Jan 30,2024

009 - Applying AI Powered Root Cause Analysis in Engineering

 

Applying AI Powered Root Cause Analysis in Engineering

 

Course Number: 009

 

Fee: Free

 

Length: 2 Hours

 

Credits: This course qualifies for 2 PDH (unstructured) and 2 CEU (structured) technical learning credits issued by most US State Engineering Regulatory Organizations and all Canadian Provincial and Territorial Engineering Regulatory Organizations.

 

Online, Self-Directed Format: Primarily Text with Illustrations and Video

 

Coming soon a short video synopsis of this course…

 

Course Description (Syllabus):

 

The use of Artificial Intelligence in Root Cause Analysis will eventually become an integral part of every engineer’s tool kit.

 

AI can significantly automate and enhance the RCA process in several ways:

 

1. Data Analysis: AI can quickly analyze large amounts of data from various sources to identify patterns and trends that may indicate the root cause of a problem.

 

2. Predictive Analysis: AI can use historical data to predict potential problems and their root causes before they occur, allowing for proactive problem-solving.

 

3. Machine Learning: AI can use machine learning algorithms to identify patterns and relationships in data that may indicate the root cause of a problem. This can help to automate the RCA process and reduce the time and effort required to identify the root cause.

 

4. Visualization: AI can create visualizations of data to help identify patterns and relationships that may indicate the root cause of a problem. This can make it easier for humans to understand and interpret the data.

 

Overall, AI can help to make the RCA process more efficient, accurate, and effective, allowing engineers to quickly identify and address the root causes of problems, and prevent them from happening again.

 

In this course we will discuss how to apply AI in RCA, software and processes required and the application of AI enhanced RCA in various fields of engineering.

 

Learning Outcomes: By completing this course you will learn:

 

1. Fundamental principles of Root Cause Analysis, 
2. Application of AI in Root Cause Analysis: Benefits, Processes, Specialized Tools and Datasets, AI Model Training Frameworks
3. The Application of AI in RCA in Different Fields of Engineering: Mechanical, Electrical, Civil, Chemical and Biomedical
4. Real Word Applications of AI in RCA, Case Studies
5. Challenges of AI Powered RCA
6. The Future of AI in RCA

 

Who Should Take This Course:

 

Engineer students and all engineers who, in their profession, are responsible for identifying and resolving system and structural failures.

 

Course Instructions:

 

Enrollment: You must be registered and logged into the Engineer eLearning Centre website to access this course.

 

Once you are logged into your Engineer eLearning account click “Browse Courses” to find this course. Click Enroll and confirm you wish to enroll.

 

Once you have confirmed your enrollment you will be returned to your account “My Courses”. Click Enter Course in course profile box. You can enter the course at any time and as many times as you wish. There is no time limit as to when you must complete this course. To access the course learning content click the module headings in the side menu.

 

Credit Options:

 

 

After completing this course you have the option of receiving eMETA PDH or CEU credit(s) or both. eMETA credits qualify for Unstructured and Structured technical learning credits required by most US State and all Canadian Provincial and Territorial Engineering Regulatory Organizations.

 

To receive your eMETA CEU credit you will be required to take an automated quiz.

 

Instructions on how to receive your credit(s) and download your PDF Certificate(s) are provided in the side menu of this course. Your credits will also be registered in your Engineer eLearning Centre account. You can download a Transcript of all credits earned in the Engineer eLearning Centre by clicking the Transcript tab in your account.

 

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