Graduate Course Ongoing 2025-2026 Spring Semester

Reliability Engineering

Graduate Professional Elective | Basic concepts, mathematical models, system reliability analysis, and AI applications in reliability engineering

Course Information

Category: Professional Elective

Course Code: AM5207

Department: School of Advanced Manufacturing

Credits: 2

Hours: 36

Grade Level: First Year Graduate

Target Majors: Mechanical Engineering and Automation, Mechanical Design, Manufacturing and Automation, Mechatronics Engineering

Course Instructor: Jianshe Feng

Prerequisites: Advanced Mathematics, Probability Theory, Mechanism Principles

Course Announcements

[2025/3/3] Welcome to this course. Course resources, announcements, and grades will be published on the course management system (Click to enter) Website: cms.sysu-sam.com

Course Overview

This course aims to enable students to understand and master the basic concepts, principles, and methods of reliability engineering. Students will learn reliability mathematical models, statistical analysis, and the application of probability theory in reliability engineering; develop the ability to analyze reliability problems of complex systems and products, and learn how to design highly reliable systems and components; cultivate the ability to apply mathematical models to solve practical problems, and learn how to use reliability test data for reliability analysis, assessment, and modeling to draw reasonable and effective conclusions.

Learning Objectives

Understand and master the basic concepts, principles, and methods of reliability engineering; learn reliability mathematical models, statistical analysis, and the application of probability theory in reliability engineering

Develop the ability to analyze reliability problems of complex systems and products; master how to design highly reliable systems and components

Cultivate the ability to apply mathematical models to solve practical problems; learn to use reliability test data for reliability analysis, assessment, and modeling to draw reasonable and effective conclusions

Course Topics

1 Introduction: Discipline background, development history, and engineering applications of reliability

2 Mathematical Foundations of Reliability: Probability theory, statistical analysis, common probability distributions

3 System Reliability Models and Applications: Series, parallel, hybrid, voting, and standby system models; reliability parameter estimation

4 Fault Tree Analysis and Failure Mode, Effects, and Criticality Analysis (FMECA)

5 Repairable Systems and Software Reliability: Maintainability and availability analysis

6 Human-Machine System Reliability: Reliability indices and design methods

7 System Reliability and Artificial Intelligence: Intelligent reliability assessment models and applications

Assessment

Regular Score (class discussion, attendance)

Final Assessment

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