Course Description
Big Data Analytics for Predictive Maintenance Strategies Training Course provides a structured approach to selecting and optimizing maintenance strategies in today’s dynamic and competitive environment. Organizations must continuously adapt their maintenance practices to ensure asset reliability, operational efficiency, and cost control.
This training course focuses on leveraging big data analytics and the Decision Making Grid (DMG) framework to support informed maintenance decisions. Participants will learn how to assess asset performance, identify improvement opportunities, and apply data-driven strategies to enhance operational outcomes.
Through practical examples and real-world case studies, the course emphasizes the use of key performance indicators (KPIs), CMMS data, and reliability methodologies. It also explores when to apply techniques such as RCM and TPM effectively.
By the end of this Predictive Maintenance Training Course, participants will be equipped with the tools to improve maintenance decision-making, optimize asset performance, and drive continuous improvement across operations.
What you will achieve
Predictive Maintenance Strategies Training Course aims to strengthen participants’ ability to evaluate, select, and implement effective maintenance strategies using data-driven insights and best practices.
Participants will be able to:
- Apply the Decision Making Grid (DMG) framework to support maintenance decisions
- Evaluate and benchmark organizational maintenance performance using KPIs
- Utilize CMMS data and analytics to improve asset reliability and efficiency
- Identify appropriate maintenance strategies, including RCM and TPM applications
- Manage contractor performance and support outsourcing decisions effectively
- Develop performance measurement guidelines aligned with organizational objectives
How the course is delivered
Predictive Maintenance and Big Data Training Course adopts an interactive and practical learning approach to ensure effective knowledge transfer and application. The course integrates proven adult learning techniques to enhance understanding and retention.
Participants will engage in instructor-led sessions supported by group discussions, workshops, and real-world case studies. Hands-on exercises using decision analysis tools and software will enable participants to apply concepts directly to operational challenges.
The training emphasizes practical application through the use of real-time and historical data, including participants’ own organizational data where applicable. Case-based learning reinforces key concepts such as DMG application, KPI analysis, and maintenance strategy selection.
This approach ensures participants gain actionable insights and practical skills to implement predictive maintenance strategies effectively within their organizations.
Designed for
Big Data Analytics Training Course for Maintenance is designed for professionals involved in maintenance planning, reliability, and operational performance improvement across industries. It supports those responsible for data-driven decision-making and asset management.
This training course is particularly suitable for:
- Maintenance and Reliability Managers and Supervisors
- Maintenance Planners and personnel transitioning into planning roles
- Team Leaders across maintenance disciplines
- Operations Supervisors involved in equipment performance
- Materials Management Managers and Supervisors
- CMMS Administrators and key system users
- Maintenance support staff and stakeholders in work planning functions
Daily programme
- 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
- 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
- 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
- Key performance Indicators (KPIs)
- Overall Equipment Effectiveness (OEE)
- Total productive maintenance (TPM)
- Ask Why 5 times concept
- Learning from others
- Application to existing data
- 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
Certification & accreditation
BII Certificate of Completion
BII Certificate of Completion Upon successful completion, participants receive a BII Development Institute Certificate of Completion with a unique reference code that is independently verifiable. Our certificates are recognised internationally and reflect successful completion of your chosen programme.
