Big Data Analytics for Predictive Maintenance Strategies

An Intensive 5-day Training Course

Big Data Analytics for Predictive Maintenance Strategies

Appropriate Maintenance Strategies

UPCOMING SESSIONS

Classroom sessions
DateVenueFee
06-10 Oct 2025Barcelona - Spain$5,950RESERVE A SEAT
09-13 Feb 2026Dubai - UAE$5,950RESERVE A SEAT
01-05 Jun 2026Barcelona - Spain$5,950RESERVE A SEAT
05-09 Oct 2026Barcelona - Spain$5,950RESERVE A SEAT

Training Course Overview

Given the ever-changing nature of disruptions and the growing need for lean and agile operations, it is crucial for organizations to manage their assets through innovative maintenance strategy selection and reconfiguration. Maintenance Strategies and Contracts help streamline the decision-making process by responding to current asset performance and guiding appropriate actions to enhance it. In today’s unpredictable and highly competitive environment, continuous assessment techniques and strategies are vital for operational success. Developing strong assessment capabilities is essential for effective leadership.

The Big Data Analytics for Predictive Maintenance Strategies training course is designed to strengthen your decision-making skills in selecting suitable maintenance strategies using the Decision Making Grid (DMG) framework. Participants will learn how to apply assessment methods focused on identifying improvement opportunities through the use of key performance indicators (KPIs). These techniques will be practiced through group work and case studies. Attendees are encouraged to bring relevant organizational data, such as KPIs, ongoing improvement initiatives, CMMS data, mission and vision statements, or any other materials they wish to analyze using the assessment tools provided in the course.

This training course will highlight:

  • Classification of maintenance Strategies
  • When to use or not to use RCM and TPM
  • How to get the most of the CMMS
  • Prioritizations and criticality of assets
  • Various case studies from different industries and especially oil and gas

Training Course Objectives

By the end of this training course, participants will be able to gain a detailed knowledge and skill towards operations and maintenance to enhance the existing skills in assessing the needs, selecting the best resources, managing operations and maintenance of systems and equipment and measure the performance of operations and maintenance providers. More specifically, at the end of this training course, you will learn: 

  • How to establish and manage outsourcing, contractor performance, monitor regularly and provide management information for continuous improvement
  • Define the concept of the DMG, reliability and maintenance strategies "best practice" and be equipped with tools and methodologies to measure and improve organizational performance
  • Assess and benchmark the performance of their own organization 
  • Use readily accessible principles, and studying real-time and historical data, to get a guideline operability
  • Develop guidelines for the development of key performance measures specific to the objectives of the organization

Designed for

This training course is suitable to a wide range of professionals but will greatly benefit:

  • Maintenance and Reliability Managers.
  • Maintenance and Reliability Supervisors 
  • Personnel designated as planners, or identified to become planners 
  • Team leaders from each Maintenance craft 
  • Key Operations Supervisors 
  • Materials Management Managers/Supervisors 
  • CMMS Administrator or key users 
  • Key Maintenance support assistants 
  • Other stakeholders in the Work Planning Function 

Learning Methods

This training course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. This includes hands-on, stimulating experience and using interactive user friendly decision analysis software. The training course is highly interactive with many discussion and facilitated practice sessions. Key points will be emphasised with case study examples. There will be a combination of presentation sessions and workshops during in this course. 

The Course Outline

Day One: Introduction to Maintenance Strategies - The Decision Making Grid (DMG)
  • Maintenance decision making and features of Big Data
  • Key performance indicators for the DMG
  • Utilization of data in the Computerized Maintenance Systems Management (CMMS)
  • Methods of partitioning the DMG
  • Identification of available maintenance strategies
  • Prioritization of responsive decisions
  • Application of multiple criteria decision making in the DMG
  • Cost-Benefit analysis of the DMG
Day Two: Keep the Best Practice - The OTF Decisions
  • Introduction to the concept of best practice ion reliability and maintenance
  • Maintenance standards
  • Maintenance auditing and benchmarkinG
  • Excellence awards in TQM
  • Reliability and Maintenance awards
  • Application to existing data
Day Three: Investigative Strategies - The CBM Decisions
  • Common definitions and terminology
  • Standards in Reliability
  • Difference between maintenance and reliability
  • Reliability modeling approaches and decision making
  • Reliability Centered Maintenance (RCM)
  • Techniques related to RCM: FMEA, RPN, ICC, FTA, RBD, and MCS
  • Condition Base Maintenance technologies
  • Application to existing data
Day Four: Human Factors - Skill Levels Upgrade Decisions
  • Key performance Indicators (KPIs)
  • Overall Equipment Effectiveness (OEE)
  • Total productive maintenance (TPM)
  • Ask Why 5 times concept
  • Learning from others
  • Application to existing data
Day Five: Reconfiguration - Design Out Maintenance Decisions
  • Getting the best out of data in CMMS
  • Integrated framework of the Decision Making Grid (DMG)
  • Reconfiguration of the Maintenance and Reliability Structurers
  • Guidelines for successful implementation

The Certificate

  • Anderson Certificate of Completion will be provided to delegates who attend and complete the course

In Association With

Aztech
Coventry
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