DATA-DRIVEN DECISION-MAKING SYSTEM FOR INJECTION MOLDING PRODUCTION AND MAINTENANCE
Keywords:
Injection molding production, Edge computing, Equipment health, Maintenance decision-makingAbstract
A data-driven injection molding production and maintenance decision-making system is designed to address the issues of low efficiency and poor real-time performance in traditional data collection models, meeting the modern industrial needs for high reliability and intelligence. The system adopts a three-layer architecture, including data collection, edge computing, and maintenance decision-making layers. It achieves real-time collection and processing of multi-source heterogeneous data to assess equipment health status dynamically and predict failures. The data collection layer integrates sensor, PLC, and visual device data; the edge computing layer processes key parameters through lightweight models to reduce cloud-side pressure; the maintenance decision-making layer predicts the remaining life of the equipment using the Weibull distribution model and optimizes maintenance strategies. The system proposes a quantitative evaluation index for the health of the injection molding machine and utilizes a weighted fusion algorithm for accurate maintenance decisions, significantly reducing operational costs and improving production efficiency, providing a feasible technical solution for intelligent manufacturing.References
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