Plant Information Management System Using OSIsoft PI System: A Case Study of Cilacap Power Plant Units 1 and 2
In the dynamic industrial sector, the ability to combine and manage data from various sources is essential. This study focuses on the utilization of the PI System to integrate operational data from multiple data sources at power plants, facilitating data driven decision making and enhancing operatio...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Center for Research and Community Service, Institut Informatika Indonesia Surabaya
2024-02-01
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| Series: | Teknika |
| Subjects: | |
| Online Access: | https://ejournal.ikado.ac.id/index.php/teknika/article/view/752 |
| Summary: | In the dynamic industrial sector, the ability to combine and manage data from various sources is essential. This study focuses on the utilization of the PI System to integrate operational data from multiple data sources at power plants, facilitating data driven decision making and enhancing operational efficiency. The application of the PI System in collecting data from Distributed Control Systems (DCS) and asset management systems like Maximo is examined, as well as its potential for integrating data from other power plant units. The study utilizes systems analysis methods to understand the potential of data integration in improving operational visibility and control. Findings from testing reveal that effective data integration can extend monitoring and management capabilities, indicating an overall improvement in operational performance. This study contributes to the literature on industrial data management by demonstrating the effective use of the PI System as a comprehensive tool for integrating data from various systems within power plants. It showcases the system's adaptability in enhancing operational decision-making and providing a cohesive platform for real-time performance monitoring. Additionally, the research offers insights into the practical application of systems analysis methods in the context of power plant operations, contributing to the ongoing discourse on digital transformation in the energy sector. |
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| ISSN: | 2549-8037 2549-8045 |