Notice of Retraction: Study on Confirming Increasable Bottleneck Device in Complex Product Dynamic Scheduling
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This article has been retracted by the publisher.Identification
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Material Flow
Production control
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Material requirements planning
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A variety of established approaches exist for the detection of dynamic bottlenecks. Furthermore, the prediction of bottlenecks is experiencing a growing scientific interest, quantifiable by the increasing number of publications in recent years. Neglected, on the other hand, is the diagnosis of occurring bottlenecks. Detection methods may determine the current location of a bottleneck, while predictive approaches may indicate the location of an upcoming bottleneck. However, mere knowledge of current and future bottlenecks does not enable concrete actions to be taken to avoid the bottlenecks, nor does it open up any immediate advantage for manufacturing companies. Since small and medium-sized companies in particular have limited resources, they cannot implement improvement measures for every bottleneck that occurs. Due to the shifts of dynamic bottlenecks, the selection of the mostsuitable stations in the value stream becomes more difficult. This paper therefore contributes to the neglected field of bottleneck diagnosis. First, we propose two data-driven metrics, relative bottleneck frequency and relative bottleneck severity, which allow a quantitative assessment of the respective bottleneck situations. For validation purposes, we apply these metrics in nine selected scenarios generated using discrete event simulation in a value stream with a serial manufacturing line. Finally, we evaluate and discuss the results.
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The performance of a manufacturing or logistic system is determined by its constraints. Therefore, in order to improve the performance, it is necessary to improve the constraints, also known as the bottlenecks. Finding the bottlenecks, however, is not easy. We compare the two most common bottleneck detection methods, based on the utilization and the waiting time, with the shifting bottleneck detection method developed by us, for AGV systems. We find that the two conventional methods have many shortcomings compared to the shifting bottleneck detection method. In the example presented here, conventional methods are either unable to detect the bottleneck at all or detect the bottleneck incorrectly. The shifting bottleneck detection method not only finds the bottlenecks but also determines the magnitude of the primary and secondary bottlenecks.
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One of the conventional ways of dispersing information in a university or corporate office is through the Notice Board. Notice boards are an ideal platform that allows one to put up information so that it can be seen by everyone. Whenever there is a new circular to be dispersed among the students or employees, it will be immediately put up on the notice board where everyone has to manually gather at the board and look into the notice. In the busy and fast moving world today, this will lead to wastage of time. Instead, this paper provides a solution to the above problem using NFC application. The idea that has been proposed in this paper is to display the notice board through NFC tags. Each NFC tag is programmed to contain the notice information to display. Whenever it is required for a circular to be displayed just program (Update the Notice) the NFC tag. The students, employees etc., can scan the NFC tag through their NFC enabled smart phones which downloads the notice in the document format online into their handheld devices. This solution is user-friendly as the end-user can read the notices at their own convenient time in turn leads no wastage of time.
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The performance of a manufacturing or logistic system is determined by its constraints. Therefore, in order to improve the performance, it is necessary to improve the constraints, also known as the bottlenecks. Finding the bottlenecks, however, is not easy. This paper compares the two most common bottleneck detection methods, based on the utilization and the waiting time, with the shifting bottleneck detection method developed by us, for AGV systems. We find that the two conventional methods have many shortcomings compared to the shifting bottleneck detection method. In the example presented here, conventional methods are either unable to detect the bottleneck at all or detect the bottleneck incorrectly. The shifting bottleneck detection method not only finds the bottlenecks but also determines the magnitude of the primary and secondary bottlenecks.
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The nationally-recognized Susquehanna
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