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- W2891886573 abstract "Abstract Because bottlenecks limit the throughput of production systems, it is important to correctly detect and control them. This task is especially demanding in high-speed dynamic production environments within asynchronous production lines. A change in conditions often shifts the bottleneck from one process to another. This paper proposes a data-driven concept for the detection of dynamic bottlenecks in multi-variant production lines. We build on and contribute to the literature of bottleneck detection methods. We propose a novel concept that dynamically and automatically detects bottlenecks using cycle time data from shop-floor machines. The cycle time distribution of produced batches is translated into the cumulative probability function, which is used to detect the moving bottlenecks." @default.
- W2891886573 created "2018-09-27" @default.
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- W2891886573 date "2018-01-01" @default.
- W2891886573 modified "2023-10-06" @default.
- W2891886573 title "Data-driven detection of moving bottlenecks in multi-variant production lines" @default.
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- W2891886573 doi "https://doi.org/10.1016/j.ifacol.2018.08.251" @default.
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