Some Remarks on the Stability of Production Networks

Scholz‐Reiter, Bernd; Wirth, Fabian; Freitag, Michael; Jagalski, Thomas; Beer, Christoph de; Rüffer, Björn S.

doi:10.1007/3-540-32539-5_15

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…The sequencing of waiting production orders is generally based on order specific criteria, e.g., planned due dates. Some approaches also assign production orders to preferred workstations with the possibility of alternative workstation assignments depending on the queue length [11]. These approaches show that autonomous control methods already partially integrate…”

Section: Coupling Strategiesmentioning

confidence: 99%

Evaluation of Strategies for the Coupling of Central Planning and Autonomous Control in Dynamic Job Shop Environments

Schukraft

Grundstein

Freitag

et al. 2016

AMR

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Autonomous control is a promising approach to cope with increasing dynamics in production environments. However, an important issue for the acceptance of autonomous control is the provision of a sufficient planning accuracy, e.g., regarding order sequences or workstation assignments. Therefore, transferring autonomous control into practical application requires the coupling of autonomous control with commonly used central planning methods. This paper introduces coupling strategies with different degrees of planning adherence. The introduced strategies are applied to the example of a job shop environment based on real data. The simulation-based comparison considers performance indicators concerning the logistic performance and planning adherence. Besides varying the level of dynamic influences, the simulation study also analyses the impact of different method combinations onto the coupled methods’ performance.

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Section: Coupling Strategiesmentioning

confidence: 99%

Evaluation of Strategies for the Coupling of Central Planning and Autonomous Control in Dynamic Job Shop Environments

Schukraft

Grundstein

Freitag

et al. 2016

AMR

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“…An approach with flows of multiple fluids was used to analyze the stability region of an autonomously controlled shop floor scenario [24]. ScholzReiter et al [25] presented a fluid model of a production network and obtained a stability region for a scenario with two locations and three types of products.…”

Section: Mathematical Modeling and Stability Analysismentioning

confidence: 99%

Modeling and stability analysis of autonomously controlled production networks

et al. 2011

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We present methods and tools for modeling autonomously controlled production networks and investigation of their stability properties. Production networks are described as interconnected dynamical systems of two types: systems of ordinary differential equations and timedelay systems. In particular with the help of time-delays, we incorporate transportation times and implement an autonomous control method, namely the queue length estimator. By stability, we mean roughly speaking, boundedness of the state of a system (e.g., the inventory level or the work in progress) over the time under bounded external inputs. In our stability analysis, we consider the case, when all the subsystems describing logistics locations are stable. We derive sufficient conditions that guarantee stability of the network. To this end, we utilize Lyapunov functions and a small gain condition.

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“…After the goal is achieved and needs are changed, the networking relationship will be adjusted accordingly. Secondly, it indicates the harmonious and fluctuated stability [13], for the networking relationship is always subject to change, movement and conflict, only when all the members in the network think the benefits they can get from the network are bigger than the cost to terminate the relationship, will they remain in the network, and the state is stable.…”

Section: Stability Of Semiconductor Modular Production Networkmentioning

confidence: 99%

Game Analysis of Determinants of Stability of Semiconductor Modular Production Networks

Chen

2014

Sustainability

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In today's rapidly changing environment, semiconductor manufacturers compete more in the area of modular production networks. However, the instability of semiconductor modular production networks can to a large extent lead to the failure of these networks. The aim of this paper is to discuss the significance and explore the maintenance of the stability of these semiconductor modular production networks. Firstly, this paper qualitatively and quantitatively defines the stability of semiconductor modular production networks. Based on this, by establishing game models, this paper analyzes the influence mechanism of the main factors: external market fluctuation, the internal benefit allocation mechanism, and opportunism, which can jeopardize the stability of these networks. We find that: the greater the benefits a member enterprise derives from the common benefits, the more likely it is the member enterprise will not exit the modular production network; the adaptive ability of the networks to the external environment is closely related to the stability of the modular production networks; the supervision and punishment in networks can be substituted for each other and the level of supervision, punishment and trust can exert great influence on the stability of semiconductor modular production networks. Lastly, we propose some specific suggestions.

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Some Remarks on the Stability of Production Networks

Cited by 6 publications

References 6 publications

Evaluation of Strategies for the Coupling of Central Planning and Autonomous Control in Dynamic Job Shop Environments

Evaluation of Strategies for the Coupling of Central Planning and Autonomous Control in Dynamic Job Shop Environments

Modeling and stability analysis of autonomously controlled production networks

Game Analysis of Determinants of Stability of Semiconductor Modular Production Networks

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