USE OF THE LAPLACE TRANSFORM IN THE PREVENTIVE MAINTENANCE OF HOSPITAL EQUIPMENT

Abstract

This article investigates the application of the Laplace Transform in the preventive maintenance of medical equipment, focusing on failure prediction and the optimization of maintenance processes. The research was conducted in a hospital environment, involving four types of devices: cardiac monitors, mechanical ventilators, infusion pumps, and ultrasound equipment. The results indicate that the use of the Laplace Transform resulted in a significant reduction in the rate of unpredicted failures, which decreased from 15% to 5%, as well as a reduction in the average downtime of the equipment.The adopted methodology included the mathematical modeling of failure rates, allowing for the calculation of the Mean Time to Failure (MTTF) for each type of equipment. Additionally, the study provides an innovative contribution by offering valuable insights for hospital and healthcare center managers, facilitating decisions regarding preventive interventions. The article also suggests directions for future research, including the exploration of other transforms and advanced forecasting techniques, such as machine learning, to enhance predictive models and develop automated systems with alerts based on predictions. In summary, the application of the Laplace Transform in preventive maintenance represents a significant advancement in the management of hospital resources, promoting improvements in operational efficiency.