Synchronization in manufacturing systems: quantification and relation to logistics performance

Chankov, Stanislav; Hütt, Marc‐Thorsten; Bendul, Julia C.

doi:10.1080/00207543.2016.1165876

Cited by 33 publications

(10 citation statements)

References 52 publications

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“…In the literature, there are two different views on synchronization (Chankov, Huett, & Bendul, 2016, 2018): (i) logistic synchronization, which originated in the manufacturing and logistics research domain and focuses on material flows and (ii) physics synchronization, which originated in the natural sciences domain and refers to the adjustment of rhythm of the production processes in a manufacturing system. Physics synchronization in our simulations refers to creating synchronized behavior across students.…”

Section: Discussionmentioning

confidence: 99%

“…Since physics synchronization realizes material flow, it follows that logistic synchronization (i.e., the synchronization of material flows) is dependent on it. This may explain the counterintuitive results in Chankov et al (2016). They found that logistics synchronization, which is widely assumed in the literature to have a positive effect, seems to have a negative effect on system performance, while physics synchronization, which has been ignored by manufacturing practice and research, is shown to be strongly correlated with the performance of manufacturing systems.…”

Section: Insight 2: Physics Synchronization Is Essential For Logisticmentioning

confidence: 98%

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Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Thürer

Cole

Hanna

et al. 2020

Decision Sci J Innov Edu

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When introducing production control solutions, most textbooks focus on a to-stock, repetitive context. In response, we extend the classical match-and-dice game, which also assumes a repetitive context, to teach complexities that emerge in a nonrepetitive setting, such as the appearance of direct and indirect load, and to introduce appropriate production control solutions (e.g., Constant Work-In-Process [ConWIP] and Control of Balance by Card Based Navigation [COBACABANA]). Two field tests were used to prove the playability of our game and assess its teaching effectiveness using postgame scores and self-assessment. Both test results give support to our game and highlight that it helps students to understand complex production control issues. Applying the simulation as part of an iterative design process not only ensured the pragmatic validity of our design, but also provided important insights on the production control systems being taught. During the application, we encountered several issues associated with the implementation of these production control systems in practice. In terms of theory, applying the simulation showed that there is a change in mindset required when switching † Corresponding Author. 568 Thürer et al. 569 from Kanban to COBACABANA, and physics synchronization is essential for logistics synchronization.

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Section: Discussionmentioning

confidence: 99%

Section: Insight 2: Physics Synchronization Is Essential For Logisticmentioning

confidence: 98%

Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Thürer

Cole

Hanna

et al. 2020

Decision Sci J Innov Edu

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show abstract

“…This model did not take into account time delays in the flow of information and/or materials that exist in reality. To evaluate different synchronisation scenarios (Chankov et al 2016), over a specific time period T, we introduce the performance indicator "Mean Synchronisation Performance" MSP with…”

Section: Seat Supply Process Of German Car Manufacturermentioning

confidence: 99%

Modelling Oscillations in the Supply Chain: The Case of a Just-in-Sequence Supply Process from the Automotive Industry

Klug

2021

Preprint

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Pervasive and ubiquitous oscillations, mapping the repetitive variation in time of a specific state, are well known as abundant phenomena in research and practice. Motivated by the success of oscillators in the modelling, analysis and control of dynamical systems, we developed a related approach for the dynamic description of supply chains. This paper aims to introduce a generic oscillator model for supply chains by the original application of oscillator equations. Therefore an established oscillator model for deductive modelling of supply chain echelons is used. With the help of coupled van der Pol oscillators, the dynamical interaction of an inventory system is described and applied to a real-life supply process in automotive industry. According to its reductionist approach only two differential equations are used to analyse a Just-in-Sequence supply process in car industry. Based on the fact that any oscillatory state can be reduced to the phase of the oscillation (phase reduction), a phase space map is generated. This compact visual reference of the supply process can act as the quantitative basis for an adaptive control mechanism during its operation. By delaying or accelerating the inventory oscillations of the supplier stock a detuned coupled supply process can be re-synchronised without changing the amplitude. An additional analysis of Hilbert transform is applied to determine the boundaries of phase-locking between the inventory oscillation phases, where the instantaneous phases are bounded. Furthermore parameters of the synchronisation threshold and the transient phases between synchronous and non-synchronous regimes have been investigated, supported by an Arnold tongue representation. The investigations show that with the help of a generic oscillatory model it is possible to measure and quantify phenomena of inventory dynamics in supply chains. Especially the analysis of synchronisation phenomena with the help of phase space and Arnold tongue representations foster developments of performance measurement in supply chain management.

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“…For this reason [27], TOC focuses on the weakest points of the productive chain since it groups them instead of considering them independent from one another. This allows us to deal with the limitations by asking [3] basic questions: what to change? What has changed and how to use the change?…”

Section: Development Model Proposalmentioning

confidence: 99%

“…For this purpose, the proposed model consists of [2] stages. The diagnosis is implemented in [3] steps.…”

Section: Case Wherein the Proposed Model Is Appliedmentioning

confidence: 99%

Lean optimization model for managing the yield of pima cotton (gossipier Barba dense) in small- and medium-sized farms in the Peruvian coast areas

Rojas

Quispe

Raymundo

2018

IJET

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This study proposes a lean manufacturing-based optimization model to standardize “Pima cotton” crop yields in the Peruvian coast areas toward the north of Piura as the study area. The study also discusses how Pima cotton is grown in the Peruvian cost areas. This is represented in 2 stages: diagnosis and development of the cotton crop model. The diagnosis stage consists of 3 steps, and the development stage consists of 2 steps. The interrelation of each stage has been identified with the lean manufacturing principle for the improvement of crop yield. Results showed that to increase current crop yield in Piura to 172 bushels/ha as well as determine the quantities of resources and raw materials required considering a standardized crop production process. The limitations of the research depend on the climatic conditions in Peru. The main contribution of this research is to propose a model using which farmers may produce Pima cotton by utilizing the indicators proposed to increase the process control. In addition, the paper proposes a standardized crop production process that farmers must follow, supported by a mathematical model simulation.

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Synchronization in manufacturing systems: quantification and relation to logistics performance

Cited by 33 publications

References 52 publications

Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Classroom Simulations for Teaching Production Control in Nonrepetitive Contexts: Insights for Theory and Practice

Modelling Oscillations in the Supply Chain: The Case of a Just-in-Sequence Supply Process from the Automotive Industry

Lean optimization model for managing the yield of pima cotton (gossipier Barba dense) in small- and medium-sized farms in the Peruvian coast areas

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