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 āsolvedā to āget back on streamā and the problems keep on recurring. These chronic failures can eat up to 80% of the maintenance budget. We must, therefore, move from being āmaintenance repairmanā to āproblem analystā. 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 youāre 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 ā 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
Date
Always available
Location
Online
Website
Course title: Lithium-Ion Batteries: Basics to Advanced Technology Course
Target group: Junior (Fresh Employee)
Level: Awareness
Lithium-Ion Batteries: Basics to Advanced Technology Course
Provider
Udemy
Description
This course of lithium ion batteries will help you to discover useful knowledge and facts about the batteries that you really need as a learner. In this class, reason of the batteries getting fired will be discussed in detail and methods to overcome this problem. Types of the batteries used in electronics and electric vehicles depending upon their materials and assembly will be analyzed in detail. When batteries will be strong enough for electric vehicles to be suitable for mass adaption and what are the hurdles there to be removed. If you are interested to learn about the operation of the batteries, this course will also give you a simple but comprehensive overview of how batteries work.
At the end of this class you will be able to:
You will be aware of the basic principles of how batteries work.
Be capable to understand vital concepts in batteries such as current, voltage, capacity, efficiency, anode, cathode, electrolyte and many more.
Description about different types of batteries and how these are different based on different applications.
Understand what lithium ion batteries are and how these are different based on their assembly.
Which batteries materials are used by electric vehicle manufacturers.
Know some essentials and resources to expand your knowledge on batteries.
Future of the batteries for electronics and electric vehicles. The class is composed of video lectures where I give explanation about interesting facts of the battery technologies. This course is arranged and designed in such a way that with each upcoming section you go deeper and deeper into comprehensive knowledge. This course is fairly suitable for the students who are new to the battery world. If you are already advanced in the battery knowledge then you can skip some of the early lectures and go into more advanced sections of the course. Therefore, join the class and advance your knowledge on the battery technology that powers the world. No prior knowledge necessary for this course.
Target
- Who are keen to grow up their profession in the field of lithium ion batteries
- Researcher, scientists and engineers that want to know essentials about the batteries
- Everybody with a desire to study
- People with a general background in science or engineering
- Students that are curious about how their phones, devices and electric vehicles are being powered
- Students who are willing to learn about the details of lithium ion batteries
Sector
- Electronics
- Electric Vehicles
- Renewable Energy
- Energy Storage
Area
- Lithium-ion battery technology
- Battery operation principles
- Battery safety
- Battery materials and assembly
- Future trends in batteries
Learning outcomes
- Complete overview about lithium ion batteries
- How lithium ion batteries work
- Know the history of batteries
- Major parts of the batteries
- Details about lithium ion batteries
- Chemistry of lithium ion batteries
- Different type of electric vehicle batteries
- Technical aspects
- Reasons of batteries getting fired and their solutions
- Assembly of lithium ion battery
- Applications of lithium ion batteries
- Types of batteries used in electronics and electric vehicles
- Battery materials used in high performance electric vehicles
- The evolution of the batteries
Learning content
- Course introduction
- Background
- Lithium demand and resources
- Lithium mining and extraction
- Introduction to lithium ion batteries
- Lithium ion battery manufacturing
- Types of lithium ion batteries
- Technical aspects of the batteries
- Major components of the batteries
- Assembly of the batteries
Approach/method
Online
Duration
7 hours on-demand video
Assessment
Yes
Certification
Yes
Date
Always available
Location
Online
Website
Course title: GNSS GPS IMU INS Sensors – for ADAS and Autonomous Vehicles
Target group: Mid Level Employee
Level: Foundations
GNSS GPS IMU INS Sensors – for ADAS and Autonomous Vehicles
Provider
Udemy
Description
GNSS (Global Navigation Satellite System), and GPS (Global Position System) with INS (Inertial Navigation System) are highly used in ADAS and Autonomous driving development. Hence, it is necessary and very useful, to know the foundation of this group of sensors and related technologies, if you are working or aiming to work in this industry.
What will you learn after completing this course (with 10 hours of video lectures)?
- Deeply understanding GNSS technology including signal processing, pseudo-range calculation, trilateration, GNSS errors, different ways to overcome these errors, various types of coordinate systems used in GNSS technology, latitude and longitude, different ways to represent them and their inter-conversions, NMEA-0183 message structures for GPS measurement (used by many sensors), and how to decode them.
- Understand each correction method – DGNSS, DGPS, SBAS, GBAS, RTK, and PPP that increases the accuracy of GNSS measurement from a few metres to a few centimetres. (Almost all the industrial GNSS sensors use one or more of these technologies to improve their accuracy). Especially nowadays RTKĀ (Real Time Kinematic) is very popular.
- Deeply understand IMU (Inertial Measurement Unit), and the working of accelerometer, gyroscope and magnetometer sensors that make INS (Inertial Navigation System) – an indispensable part of a high-quality GNSS device used for ADAS and AD development.
- Deep dive into AHRS (Attitude and Heading reference system), GNSS-aided INS technology and Dual GNSS-aided INS technology along with some case studies (taken from research papers)
Hands-on with low-cost GPS and IMU sensor together with Raspberry Pi 4 using Python-based programming. Here you will learn to read GPS location and IMU data in real time.
Target
- Engineers and professionals in ADAS and autonomous driving development
- Robotics and navigation system developers
- Students and researchers in GNSS, INS, and sensor technologies
- Embedded systems and IoT developers working with GPS/IMU sensors
Sector
- Automotive (ADAS & Autonomous Vehicles)
- Aerospace and Defense (navigation systems)
- Robotics and Industrial Automation
- Research & Development in navigation and sensor fusion technologies
Area
- GNSS/GPS technology and applications
- Inertial Navigation Systems (INS) and sensor fusion
- Advanced Driver Assistance Systems (ADAS)
- Real-time data acquisition and processing using Python and embedded systems
Learning outcomes
- You will learn GNSS (Global Navigation Satellite System) and GPS in detail including all the necessary concepts required to understand it.
- You will learn various GNSS based correction methods like DGNSS, DGPS, SBAS, GBAS, RTK, PPP in detail that are used widely in ADAS and AD development
- You get deep understanding of accelerometer, gyroscope and magnetometer sensors that forms INS (Inertial Navigation System)
- You will learn about GNSS + INS fused sensor, and dual GNSS + INS fused sensor – very common sensor use in ADAS and AD development
- You will get hands on with low cost GPS sensor, and IMU sensor using raspberry pi 4 and python to read real-time data
Learning content
- Introduction
- Why GNSS GPS IMU INS RTK in ADAS and Autonomous Driving?
- GNSS (Global Navigation Satellite Systems)
- GNSS – Differential correction based systems
- IMU (Inertial Measurement Unit)
- INS + GNSS, AHRS
- Wrap Up
Approach/method
Online
Duration
10 hours on-demand video
Assessment
No
Certification
Yes
Date
Always available
Location
Online
Website
Course title: UAS / Drone Preventative Maintenance
Target group: Junior (Fresh Employee)
Level: Awareness
UAS / Drone Preventative Maintenance
Provider
opensesame.com
Description
This course is designed to assist Drone Pilots and Operators in the development and implementation of an effective Drone Preventative Maintenance Program, and to how to carry out such preventative maintenance. The program also aims to ensure Drone Pilots understand the benefits and safety implications of a Preventative Maintenance schedule.
Target
- Drone pilots and operators
Sector
- Aviation / Unmanned Aerial Systems (UAS)
Area
- Drone preventative maintenance and safety procedures
Learning outcomes
- Implement a drone repetitive maintenance program
- Ā Identify the components and systems that require preventative maintenance
- Ā Describe the financial and safety benefits of a UAV (Drone) preventative maintenance program
Learning content
- Module 1: Introduction to Drone Preventative Maintenance
- Module 2: Roles and Responsibilities of Drone Pilots and Operators
- Module 3: Components and Systems Requiring Preventative Maintenance
- Module 4: Developing and Implementing a Preventative Maintenance Program
- Module 5: Safety Procedures and Best Practices
- Module 6: Financial and Operational Benefits
- Module 7: Practical Application and Case Studies
Approach/method
Online
Duration
4Ā hours
Assessment
No
Certification
No
Date
Always available
Location
Online
Website
Course title: Condition Monitoring and Maintenance Management
Target group: Mid Level Employee
Level: Foundations
Condition Monitoring and Maintenance Management
Provider
classcentral
Description
This course āCondition Monitoring and Maintenance Managementā comprises of three modules and ten chapters will be covered in eight weeks.The Module 1: Maintenance Concepts, deals with functions and objectives of maintenance, maintenance strategies, maintenance scheduling and organization and spare parts management and also deals with various methods and policies of maintenance engineering.Module 2: Condition Based Maintenance, describes the methods of fault diagnosis, condition checking and inspection and trend monitoring methods. This module also explains various methods of machine fault identification and its diagnosis.Module 3: Reliability Centered Maintenance, discusses about maintenance division models, reliability oriented maintenance systems, Total Productive Maintenance (TPM) and Benchmarking. Finally it concludes with procedures of JIT maintenance, zero defect maintenance and zero breakdown maintenance systems
Target
- Maintenance engineers
- Reliability engineers
- Plant managers
- Mechanical and electrical technicians
- Maintenance supervisors
Sector
- Manufacturing and factories
- Power and energy
- Automotive
- Oil and gas
- Heavy machinery
Area
- Maintenance management
- Condition monitoring
- Reliability engineering
- Preventive and predictive maintenance
- Total Productive Maintenance (TPM)
Learning content
- Unit 1: Functions and Objectives of Maintenance
- Unit 2: Maintenance Strategies
- Unit 3: Maintenance Schedules
- Unit 4: Spare Parts Management
- Unit 5: Diagnostic Maintenance
- Unit 6: Condition Monitoring
- Unit 7: Trend Analysis
- Unit 8: Maintenance Models
- Unit 9: Reliability Oriented Maintenance Models
- Unit 10: TPM and Japanese Concepts: Kaizen
Approach/method
Online
Duration
8 weeks
Assessment
No
Certification
Yes
Date
Always available
Location
Online
Website
Course title: Edge Computing and AI Integration in Real-Time Systems Training
Target group: Mid Level Employee
Level: Foundations
Edge Computing and AI Integration in Real-Time Systems Training
Provider
tonex
Description
Edge computing and AI integration are transforming real-time systems across industries. This training provides a comprehensive understanding of edge computing frameworks, AI-driven decision-making, and real-time data processing. Participants will explore architecture, deployment strategies, and optimization techniques. The course covers security challenges, latency reduction, and AI-enhanced automation. Real-world case studies illustrate best practices and emerging trends. Attendees will gain the skills needed to design, implement, and manage AI-driven edge computing solutions effectively.
Target
- IT professionals
- System architects
- AI engineers
- Network administrators
- Data scientists
- Industry consultants
Sector
- Information Technology
- Telecommunications
- Industrial Automation
- Smart Manufacturing
Area
- Edge Computing
- Artificial Intelligence
- Real-Time Systems
- IoT Integration
- Automation
Learning outcomes
- Understand edge computing fundamentals and AI integration
- Learn real-time data processing and decision-making techniques
- Explore security challenges and risk mitigation strategies
- Optimize edge architectures for performance and scalability
- Apply AI-driven automation in real-time environments
Learning content
- Module 1: Introduction to Edge Computing and AI
- Module 2: Edge Computing Architectures and Frameworks
- Module 3: Real-Time Data Processing and AI Analytics
- Module 4: Security Challenges in Edge AI Systems
- Module 5: Optimizing Edge Computing for AI Applications
- Module 6: Future Trends and Industry Applications
Approach/method
Online
Duration
2 Days
Assessment
Yes
Certification
Yes
Date
Always available
Location
Online
Website
Course title: Optimization with Julia: Mastering Operations Research
Target group: Mid Level Employee
Level: Foundations
Optimization with Julia: Mastering Operations Research
Provider
Udemy
Description
The increasing complexity of the modern business environment has made operational and long-term planning for companies more challenging than ever. To address this, optimization algorithms are employed to find optimal solutions, and professionals skilled in this field are highly valued in today’s market.
In this course, you will learn how to problems problems using Mathematical Optimization, covering:
- Linear Programming (LP)
- Mixed-Integer Linear Programming (MILP)
- Nonlinear Programming (NLP)
- Mixed-Integer Nonlinear Programming (MINLP)
- ImplementingĀ summationsĀ andĀ multiple constraints
- Working withĀ solver parameters
- The followingĀ solvers: CPLEX, Gurobi, GLPK, CBC, IPOPT, Couenne, Bonmin, SCIP
This course is designed to teach you through practical examples, making it easier for you to learn and apply the concepts.
If you are new to Julia or programming in general, don’t worry! I will guide you through everything you need to get started with optimization, from installing Julia and learning its basics to tackling complex optimization problems. By completing this course, you’ll not only enhance your skills but also earn a valuable certification from Udemy.
Target
- Data scientists
- Operations researchers
- Analytics professionals
- Graduate students in engineering or applied mathematics
- Professionals interested in optimization
Sector
- Technology
- Manufacturing
- Logistics
- Finance
- Consulting
- Energy
- Research & Academia
Area
- Mathematical optimization
- Operations research
- Applied analytics
- Decision science
- Computational problem-solving
Learning outcomes
- Solve optimization problems using linear programming, mixed-integer linear programming, nonlinear programming, mixed-integer nonlinear programming
- Main solvers, including Gurobi, CPLEX, GLPK, CBC, IPOPT, Couenne, SCIP, Bonmin
- How to use JuMP to solve optimization problems with Julia
- How to solve problems with summations and multiple constraints
- How to install and use Julia
- How to install and activate each solver
Learning content
- Introduction
- Starting with Julia
- Linear Programming (LP)
- Mixed-Integer Linear Programming (MILP)
- Working with Double Summation and Multiple Constraints
- Using external inputs to solve a routing problem (VRP)
- Parameters and Progress of the Solver
- Nonlinear Programming (NLP)
- Mixed-Integer Nonlinear Programming (MINLP)
- Expanding Your Knowledge and Exploring Opportunities
Approach/method
Online
Duration
6 hours on-demand video
Assessment
No
Certification
Yes
Date
Always available
Location
Online
Website