Course description
In Finding the Root Cause, you'll learn ...
- Learn the natural pitfalls which lead to divergent problem solving investigations
- Learn how to conduct a convergent investigation
- Learn how to design simple statistical experiments that work on small sample sizes
- Be able to solve problems in engineering systems more reliably and efficiently
Overview
To meet the Ohio Board's intent that online courses be "paced" by the provider, a timer will be used to record your study time. You will be unable to access the quiz until the required study time of 300 minutes has been met.
Credit: 6 PDH
Length: 56 pages
Whether in electrical, industrial, or mechanical systems, problems always seem to pop up at the worst time. Engineers are often seen as resorting to "shot-gun" methods to find solutions. When faced with a problem, the engineer must resist the natural tendency to reinvent the system based on speculation about the cause of the problem. When the engineer "thinks like an inventor", he/she loses the chance to learn what really went wrong. Secondly, thinking like an inventor often leads to a diverging problem-solving investigation. That is, the investigation keeps growing bigger and bigger.
In this course, you will learn to "think like a detective", which involves avoiding theories, preserving the existing system (and data) and finding evidence to narrow down the list of possible causes. This Converging Process of Elimination will help you to identify the Root Cause of the problem.
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Upcoming start dates
Who should attend?
Certificate of Completion
You will be able to immediately print a certificate of completion after passing a multiple-choice quiz consisting of 30 questions. PDH credits are not awarded until the course is completed and quiz is passed.
Training content
This course teaches the following specific knowledge and skills:
- Learn the natural pitfalls which lead to divergent problem solving investigations
- Learn how to conduct a convergent investigation
- Learn how to design simple statistical experiments that work on small sample sizes
- Be able to solve problems in engineering systems more reliably and efficiently
Costs
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