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Case Study: Testing the Overall Efficiency of Equipment in the Production Process in TX Plant Simulation Software

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Warianty tytułu
Języki publikacji
EN
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EN
The article deals with a widely used method of measuring the overall efficiency of equipment (OEE), which in combination with technologies and software tools is gaining in importance. The overall efficiency of OEE equipment is a key performance metric for machines and equipment to identify hidden capacities and increase production productivity. The intensification of Industry 4.0 in traditional manufacturing companies supports and creates the conditions for their transformation into a smart factory. The integration of intelligent machines and devices with complex human-machine communication network systems requires a new direction in measuring and increasing OEE. Mass customization, resp. personalization of production raises a high need to monitor, improve and further maintain productivity. The aim of the article is to create a simulation model of the production process and test the energy consumption of selected equipment using TX Plant Simulation software with a proposal of measures to increase the OEE of the company.
Twórcy
  • Department of Industrial and Digital Engineering, Technical University of Košice, Faculty of Mechanical Engineering, Park Komenského 9, 040 00, Košice, Slovak Republic
  • Department of Industrial and Digital Engineering, Technical University of Košice
  • Department of Industrial and Digital Engineering, Technical University of Košice
autor
  • Department of Industrial and Digital Engineering, Faculty of Mechanical Engineering, Technical University of Košice, Slovak Republic
autor
  • Department of Industrial and Digital Engineering, Faculty of Mechanical Engineering, Technical University of Košice, Slovak Republic
autor
  • Department of Industrial and Digital Engineering, Faculty of Mechanical Engineering, Technical University of Košice, Slovak Republic
  • Department of Industrial and Digital Engineering, Faculty of Mechanical Engineering, Technical University of Košice, Slovak Republic
Bibliografia
  • Agárdi A. and Nehéz, K. (2021), The Unrelated Parallel Machines Scheduling Problem with Machine and Job Dependent Setup Times, Availability Constraints, Time Windows and Maintenance Time, Management and Production Engineering Review, Vol. 12, No. 3, pp. 15–24. DOI: 10.24425/mper.2021.138527.
  • Bangsow S. (2015), Tecnomatix Plant Simulation. Modeling and Programming by means of examples, Springer, Switzerland.
  • Barosz P., Gołda G. and Kampa A. (2020), Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators, Applied Science, Vol. 10. DOI: 10.3390/app10082862.
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  • Clarke P. (2022), The Relevance of OEE in the Industry 4.0 and Smart Factory Era, online: https://slcontrols.com/the-relevance-of-oee-in-theindustry-4-0-and-smart-factory-era/ [date of Access February, 2022].
  • Clarke P. (2022), The Relevance of OEE in the Industry 4.0 and Smart Factory Era, online: https://slcontrols.com/the-relevance-of-oee-in-theindustry-4-0-and-smart-factory-era/ [date of Access February, 2022].
  • El Ahmadi SEA. and El Abbadi L. (2022), Reducing Flow Time in an Automotive Asynchronous Assembly Line - An application from an automotive factory, Management and Production Engineering Review, Vol. 13, No. 1, pp. 99–106. DOI: 10.24425/mper.2022.140880.
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  • Focke M. and Steinbeck J. (2018), Steigerung der Anlagenproduktivität durch OEE-Management Definitionen, Vorgehen und Methoden - von manuell bis Industrie 4.0, Springer Gabler, Wiesbaden, Germany, ISSN 2197-6708.
  • Fusko M., Buckova M, Gaso M., Krajcovic M., Dulina L. and Skokan R. (2019), Concept of LongTerm Sustainable Intralogistics in Plastic Recycling Factory, Sustainability, Vol. 11, No. 23. DOI: 10.3390/su11236750.
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  • Lindegren M.L., Lunau M.R. and da Silva E.R. (2022), Combining simulation and data analytics for OEE improvement, International Journal of Simulation Modelling, 2022, Vol. 21, No. 1, pp. 29–40. DOI: 10. 2507/IJSIMM21-1-584.
  • LeanProduction. OEE (Overall Equipment Effectiveness), https://www.leanproduction.com/oee/ [date of Access February, 2022]
  • Moravec M., Badida M., Mikusova N., Sobotova L., Svajlenka J. and Dzuro T. (2021), Proposed Options for Noise Reduction from a Wastewater Treatment Plant: Case Study. Sustainability, Vol. 13, pp. 2409. DOI: 10.3390/su13042409.
  • Ondov M., Andrea R., Sofranko M., Feher J., Cambal J. and Feckova Skrabulakova E. (2022), Redesigning the Production Process Using Simulation for Sustainable Development of the Enterprise, Sustainability, Vol. 14, No. 3, pp. 1514. DOI: 10.3390/su14031514.
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  • Saderova J., Rosova A., Kacmary P., Sofranko M., Bindzar P. and Malkus T. (2020), Modelling as a Tool for the Planning of the Transport System Performance in the Conditions of a Raw Material Mining, Sustainability, Vol. 12, p. 8051. DOI: 10.3390/su12198051.
  • Saniuk S., Grabowska S. and Straka M. (2022), Identification of Social and Economic Expectations: Contextual Reasons for the Transformation Process of Industry 4.0 into the Industry 5.0 Concept, Sustainability, Vol. 14, No. 3. DOI: 10.3390/su14031391.
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  • Straka M., Khouri S., Lenort R. and Besta P. (2020a), Improvement of logistics in manufacturing system by the use of simulation modelling: A real industrial case study, Advances in Production Engineering and Mangement, Vol. 15, No. 1, ppl 18–30. DOI: 10.14743/apem2020.1.346.
  • Straka M., Tausova M., Rosova A., Cehlar M., Kacmary P., Sisol M., Ignacz P. and Farkas C. (2020b), Big Data Analytics of a Waste Recycling Simulation Logistics System, Polish Journal of Envirnmental Studies, Vol. 29, No. 3, pp. 2355–2364. DOI: 10.15244/pjoes/108684.
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  • SIMTech (2022), REAL-TIME OEE FOR INDUSTRY 4.0, https://www.a-star.edu.sg/simtech/kto/ advanced-manufacturing/real-time-oee [date of Access February, 2022]
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-799a7628-245a-4494-b1ba-b34bcadf64fd
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