Course Overview

What are predictive maintenance technologies?

Predictive maintenance technologies are used for the estimation of potential equipment failure. The actual point of failure of the equipment can also be recognized in advance. The driving idea behind predictive maintenance technologies is to prepare corrective maintenance strategies before the equipment completely degrades. The corrective maintenance strategies are established at a suitable time and situation to avoid any significant problems. Moreover, the strategist got a lot of time to evaluate different strategies within the minimum budget.

How do you start predictive maintenance?

Zoe Talent Solutions’ Predictive Maintenance Technologies course is meant to help you start and develop high-level skills in predictive maintenance. This Zoe course encompasses various contemporary technologies and software that will enable you to get in-depth knowledge of equipment analysis and interpretation. After completing this course, you will be able to apply the gained knowledge in real—life and be professional in handling the issues.

Course Objectives

The Predictive Maintenance Technologies course has many primary objectives that will enable the trainees in

• Understanding the use of predictive maintenance technologies as per the changing requirements of the market trends
• Implementation of predictive maintenance technologies to predict the failing point of the equipment using software and other new technologies
• Learning how the best solutions and technologies can help in untying the complex knot of real-world issues
• Assessing the chances of the productivity increment by using better and more current information, technologies, and processes
• Knowing how to make Predictive maintenance practical and effective to develop strategies to solve the issue of equipment failure
• Comprehending the technologies to improve the asset information consistency and reliability so that they could work best to be at a consistent pace of achieving the company’s objectives
• Apprehending why Predictive maintenance should be given more priority than reactive maintenance

Training Methodology

Because the world is constantly changing and evolving, all of Zoe Talent Solutions’ courses undergo a rigorous testing process to ensure that they satisfy the most up-to-date industry standards. Professionalism and hands-on experience are hallmarks of the instructors. Various activities such as role-plays, individual and group projects, and big and minor projects all maintain a constant flow of two-way interaction. Real-world situations and case studies play an essential role in this training.

Zoe Talents has invented a distinctive approach, the Do–Review–Learn–Apply Model, to ensure the best learning experience by maximizing the input of the trainees.

Organisational Benefits

The organizations can gain the below-mentioned benefits from the experts in predictive maintenance technologies who are the products of this course:

• Use of contemporary predictive maintenance technologies
• Developing the maintenance strategies which are cost-effective and based on the analysis generated with the help of predictive maintenance techs
• Confident employees to make forecasts about failure points of the equipment
• Adequate and reasonable integration of the Predictive Maintenance into the workflow and CMMS
• Streamline the processes, workflow, and their effects on equipment degradation
• Monitor the performance of your employees with an effective system
• Regulating the time and money spent on maintenance
• Ensure that the maintenance budget is well-managed, overseen, and well-spent

Personal Benefits

After completing this course, the experts would be able to achieve the following personal benefits:

• Increased ability to conduct the analysis
• Enhanced critical thinking ability and technology usage skills
• Understanding and correctly using equipment analysis and how it can help in developing the maintenance strategies
• Find out what equipment parts should be included in the predictive maintenance strategy
• Be able to determine the equipment’s failure risk and the most appropriate failure detection interval for protection devices using condition-based maintenance
• Know how to determine the best inspection frequency for equipment that is constantly running
• Predictive maintenance solutions can be seamlessly included in workflows and CMMS
• Know how to get to the point where an asset’s usage begins to fall as it ages
• Enhancing personal knowledge
• A clear vision and sense of direction for your professional life
• Improved ability to present data analysis visually and interpret the analysis
• Knowing current trends of the industry and working on predictive maintenance technologies accordingly

Who Should Attend?

• Maintenance supervisors. Maintenance Managers
• Any individual who is meant to become a planner
• Predictive Maintenance supervisors
• PdM Managers
• Technicians in the field of PdM
• Leaders who aim to keep the equipment up
• Important users of CMMS
• Reliability Engineers
• Maintenance Engineers
• Material Managers
• Materials supervisors 
• Any individual who is interested in this domain and wants to adopt this career

Course Outline

The most important topics that are necessary to be an expert on PdM technologies are given below:

Module 1: Overview of the Maintenance

• What is Maintenance?
• Why is it important?
• What are the benefits of Maintenance?
• Types of Maintenance

Module 2: PdM

• What is PdM?
• Why is it used?
• Why is it important?
• How is it work?
• Existing technologies names

Module 3: Analysis: Vibration

• Definition
• Usage
• Applications
• Safety measures
• Tools

Module 4: Thermography, Ultrasonic, and Tribology 

• Definitions
• Usages of each technology
• Applications
• Safety measures
• Tools

Module 5: Establishing a PdM Program

• Steps
• Requirements
• Things to consider
• Things to avoid

Module 6: CMMS

• Structure
• DB
• Workflow
• Maintenance strategies
• Management of the Configuration
• Asset Register

Module 7: PFA

• FMECA and RBM integrating with PFA
• Comprehension of P-F intervals
• Decisions about which technology is well-suited and when

Module 8: New Technologies (PdM)

• Megger Tests
• Temperature Sensitive Labels
• Visual Inspections

Module 9: Maintenance Process: Control

• Stages of Implementation
• Things to consider
• KPIs for reporting

Module 10: The Planning

• The workflow of maintenance
• Roles during preparation
• Roles during planning
• Roles during Scheduling
• Responsibilities during Preparation
• Responsibilities during planning
• Responsibilities during Scheduling
• Preparation principles
• Planning principles
• Principles of work Scheduling
• Network of the team

Module 11: Six critical steps for developing a predictive maintenance program

• Formulation of the plan for the program
• Understating the audience
• Know what is an implementation plan and how to create it
• Working on some background knowledge
• Holistic view
• Achieving an effective Buy-in
• Some most essential rules of the predictive maintenance program

Module 12: Core topics

• Analysis of the Data
• Data trend
• Understanding the data analysis
• ROI
• Predictive Maintenance economics