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Title | Modeling of the manufacturing systems state in the conditions of the lean production |
Authors |
Diadiura, Kostiantyn Oleksandrovych
Hrebeniuk, Larysa Fedorivna Krenicky, T. Zaborowski, T. |
ORCID |
http://orcid.org/0000-0002-7575-9711 |
Keywords |
Lean production value stream manufacturing systems manufacturing process resource markov techniques |
Type | Article |
Date of Issue | 2021 |
URI | https://essuir.sumdu.edu.ua/handle/123456789/84686 |
Publisher | MM Science Journal, Czech Republic |
License | Creative Commons Attribution 4.0 International License |
Citation | Dyadyura, Konstantin & Hrebenyk, Liudmyla & Krenicky, Tbor & Zaborowski, Tadeusz. (2021). Modeling of the manufacturing systems state in the conditions of the lean production. MM Science Journal. 2021. 4408-4413. 10.17973/mmsj.2021_6_2021024. |
Abstract |
This article investigates the hierarchy of the manufacturing
system, which consists of a set of interrelated processes aimed
at converting information, knowledge, energy, materials, and
other resources into value for the consumer based on the
principles of lean production. Modern manufacturing systems
are becoming more and more complex to manage. The
problems that need to be solved are associated with a
significant number of time-varying parameters, large time
delays, high non-linearity of processes, and a complex
relationship between input and output parameters. Depending
on the parameters of internal components and characteristics
of external conditions, the state of manufacturing systems can
change in an unpredictable manner. The paper considers many
types of discrete states in which the system can be. The
estimation of the probability of finding the manufacturing
system in any of the given states was carried out using discrete
Markov analysis. The article also presents the results of studies
of possible transitions between states in which the production
system is presented in the form of a transition matrix. |
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File | Size | Format | Downloads |
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Diadiura_et.al_Modeling_of_the_manufacturing_systems_state_mmscience_2021-06.pdf | 1.3 MB | Adobe PDF | 435435257 |
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