Santo Wijaya, Nita Winda Sari, Dwiky Firnanda Dewa

Pengembangan Sistem Kontrol Redundancy Chiller MRI berbasis Internet-of-Things

Introduction

Pengembangan sistem kontrol redundancy chiller mri berbasis internet-of-things. Kembangkan sistem kontrol otomatis chiller MRI berbasis IoT & PLC. Tingkatkan keandalan dan efisiensi pendingin MRI dengan pemantauan real-time via HMI. Teruji valid.

Abstract

Rumah sakit modern memanfaatkan teknologi seperti Magnetic Resonance Imaging (MRI) untuk diagnosis medis, namun masih ditemukan kendala pada sistem pendinginan magnet superkonduktor akibat kontrol chiller yang manual dan terbatas. Masalah ini menyebabkan keterlambatan, informasi tidak tersampaikan dengan baik, serta berisiko merusak perangkat MRI. Penelitian ini mengembangkan sistem kontrol otomatis berbasis Programmable Logic Controller (PLC) yang dilengkapi dengan Virtual Human Machine Interface (HMI) dan Mobile HMI untuk pemantauan real-time yang efisien dan mudah digunakan. Hasil pengujian dengan metode Black-box dan White-box menunjukkan validasi 100%, sementara survei kepuasan pengguna mencatat tingkat kepuasan sebesar 96,36%. Sistem ini juga bersifat plug and play, sehingga dapat diterapkan pada unit MRI lain dengan penyesuaian minimal. Solusi ini terbukti efektif dalam meningkatkan keandalan dan efisiensi sistem pendingin MRI.

Review

The article "Pengembangan Sistem Kontrol Redundancy Chiller MRI berbasis Internet-of-Things" addresses a critical operational challenge within modern healthcare facilities: the manual and often problematic control of chiller systems essential for superconducting MRI magnets. The authors clearly articulate the issues arising from current limitations, including diagnostic delays, poor information dissemination, and the significant risk of damage to expensive MRI equipment. By proposing an automated, IoT-enabled control system utilizing a Programmable Logic Controller (PLC) combined with Virtual and Mobile Human Machine Interfaces (HMI), the research aims to provide an efficient and user-friendly solution for real-time monitoring and enhanced system reliability. The methodology employed in developing and validating this system appears comprehensive and robust. The integration of PLC for automated control with both Virtual and Mobile HMI for accessible real-time monitoring is a well-conceived approach to address the identified problems. The rigorous validation process, incorporating both Black-box and White-box testing methods, yielded a perfect 100% validation, which speaks to the system's functional integrity and reliability. Furthermore, the practical applicability and user-friendliness are underscored by an impressive 96.36% user satisfaction rate. The "plug and play" characteristic, allowing for minimal adjustments when applied to other MRI units, highlights the system's excellent scalability and ease of implementation. Overall, this research presents a highly effective and practical solution with significant implications for the reliability and efficiency of medical imaging departments. The high validation percentages and strong user satisfaction ratings strongly affirm the system's capability to improve the uptime and operational safety of critical MRI equipment. By automating a previously manual and error-prone process, this IoT-based control system offers a substantial advancement in healthcare technology management, ultimately contributing to more consistent diagnostic services and improved patient care. The work represents a valuable contribution to enhancing the resilience of modern hospital infrastructure.

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