Abstract
Asynchronous serial manufacturing lines that fabricate discrete parts are traditionally used in mass production, which represents a key sector in the global economy. Recent technological solutions for the modularization and standardization of manufacturing stations have led to this type of manufacturing system being reconfigured more often than in the past. Therefore, synthetic but accurate performance-evaluation models have become relevant as kernels in decision supporting tools for the continuous improvement of manufacturing systems. This paper presents a novel analytical model for the performance evaluation of asynchronous unreliable manufacturing lines fabricating discrete parts with finite buffers and deterministic processing times. This approach is based on continuous-time continuous-flow Markov chains. The general concept of operational cycles in discrete production is integrated into the modeling. The proposed model was validated using a discrete event simulation. The results demonstrate the accuracy and robustness of this model in evaluating a wide set of performance measures. The advantages of using this approach with respect to a purely continuous model were demonstrated. The applicability of the model to actual industrial scenarios was also demonstrated in a use case involving a high-volume assembly line.
Published Version
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