Assessing the Impact of Disturbance Factors on Manufacturing Enterprise Scheduling
AUTHORS
Mayur Qumer Collins,Western Sydney University, Rydalmere, Australia
Estrella Galbraith,Western Sydney University, Rydalmere, Australia
ABSTRACT
This research paper investigates the impact of various disturbance factors on manufacturing enterprise scheduling. Factors such as machine breakdowns, supply chain interruptions, and fluctuating customer demands can significantly disrupt production schedules and reduce operational efficiency. To address these issues, this study systematically describes and classifies disturbance factors based on their specific impacts and characteristics. Given the complex and often uncertain nature of these disturbances, a novel approach utilizing a fuzzy neural network is proposed to assess and mitigate their effects. This method aims to improve the accuracy and adaptability of scheduling decisions, thereby enhancing the resilience and efficiency of production processes. Through simulation experiments with real-world scenarios, the proposed approach's effectiveness is validated, demonstrating notable improvements in schedule reliability and overall operational performance. The findings underscore the potential of fuzzy neural networks in providing robust solutions for managing uncertainty in manufacturing scheduling, offering valuable insights for both practitioners and researchers in the field.
KEYWORDS
Disturbance factors, Manufacturing enterprise scheduling, Fuzzy neural network
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