Predictive Analytics for Enhanced Industrial Operations: Operation Time and Task Sequence Prediction

The integration of AI technology in industrial settings has garnered significant attention due to its immense capabilities. Modern industrial companies are actively exploring the practical implementation of AI technology to enhance management decision-making processes. In this regard, a key area of focus revolves around predicting the operation time required for manufacturing specific components, taking into account various production factors. Additionally, determining the optimal task sequence for different projects and accurately predicting lead times is a critical concern for companies. The objective of this project is to address these two essential questions by leveraging existing databases and refining data collection processes within the company. The ultimate goal is to facilitate the utilization of datasets for enhancing management software in the future. By employing advanced predictive analytics, this research aims to empower industrial enterprises with actionable insights for improved operational efficiency and decision-making.