Home / Chemical engineering / Development of Advanced Process Monitoring Techniques Using Artificial Intelligence

Development of Advanced Process Monitoring Techniques Using Artificial Intelligence

 

Table Of Contents


<p>1. Introduction<br>&nbsp; 1.1 Background and motivation<br>&nbsp; 1.2 Objectives of the project<br>2. Literature Review<br>&nbsp; 2.1 Overview of process monitoring techniques<br>&nbsp; 2.2 Role of artificial intelligence in process monitoring<br>3. Data Acquisition and Preprocessing<br>&nbsp; 3.1 Selection of process variables and sensors<br>&nbsp; 3.2 Data preprocessing and feature extraction<br>4. Development of AI-Based Monitoring Models<br>&nbsp; 4.1 Selection of machine learning algorithms<br>&nbsp; 4.2 Training and validation of monitoring models<br>5. Real-Time Implementation and Validation<br>&nbsp; 5.1 Integration of AI-based monitoring systems in industrial processes<br>&nbsp; 5.2 Validation and performance assessment<br></p>

Project Abstract

This project focuses on the development of advanced process monitoring techniques using artificial intelligence (AI) for chemical engineering applications. The project aims to explore the use of machine learning algorithms and AI-based models for real-time monitoring of chemical processes, with a focus on early fault detection, process optimization, and improved safety. The project will involve the development and validation of AI-based monitoring systems using process data from industrial case studies.


Project Overview

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