Drone Fleet Maintenance and Edge Operations Engineer
Course title: Root Cause FAILURE Analysis
Target group: Senior Employee
Level: Foundations
Root Cause FAILURE Analysis
Provider
Udemy
Description
Maintenance professionals probably spend a lot of time putting out fires: administering quick fixes to small, nuisance-type problems. All too often these problems are “solved” to “get back on stream” and the problems keep on recurring. These chronic failures can eat up to 80% of the maintenance budget. We must, therefore, move from being “maintenance repairman” to “problem analyst”. We need to identify the causes underlying the problems and do something to prevent the problems from ever happening again.
Many maintenance professionals, maintenance managers, and equipment reliability engineers do not use a systematic approach to troubleshooting and root cause analysis.
Whether you’re looking to enhance your maintenance strategies, optimize your manufacturing processes, or improve your quality management system, understanding and applying RCFA principles can be a game-changer for your organization.
RCFA has a connotation of a failure analysis on mechanical / electrical components , functional loss of components /equipment / process or function reduction of equipment/ process. Using aa structured, data-driven process RCFA helps to identify the underlying causes of problems or failures.
The goal of RCFA is to determine the root cause of an issue, rather than just addressing the immediate or obvious symptoms. RCFA is primary used to address chronic problems in industry.
RCFA utilizes various analytical techniques such as fault tree analysis, Ishikawa diagrams, Ladder Diagram, P-M Analysis and the 5 Whys method, just to mention a few, to systematically uncover the underlying reasons for the failure. It then incorporate a full blown Root Cause Analysis to identify the human and latent roots, By addressing the root cause, organizations can then implement corrective actions that prevent the problem from recurring. It is simply impossible to deal with every conceivable type of failure. This course is structured to teach failure identification and analysis methods that can be applied to virtually all problem situations that might arise. A uniform methodology of failure analysis and root cause analysis is needed to analyze a situation thoroughly to find its underlying cause.
Target
- Maintenance professionals
- maintenance managers
- equipment reliability engineers
Sector
- Manufacturing
- Industry
- industrial facilities
Area
- Maintenance optimization
- Troubleshooting
- root cause failure analysis (RCFA)
- reliability improvement
- failure analysi
Learning outcomes
- Learn the importance of Root Cause Failure Analysis (RCFA)
- Learn the difference between Failure Analysis, Root Cause Failure Analysis and Root Cause Analysis
- Learn a Toot Set for RCFA process to identify the root cause of failures
- Learn the characteristics of problems:- sporadic versus chronic problems and function loss versus function reduction.
- Gain insights of various RCFA tools and techniques for effective problem-solving – 5 WHY, Fault Tree Analysis, Ladder Diagram and P-M Analysis
- Discover how to implement a successful RCFA program and integrate it into your quality management system
- Gain insights from real-world case studies and industry best practices for RCFA
Learning content
- An Overview of the Course
- Introduction To RCFA Tool Set
- Understanding Failure Modes
- Defining the Problem
- RCFA Analysis Tools
- A Case Example
- Deploying RCA
- Identify Effective Solutions
- Decide On Solution and Implement
Approach/method
Online
Duration
3.5 hours on-demand video
Assessment
No
Certification
Yes
Cost
€44.99
Date
Always available
Location
Online
Website
Course title: Edge AI and Edge Computer vision
Target group: Mid Level Employee
Level: Foundations
Edge AI and Edge Computer vision
Provider
Udemy
Description
Mastering Edge AI and Edge Computer Vision: Unveiling the Future of Intelligent Devices
In an era where data-driven decision-making is the norm, the importance of artificial intelligence (AI) and computer vision cannot be overstated. The ability to process and interpret visual information has transformed industries, ranging from healthcare and automotive to manufacturing and agriculture. And while cloud-based AI has been pivotal in this transformation, there’s a new player in town – Edge AI and Edge Computer Vision.
In master course, we will delve into the exciting world of Edge AI and Edge Computer Vision, uncovering the key topics covered in a Master Course dedicated to these cutting-edge technologies.
Edge AI and Edge Computer Vision offer a multitude of advantages in various industries. These technologies empower real-time decision-making by processing data locally on edge devices, reducing latency and dependence on cloud connectivity. They enhance privacy and security by keeping sensitive data on-site, reducing the risk of data breaches. Edge AI enables more efficient resource utilization, as it minimizes the need for continuous high-bandwidth data transmission. In sectors like healthcare, autonomous vehicles, and manufacturing, Edge Computer Vision facilitates rapid and precise object recognition, enabling safer, more efficient operations. Moreover, these technologies enhance scalability, allowing businesses to deploy intelligent solutions across distributed environments, improving efficiency, and providing a competitive edge in today’s data-driven world.
The Master Course in Edge AI and Edge Computer Vision offers a comprehensive education in one of the most exciting and rapidly growing fields in technology. Graduates will be equipped with the skills and knowledge needed to harness the power of edge computing, create intelligent devices, and drive innovation across industries. As the world continues its digital transformation, mastering edge AI and edge computer vision is a key to staying ahead of the curve.
In this master course, I would like to teach the 6 major topics:
1. Introduction to Edge AI and Edge Computer Vision
2. Hardware for Edge Devices
3. Edge AI Fundamentals, Edge Computer Vision Basics benefits, strategy & Challenges
4. Edge AI Software Frameworks
5. Edge AI Deployment and Case Studies 6. Emerging Trends and Future Directions
Target
- Professionals and graduates in AI, computer vision, and robotics
- Engineers and developers working with IoT and embedded systems
- Healthcare technologists and medical device developers
- Automotive and autonomous vehicle engineers
- Manufacturing and industrial automation specialists
Sector
- Healthcare
- Automotive and autonomous vehicles
- Manufacturing and industrial automation
- Agriculture and agritech
- Technology and IoT development
Area
- Edge AI and Edge Computer Vision technology and applications
Learning outcomes
- Understand the principles of Edge AI and its applications in real-world scenarios.
- Gain insights into Edge Computer Vision and its role in processing data at the edge.
- Identify the essential hardware components required for efficient edge computing.
- Evaluate hardware choices to optimize performance and power consumption for edge devices.
- Comprehend the fundamental concepts of Edge AI and Edge Computer Vision.
- Analyze the benefits, strategic implications, and challenges associated with implementing Edge AI solutions.
- Explore various software frameworks used for developing Edge AI applications.
- Learn how to select and leverage appropriate software tools for efficient edge computing.
- Master the deployment process of Edge AI models in real-world scenarios.
- Examine case studies to understand successful implementations and best practices in edge AI.
- Stay updated on the latest trends and innovations in the field of Edge AI.
- Anticipate future directions and potential advancements that will shape the landscape of edge computing.
Learning content
- Master Course : Edge AI and Edge Computer vision
- Master Course : Edge AI and Edge Computer vision (101 level)
Approach/method
Online
Duration
1 hour on-demand video
Assessment
No
Certification
Yes
Cost
€19.99
Date
Always available
Location
Online
Website