ABSTRACT The current work addresses an industrial problem related to injection moulding manufacturing with focus on mould wear-out prediction. Real data sets are provided by an industrial partner that uses a multitude of moulds with different shapes and sizes in its production. An analysis of the data is presented and begins with clustering the moulds based on their characteristics and pre-chosen running settings. Using the results of the clustering, the mould wear-out is modelled using Kaplan-Meier survival curves. Furthermore, a random survival forest model is fitted for comparison and model performance is assessed. The main novelty of the case study is the implementation of mould wear-out prediction in real-time with the outcomes presented in terms of conditional survival curves including a proposed early warning system. For visualization and further industrial implementation, an R Shiny dashboard is developed and presented.

中文翻译：

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注塑行业模具磨损预测：案例研究

摘要 当前的工作解决了与注塑成型制造相关的工业问题，重点是模具磨损预测。真实数据集由工业合作伙伴提供，该合作伙伴在其生产中使用多种不同形状和尺寸的模具。对数据进行分析并开始根据模具的特性和预先选择的运行设置对模具进行聚类。使用聚类结果，使用 Kaplan-Meier 生存曲线对模具磨损进行建模。此外，还拟合了随机生存森林模型以进行比较并评估模型性能。案例研究的主要新颖之处在于实时实施模具磨损预测，结果以条件生存曲线的形式呈现，包括提议的早期预警系统。