faculty of Technology, Okružní 517/10, 37001, České Budějovice, Czech Republic
 
 
The Archives of Automotive Engineering – Archiwum Motoryzacji 2024;103(1):77-94
 
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ABSTRACT
With the introduction of the concept of the industry 4.0, automation, robotics, artificial intelligence, communication methods, automotive engineering, mechanics, construction and operation of automotive vehicles, and so on, as well as the methods of corporate management are changing. Following this concept, new risks emerge, when workers have to cooperate with collaborative robots, autonomous systems, artificial intelligence, machine learning and learn new methods different from previous processes and systems. The paper first presents the theoretical background related to the topic addressed. The next sections encompass the literature review, including a list of references relevant to achieving the main objective of the paper, as well as a description of the research methods used in the paper. With regard to the main objective, quantitative research concerning the vehicle construction systems' safety issues in industry 4.0 was conducted; i.e., a questionnaire survey was developed within a sufficiently representative sample of respondents. After conducting the survey, the risk assessment model of vehicle construction systems' safety under the conditions of Industry 4.0 was proposed while applying the principles of system dynamics. An integral part of the paper is represented by the discussion of the obtained results and benefits, as well as the formulation of relevant conclusions.
REFERENCES (23)
1.
Allen T.: Family-supportive work environments: The role of organizational perceptions. Journal of Vocational Behaviour. 2001, 58(3), 414–435, DOI: 10.1006/jvbe.2000.1774.
 
2.
Amin Md.T, Khan F.: Risk assessment in Industry 4.0. Methods in Chemical Process Safety. 2022, 6, 631–651, DOI: 10.1016/bs.mcps.2022.05.003.
 
3.
BAuA. Stressreport Deutschland 2019: Psychische Anforderungen, Ressourcen und Befinden. Dortmund, Berlin, Dresden: Federal Institute for Occupational Safety and Health. 2020, DOI: 10.21934/baua:bericht20191007.
 
4.
Brauner C., Wöhrmann A., Frank K., Michel A.: Health and work-life balance across types of work schedules: A latent class analysis. Applied Ergonomics. 2019, 81, 102906, DOI: 10.1016/j.apergo.2019.102906.
 
5.
British Academy. The impact of artificial intelligence on work. The Royal Society. London, Great Britain, 2018.
 
6.
Coyle G.: Qualitative and Quantitative Modelling in System Dynamics: Some Research Questions. System Dynamics Review. 2000, 16(3), 225–244, DOI: 10.1002/1099-1727(200023)16:3<225::AID-SDR195>3.0.CO;2-D.
 
7.
Deutsch A., Frerichs L., Perry M., Jalali M.S.: Making Systems Modeling for Syndemics Useful: Challenges and Recommendations for Balancing Qualitative Understanding and Quantitative Questions. 2022, DOI: 10.2139/ssrn.4238173.
 
8.
Falconi S.M., Palmer R.N.: An interdisciplinary framework for participatory modeling design and evaluation—What makes models effective participatory decision tools? Water Resources Research. 2017, 53(2), 1625–1645, DOI: 10.1002/2016WR019373.
 
9.
Forrester J.W.: Principles of Systems: Text and Workbook Chapters 1 through 10. System Dynamics Society. 2022, 392.
 
10.
Gualtieri L., Rauch E., Vidoni R.: Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review. Robotics and Computer-Integrated Manufacturing. 2021, 67, 101998, DOI: 10.1016/j.rcim.2020.101998.
 
11.
Hendl J.: Qualitative Research: Basic theory, Methods and Applications (Kvalitativní výzkum: základní teorie, metody a aplikace). Prague, Karolinum, Czech Republic, 2016, (in Czech).
 
12.
Javaid M., Haleem A., Singh R.P., Suman R., Gonzalez E.S.: Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability. Sustainable Operations and Computers. 2022, 3, 203–217, DOI: 10.1016/j.susoc.2022.01.008.
 
13.
Jung M., Lim S., Chi S.: Impact of Work Environment and Occupational Stress on Safety Behavior of Individual Construction Workers. International Journal of Environmental Research and Public Health. 2020, 17(22), 8304, DOI: 10.3390/ijerph17228304.
 
14.
Leso V., Fontana L., Iavicoli I.: The occupational health and safety dimension of Industry 4.0. Med Lav. 2018, 110(5), 327–338, DOI: 10.23749/mdl.v110i5.7282.
 
15.
Pečman J., Luptak V.: Cleanliness Test for Variable Packaging Solutions in the Automotive Supply Chain. The Archives of Automotive Engineering – Archiwum Motoryzacji. 2021, 91(1), 49–62, DOI: 10.14669/AM.VOL91.ART4.
 
16.
Pizoń J., Gola A.: The Meaning and Directions of Development of Personalized Production in the Era of Industry 4.0 and Industry 5.0. Lecture Notes in Mechanical Engineering. 2023, 1-13, 279569, DOI: 10.1007/978-3-031-09360-9_1.
 
17.
Richnák P.: Current Perspectives on Development of Industry 4.0 in Logistics of Machinery and Equipment Industry in Slovakia. LOGI – Scientific Journal on Transport and Logistics. 2022, 13(1), 25–36, DOI: 10.2478/logi-2022-0003.
 
18.
Soualhi M., Nguyen K.T.P., Medjaher K.: Pattern recognition method of fault diagnostics based on a new health indicator for smart manufacturing. Mechanical Systems and Signal Processing. 2020, 142, 106680, DOI: 10.1016/j.ymssp.2020.106680.
 
19.
Speth C.: The SWOT analysis: A key tool for developing your business strategy. Lemaitre Publishing, Belgium, 2015.
 
20.
Štědroň B., Potůček M., Knápek J., Mazouch P.: Prognostic methods and their application (Prognostické metody a jejich aplikace). C.H. Beck, Prague, Czech Republic, 2012, (in Czech).
 
21.
Stoma M., Caban J., Dudziak A., Kuranc A.: Selected aspects of the road traffic safety management system. Communications - Scientific Letters of the University of Žilina. 2021, 23(2), F33–F42, DOI: 10.26552/COM.C.2021.2.F33-F42.
 
22.
Witt A.: Determination of the Number of Required Charging Stations on a German Motorway Based on Real Traffic Data and Discrete Event-Based Simulation. LOGI – Scientific Journal on Transport and Logistics. 2023, 14(1), 1–11, DOI: 10.2478/logi-2023-0001.
 
23.
Wolstenholme E.F.: Qualitative vs quantitative modelling: the evolving balance. Journal of the Operational Research Society. 1999, 50(4), 422–428, DOI: 10.1057/palgrave.jors.2600700.
 
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