An Intensive 5-day Training Course

Maintenance Analytics

Leveraging Analytics to Enhance Operational Efficiency

Course Introduction

Maintenance Analytics involves the use of data-driven techniques to optimize maintenance processes and improve asset performance. This Oxford Management Centre training course offers a comprehensive introduction to maintenance analytics, covering essential aspects such as data collection, analysis, and interpretation to support informed decision-making.

Participants will gain expertise in utilizing maintenance data to predict equipment failures, optimize maintenance schedules, and minimize downtime. Through a blend of theoretical concepts and hands-on exercises, attendees will develop the necessary skills to effectively implement maintenance analytics within their organizations

Objectives

By the End of This Maintenance Analytics Training Course, Participants Will Be Able To:

  • Understand the core principles of maintenance analytics and its impact on asset management.
  • Identify and gather relevant maintenance data for effective analysis.
  • Apply data analysis techniques to derive actionable insights from maintenance data.
  • Develop predictive maintenance models to enhance scheduling and efficiency.
  • Calculate and interpret key performance indicators (KPIs) to assess maintenance effectiveness.
  • Utilize maintenance analytics to improve asset reliability and minimize costs.
  • Effectively communicate analytical insights to key stakeholders for informed decision-making.

Training Methodology

The Oxford Management Centre training course will employ a blended learning approach, combining classroom instruction, hands-on exercises, and case studies. Participants will have the opportunity to work with real-world maintenance data using industry-standard analytics tools. The training course will be interactive, encouraging active participation and discussion among attendees.

Organisational Impact

By integrating maintenance analytics into operations, organizations can achieve:

  • Greater equipment reliability and availability through proactive maintenance strategies.
  • Lower maintenance costs by optimizing maintenance schedules and resource allocation.
  • Improved decision-making based on data-driven insights and predictive analysis.
  • Enhanced asset lifecycle management to maximize equipment longevity and performance.
  • Better overall equipment effectiveness (OEE) by minimizing downtime and inefficiencies.
  • Stronger risk management through predictive failure analysis and early issue detection.
  • Increased operational efficiency and productivity by reducing unplanned maintenance activities.

Personal Impact

Upon completing this Maintenance Analytics training course, participants will:

  • Build a solid foundation in maintenance analytics and data-driven decision-making.
  • Develop practical expertise in collecting, analyzing, and interpreting maintenance data.
  • Enhance their ability to identify opportunities for maintenance optimization and process improvements.
  • Strengthen problem-solving and critical thinking skills for data-informed decision-making.
  • Increase their professional value by contributing to cost reduction and operational efficiency.

Who Should Attend?

This Oxford Management Centre Maintenance Analytics training course is designed for professionals involved in maintenance and asset management, including:

  • Maintenance managers and supervisors
  • Reliability engineers
  • Asset management professionals
  • Maintenance planners and schedulers
  • Data analysts with an interest in maintenance
  • Engineers and technicians with maintenance responsibilities
  • Individuals looking to develop their data analytics skills for maintenance applications

Course Outline

Day One

Introduction to Maintenance Analytics and Data Collection

  • Introduction to maintenance analytics and its benefits
  • Importance of data-driven decision making in maintenance
  • Identifying key performance indicators (KPIs) for maintenance
  • Data sources and types relevant to maintenance (CMMS, ERP, IoT sensors, etc.)
  • Data quality and cleansing techniques
  • Data exploration and visualization using sample maintenance data
  • Introduction to data visualization tools (e.g., Excel, Power BI, Tableau)
  • Creating basic visualizations (charts, graphs, dashboards) to understand maintenance patterns
Day Two

Descriptive and Diagnostic Analytics

  • Descriptive statistics for maintenance data (mean, median, mode, standard deviation)
  • Data distribution analysis (histogram, box plot)
  • Correlation analysis to identify relationships between variables
  • Time series analysis for maintenance data (trend analysis, seasonality)
  • Root cause analysis techniques (5 Whys, Pareto analysis)
  • Failure mode and effects analysis (FMEA)
Day Three

Predictive Analytics and Machine Learning

  • Introduction to predictive modeling and its applications in maintenance
  • Data preparation for predictive modeling (feature engineering, normalization)
  • Overview of machine learning algorithms for maintenance (regression, classification, clustering)
  • Model evaluation metrics (accuracy, precision, recall, F1-score)
  • Building a predictive maintenance model using a machine learning tool (e.g., Python, R)
  • Model deployment and monitoring
Day Four

Prescriptive Analytics and Optimization

  • Introduction to prescriptive analytics and optimization
  • Optimization techniques for maintenance scheduling (linear programming, integer programming)
  • Simulation modeling for maintenance planning
  • Risk-based maintenance (RBM)
  • Implementing prescriptive analytics to optimize maintenance operations
  • Challenges and opportunities in applying prescriptive analytics
Day Five

Implementation and Organizational Change

  • Developing a maintenance analytics roadmap
  • Change management and stakeholder engagement
  • Overcoming challenges in implementing maintenance analytics
  • Return on investment (ROI) measurement
  • Continuous improvement and monitoring of maintenance analytics
  • Best practices for maintenance analytics

Certificate

Oxford Management Centre Certificate will be provided to delegates who successfully completed the training course.

Maintenance Analytics
Duration
5 days
Format
Classroom
Language
English
Choose the date and location that suits you:
Classroom Sessions
London
09-13 Jun 2025
Fee: $5,950
Book your place
London
20-24 Oct 2025
Fee: $5,950
Book your place
London
08-12 Jun 2026
Fee: $5,950
Book your place
London
19-23 Oct 2026
Fee: $5,950
Book your place

FREQUENTLY ASKED QUESTIONS

To check on availability please call Registrar’s Office at +971 50 985 0174. If you have any questions or enquiries please feel free to contact us

Yes, we provide assistance in securing both hotel reservations & entry visa on all our international training venues, for delegates attending our training courses. For further information / assistance, please contact our Customer Service at:

Yes, Oxford Management Centre is accredited by the following professional bodies;

National Association of State Board of Accountancy (NASBA)
The Oxford Management Centre is registered with NASBA as a sponsor of Continuing Professional Education (CPE) on the National Registry of CPE Sponsors. NASBA have final authority on the acceptance of individual courses for CPE credit.

Yes, discounts are available. For further information please call +971 50 985 0174 or email, [email protected]

Note: Discounts are not applicable with any other special offer that may be available.

There are 2 easy ways to register:

  • Online: Select the training course you want to register for, Click the “Book Your Place” button on the course page, complete the form and click submit.
  • E-mail: Send your details to [email protected]

We request that all cancellations be made at least one week before the class start date. You may reschedule this class without any penalty. If not, a $250 fee will be charged for cancellations received less than one week before a class begins and for no-shows. Cancellation penalties and any fees incurred by Oxford Management Centre will be deducted from refunds.

For more information request, email [email protected] or call +971 50 985 0174.

The classroom training fees include course presentation, relevant materials, physical & digital documentation, lunch and refreshments served during entire training. Accommodation and transportation are not included in the training course fees.

While, online training fees cover the course presentation and digital documentation and relevant materials.

The Oxford Management Centre Certificate of Completion with corresponding CPE credits shall be awarded to delegates who has successfully completed the training course.

Payment must be received before the training course commences. You can make payment by bank draft, cash, credit card or wire transfer.

Note: If the payment is not received, Oxford Management Centre has the right to refuse admission.

Upon receipt of your registration form, we will send you the following by e-mail:

  • Registration Confirmation
  • Invoice/Receipt (where appropriate)

If you register online you will receive an e-mail within 24 hours confirming your registration.


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