AI-POWERED PREDICTIVE MAINTENANCE FOR INDUSTRIAL EQUIPMENT

Abstract

An AI-powered predictive maintenance system for industrial equipment is disclosed, featuring a network of sensors, a data processing unit, an artificial intelligence (AI) module, an alert system, and a cloud-based platform. The system continuously monitors critical operational parameters, such as vibration, temperature, and pressure, through strategically placed sensors on industrial equipment. The data processing unit aggregates and preprocesses this sensor data, which is then analyzed by an AI module comprising a machine learning model trained to detect patterns or anomalies that may indicate potential equipment failures. Based on these predictions, the alert module generates notifications to maintenance personnel, suggesting proactive maintenance actions to prevent unexpected failures and reduce downtime. The cloud-based platform aggregates data from multiple equipment units, enabling centralized monitoring, model updating, and visualization through an accessible user interface. This system optimizes maint

Specification

Description:The embodiments of the present invention generally relates to predictive maintenance systems in industrial applications, focusing on the use of artificial intelligence to monitor, analyze, and forecast the operational health of industrial equipment. By deploying sensors and AI-driven models, the invention aims to predict potential equipment failures before they occur, allowing for proactive maintenance scheduling. This results in reduced downtime, extended equipment lifespan, and optimized maintenance processes, which are critical in industrial environments where equipment reliability is paramount.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present discl , Claims:1. An AI-powered predictive maintenance system for industrial equipment, comprising:
a plurality of sensors configured to monitor operational parameters of the industrial equipment, wherein the sensors capture data indicative of equipment health, including vibration, temperature, and pressure data;
a data processing unit configured to receive, aggregate, and preprocess the captured data;
an artificial intelligence module comprising a machine learning model trained to analyze the processed data to detect patterns or anomalies indicative of potential equipment failures;
an alert module configured to generate notifications based on predictions from the artificial intelligence module, wherein the notifications indicate recommended maintenance actions to be performed; and
a cloud-based platform configured to aggregate data from multiple equipment units, store historical data, and provide a user interface to display predictive maintenance insights.

2. The system of Claim 1, wherein the machine learning model is tr

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