AI-Powered Failure Modes and Effects Analysis (FMEA)

Master practical FMEA using modern tools like ChatGPT to improve accuracy, efficiency, and team collaboration.

What you'll learn
- Understand the fundamentals of FMEA theory, types, and terminology for design and process applications.
- Learn the complete step-by-step FMEA process with clear guidance from scope to action plan.
- Use Generative AI (ChatGPT) to accelerate brainstorming, scoring, and documentation of FMEA.
- Use provided FMEA template to practice and apply concepts immediately to your work.
- Apply both traditional RPN and the AIAG-VDA Action Priority method for risk ranking.
- Gain hands-on experience with a customized GPT for faster, collaborative FMEA creation.

Requirements
- No prior FMEA experience required; course is beginner-friendly.
- Access to ChatGPT or another AI tool for the AI-assisted exercises.

Description
This course provides a comprehensive and practical approach to masteringFailure Modes and Effects Analysis (FMEA), combining foundational theory with modern practices, including theAIAG-VDA Action Priority (AP)and optional AI support. It is designed to help engineers, quality professionals, and team leaders confidently conduct bothDesign FMEAs (DFMEA)andProcess FMEAs (PFMEA), regardless of prior experience.

FMEA is a cornerstone of quality and risk management across industries, but many professionals struggle to implement it effectively in day-to-day work. This course bridges the gap between theory and practice through a detailed, real-world case study of acordless electric glass kettle. You will learn how to define system boundaries, identify failure modes and causes, assess risk, and develop meaningful action plans.

Bothtraditional RPN-based methodsand themodern Action Priority (AP)approach from the AIAG-VDA handbook are merged to provide a simple and practical approach.

The course is designed to be effective with or without AI assistance. For those looking to enhance their workflow, acustom GPT-based assistantis provided to support brainstorming, clarify terminology, generate potential failure modes, and accelerate documentation. A downloadable template is included to reinforce learning and guide implementation.

What You Will Learn

Complete FMEA methodology and terminology, including severity, occurrence, detection, and risk prioritization.

How to conduct DFMEA and PFMEA.

How to use both RPN scoring and AIAG-VDA Action Priority (AP) ratings for more effective risk ranking.

Techniques for defining functions, identifying failure modes, causes, and effects, and linking them to appropriate controls.

How to facilitate cross-functional FMEA sessions and maintain the analysis as a living document.

How to leverage AI tools like ChatGPT to streamline analysis, brainstorming, and documentation.

Industry Applications

FMEA is widely used in automotive, aerospace, electronics, healthcare, manufacturing, construction, and software development. The methods taught in this course can be applied to bothproductsandprocessesin any industry where reliability, compliance, and safety are critical.

Who Should Enroll

Quality managers, quality engineers, design engineers, process engineers, Six Sigma practitioners, reliability professionals, and team leaders. It is also ideal for anyone who has learned FMEA in theory but has not successfully applied it in practice.

By the end of the course, you will be able to complete an FMEA independently or with your team,  and optionally supported by AI tools. You will have the skills to improve compliance, reduce risk, and implement FMEA effectively in your own work environment.

Who this course is for:
- Quality Managers seeking to strengthen risk management processes.
- Quality Engineers responsible for product or process reliability.
- Design Engineers involved in developing new products or improving existing designs.
- Process Engineers working on manufacturing process optimization.
- Six Sigma Practitioners aiming to integrate FMEA into DMAIC projects.
- Project Managers overseeing cross-functional product or process development.
- Reliability Engineers focusing on failure prevention and system performance.
- Operations Managers seeking proactive quality improvement strategies.
- Professionals from automotive, aerospace, manufacturing, healthcare, electronics, and other industries where risk analysis is critical.
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