Work

Design and Optimization of Smart Biomedical Equipment Maintenance Systems Using Predictive Analytics

Year: 2026

Type: article

Abstract: Efficient maintenance of biomedical equipment is critical for ensuring patient safety, device reliability, and cost-effective healthcare delivery. Conventional maintenance methods, such as preventive and corrective maintenance, sometimes fail to anticipate unforeseen breakdowns. In order to include predictive analytics into biomedical equipment management systems, this study suggests a smart maintenance framework. The system may anticipate possible faults before they happen by using sensor data, past maintenance records, and machine learning algorithms. System architecture, data processing methods, and implementation difficulties in hospital settings are all included in the study. The suggested strategy lowers operating expenses, increases equipment uptime, and raises the standard of healthcare services.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22157631

Author: *Eng. Aktham Ali Al-Omar, Eng. Mohamed Fowzi Ababeneh, Eng. Fadi Tawfiq Asasfeh, Eng. Waseem Bakheet Al-hawari

Language: English

Topic: Quality and Safety in Healthcare

Subfield: Medical Laboratory Technology

Field: Health Professions

Domain: Health Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7204632802

FWCI:

Cites:

Cited by:

Related to: