Developing a Customer Oriented Lean Production System Using Axiomatic Design and Fuzzy Value Stream Mapping

Yılmaz, Ömer Faruk; Özçelik, Gökhan; Yeni, Fatma Betül

doi:10.1007/978-3-030-42188-5_9

Cited by 2 publications

(1 citation statement)

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“…In some researches [Panda 2014[Panda , 2018a[Panda ,b, 2019Valicek 2016, Macala 2009Pandova 2018, Flegner 2019, Markulik 2016, Prislupcak 2014] developed a method for assessing the individual properties of a system, which allows determining the parameters of the operating state and longevity of functioning, including manufacturing systems. Some authors [Yılmaz 2020, Zhang 2019, Gelmez 2020, Razali 2020, Kopylov 2020] offered an interesting and accessible research tool that involves the creation of a value stream mapping (VSM) using estimates of lean manufacturing in combination with discrete event modeling. Some authors [Jbara 2019, Asokan 2020] used another compact conceptual approach  Object-Process Methodology (OPM), which is considered as an up-to-date methodology for modeling the components of complex, multidisciplinary dynamic systems and for decision support using information technologies.…”

Section: Introductionmentioning

confidence: 99%

Modeling of the Manufacturing Systems State in the Conditions of the Lean Production

Dyadyura¹,

Hrebenyk²,

Krenický³

et al. 2021

MM SJ

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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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