EdX

Reliability in Engineering Design (edX)

Offered by Purdue University, PurdueX,
Reliability in Engineering Design (edX)

Learn the methods of reliability analysis and reliability-driven design of mechanical and electronic systems. The course is aimed at providing an engineering view (as opposed to a purely statistical view or a management view) of reliability analysis as well as reliable product design.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

The goal is to make the student familiar with both the statistical tools as well as the failure physics that enable one to model time to failure of products and to use such models during design phase to ensure reliable product designs.

This course is part of the Reliability and Decision Making in Engineering Design MicroMasters Program

What you'll learn

  • Probability rules and conditional probabilities
  • Expectation and variance of continuous functions and their manipulation
  • Failure rate modeling
  • Normal, lognormal, exponential, Weibull, binomial and Poisson distributions
  • Reliability, mean time to failure and availability
  • Data fitting and reliability estimation
  • Multimodal distributions and mixed multiple failure mechanisms
  • Reliability block diagrams
  • Monte Carlo simulation
  • Load-strength interference and probabilistic design
  • First-order reliability methods
  • Accelerated tests and acceleration factors
  • Time to failure modeling for selected failure mechanisms in mechanical and electronic systems

Syllabus

Week 1:
Introduction and Overview
Rules of Probability

Week 2:
Probability Examples
Conditional Probability

Week 3:
Expectations and Variance Definition
Expectation and Variance of Continuous Functions
Normal Distribution PDF and CDF

Week 4:
Load-Strength Interference Theory
Load-Strength Interference Examples

Week 5:
Material Degradation and Time to Failure Modeling
Practice Problems for Test 1

Week 6:
Lognormal Distribution, Reliability, Hazard Rate and MTTF
Test 1

Week 7:
Exponential Distribution and Examples of MTTF Estimation
Weibull Distribution

Week 8:
Multimodal Distributions and Mixed Multiple Failure Mechanisms
Goodness of Fit

Week 9:
Binomial and Poisson Distributions
Practice Problems for Test 2

Week 10:
Reliability Block Diagrams
Test 2

Week 11:
Monte Carlo Simulation
Uncertainty in Geometry, Load and Strength
Covariance and Correlation

Week 12:
-Covariance and Correlation Examples
First Order Reliability Methods Introduction

Week 13:

  • First Order Reliability Methods Examples
  • Reliability Review During Design

Week 14:

  • Accelerated Degradation
  • Accelerated Testing and Acceleration Factors
  • Practice Problems for Test 3

Week 15:

  • Time to Failure Models for Mechanical Systems
  • Test 3
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Engineering Drawing | 工程制图 (edX) EdX
Tsinghua University,TsinghuaX

Engineering Drawing | 工程制图 (edX)

“Engineering Drawing” is a fundamental course of engineering technology, including two parts: basic theories and advanced practices. The first part will introduce the theory of projection and its application on drawings. The second part is to give students general experience in producing a variety of mechanical drawings.

Self Paced
Self-Paced
A System View of Communications: From Signals to Packets (Part 2) (edX) EdX
The Hong Kong University of Science and Technology - HKUST,HKUSTx

A System View of Communications: From Signals to Packets (Part 2) (edX)

Explore the tradeoffs in designing communication systems like mobile phones, and the engineering tools to handle them. Have you ever wondered how information is transmitted using your mobile phone or a WiFi hotspot? This introductory course seeks to enable you to understand the basic engineering tools used and tradeoffs encountered in the design of these communication systems.

Self Paced
Self-Paced
Engineering Design for a Circular Economy (edX) EdX
Delft University of Technology,DelftX

Engineering Design for a Circular Economy (edX)

Discover and develop sustainable design and engineering methods to improve the reuse, repair, remanufacturing, and recycling of products for a circular economy. Products and equipment all around us are made of materials: look around you and you will see phones, computers, cars, and buildings. We face challenges in securing the supply of materials and the impact this has on the planet. Innovative product design can help us find solutions to these challenges. This course will explore new ways of designing products.

Self Paced
Self-Paced
Fundamentos de Mecánica para Ingeniería (edX) EdX
Universitat Politècnica de València,UPValenciaX

Fundamentos de Mecánica para Ingeniería (edX)

Estudiaremos la cinemática y la dinámica del punto, los conceptos de trabajo y potencia y la energía mecánica. Se aborda el estudio del universo físico analizando objetos en movimiento. Se definen y analizan todas las magnitudes y leyes físicas que permiten describir geométrica y causalmente el movimiento de cuerpos representados por un punto.

Self Paced
Self-Paced
水力学 | Hydraulics (edX) EdX
Tsinghua University,TsinghuaX

水力学 | Hydraulics (edX)

This Hydraulics course explores the science of hydraulics and focuses on hydrodynamic laws and their applications, which are indispensable and a critical factor in the development and utilization of water resources. 水,是人类生活不可或缺的资源。水力学是人类开发利用水资源的有力工具。本课教你认识和掌握水流静止和运动的力学规律,了解在相关领域的工程应用。

Self Paced
Self-Paced
A System View of Communications: From Signals to Packets (Part 1) (edX) EdX
The Hong Kong University of Science and Technology - HKUST,HKUSTx

A System View of Communications: From Signals to Packets (Part 1) (edX)

Explore the tradeoffs in designing communication systems like mobile phones, and the engineering tools to handle them. Have you ever wondered how information is transmitted using your mobile phone or a WiFi hotspot? This introductory course seeks to enable you to understand the basic engineering tools used and tradeoffs encountered in the design of these systems.

Self Paced
Self-Paced
A Hands-on Introduction to Engineering Simulations (edX) EdX
CornellX,Cornell University

A Hands-on Introduction to Engineering Simulations (edX)

Learn how to analyze real-world engineering problems using ANSYS simulation software and gain important professional skills sought by employers. In this hands-on course, you’ll learn how to perform engineering simulations using a powerful tool from ANSYS, Inc. This is a problem-based course where you’ll learn by doing. The focus will be on understanding what’s under the blackbox so as to move beyond garbage-in, garbage-out. You’ll practice using a common solution approach to problems involving different physics: structural mechanics, fluid dynamics and heat transfer.

Self Paced
Self-Paced
MathTrackX: Probability (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Probability (edX)

Understand probability and how it manifests in the world around us. This course introduces probability and how it manifests in the world around us. Beginning with discrete random variables, together with their uses in modelling random processes involving chance and variation, you will start to uncover the framework for statistical inference.

Self Paced
Self-Paced
Probability and Statistics I: A Gentle Introduction to Probability (edX) EdX
Georgia Institute of Technology,GTx

Probability and Statistics I: A Gentle Introduction to Probability (edX)

This course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of real-world problems. In order to make the course completely self-contained (and to bring back long-lost memories), we’ll start off with Bootcamp lessons to review concepts from set theory and calculus.

Self Paced
Self-Paced
Statistics Using Python (edX) EdX
University of Wisconsin–Madison,WisconsinX

Statistics Using Python (edX)

Learn the fundamentals of statistics using Python. This course is a compact primer in statistics as a foundation for data-driven business analysis. A selection of concepts include descriptive statistics, probability, inference, correlation, and regression. The course also exposes students to basic Python programming for use in statistics.

Sep 2nd 2026
5-12 Weeks
Probability and Statistics in Data Science using Python (edX) EdX
University of California, San Diego,UC San DiegoX

Probability and Statistics in Data Science using Python (edX)

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

Self Paced
Self-Paced
Decision-Making for Autonomous Systems (edX) EdX
Chalmers University of Technology,ChalmersX

Decision-Making for Autonomous Systems (edX)

Learn effective tactics for making key decisions when working with autonomous, self-driving vehicles. In autonomous vehicles such as self-driving cars, we find a number of interesting and challenging decision-making problems. Starting from the autonomous driving of a single vehicle, to the coordination among multiple vehicles. This course will teach you the fundamental mathematical model for many of these real-world problems.

Self Paced
Self-Paced