Overview:
This course aims to introduce participants to predictive maintenance techniques used in complex mechanical systems. It covers the importance of early analysis of performance and failure data, along with the application of various sensing technologies to predict failures, ultimately reducing downtime and enhancing system efficiency.
Objectives:
- Understand the principles of predictive maintenance and its significance in managing mechanical systems.
- Learn about the tools and techniques for collecting data necessary for predicting equipment condition.
- Apply data analysis strategies to foresee failures and improve maintenance practices.
- Design and implement effective predictive maintenance programs.
- Develop the skills to make data-driven decisions to enhance operational performance.
Training Content:
- Introduction to Predictive Maintenance: Definitions and principles of predictive maintenance.
- Data Collection Techniques: Utilizing sensors and measurement tools.
- Data Analysis: Techniques for big data analysis and its applications.
- Failure Modeling: How to model and predict failures based on data.
- Implementing Predictive Maintenance Programs: Designing and applying effective predictive maintenance strategies.
- Case Studies: Examination of real-world applications of predictive maintenance in mechanical systems.
Target Audience:
This course is designed for engineers and technicians working in maintenance and facility management, as well as students in mechanical engineering. It is also suitable for professionals looking to enhance their skills in predictive maintenance to improve mechanical system performance and reduce maintenance costs.
