Pemanfaatan Teknologi Big Data pada Crane Health Management System (CHMS) dengan Pendekatan Integrative Framework

Abstract

Ports around the world play a vital role in supporting the global economy. Since 1990, the volume of international container trade has increased by about 10% annually, adding to the pressure on port operations. Ship-to-shore cranes (STS) are a crucial element in this operation, so maintenance and prediction of their health are essential to avoid unexpected damage and disruptions. This study explores using Big Data technology in the Crane Health Management System (CHMS) with an integrative framework approach. Through the analysis of diverse operational data, predictive models can be developed to improve maintenance efficiency, reduce downtime, and improve the productivity and reliability of port operations. The application of this technology is expected to provide more comprehensive solutions, support better decision-making, and contribute to more efficient and reliable port operations.