부산대학교 도서관

Intelligent systems and applications on manufacturing domain aim to improve decision-making capabilities, ease complex decision problems, offer predictions related to maintenance activities and provide cost savings to companies. In order to support the aforementioned functionalities, the intelligent prediction and decision support systems are based on machine learning and signal processing techniques, AI algorithms, IoT devices, data mining and modeling techniques, rules and fuzzy logic systems, and advance visualizations. In this paper, we introduce an intelligent information management system that aims to provide predictive maintenance and enhance decision support in a leading lift manufacturer. The proposed solution is a decision support system equipped with analytic tools, IoT sensors and visualizations. The system supports the full cycle of polishing procedures of the lift manufacturer, as it starts from predictive maintenance during the polishing machines' operation and ends in the scrap metals' removal after the operation. Both the intelligent information system and the scenario of its usage in the lift manufacturer's shop floor are presented in this work.