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MAINT-015 Maintenance Engineering and Asset Management
PROGRAMME BROCHURE

Predictive Maintenance with Data Analytics

An applied five-day programme focused specifically on Predictive Maintenance with Data Analytics.

Duration 5 days
Level Professional
Programme MAINT-015
KAIZEN EUROPEAN ACADEMY Executive & Professional Development www.kaizeneurope.academy
01

Programme Overview

This five-day Kaizen European Academy programme is dedicated specifically to Predictive Maintenance with Data Analytics. It develops practical capability in Preventive & Predictive Maintenance through structured explanation, applied tools, realistic scenarios and guided workshops. Participants move from core concepts to hands-on application, performance control and an implementation plan that can be transferred directly to their workplace.

02

Learning Objectives

Explain the essential concepts, terminology and professional context of Predictive Maintenance with Data Analytics.
Apply the principal methods and tools used in Predictive Maintenance with Data Analytics.
Analyse realistic situations and make evidence-based decisions related to Predictive Maintenance with Data Analytics.
Evaluate performance, risk and control requirements in Predictive Maintenance with Data Analytics.
Develop a practical implementation or improvement plan for Predictive Maintenance with Data Analytics.

Who Should Attend

Professionals, specialists, supervisors and managers whose responsibilities involve predictive maintenance with data analytics or who need to build practical capability in this area.

Programme Methodology

Instructor-led explanation, facilitated discussion, subject-specific case studies, practical templates, individual and group exercises, simulations or technical scenarios where appropriate, peer review and a final implementation workshop.

Learning Outcomes

Explain the essential concepts, terminology and professional context of Predictive Maintenance with Data Analytics. Apply the principal methods and tools used in Predictive Maintenance with Data Analytics. Analyse realistic situations and make evidence-based decisions related to Predictive Maintenance with Data Analytics. Evaluate performance, risk and control requirements in Predictive Maintenance with Data Analytics. Develop a practical implementation or improvement plan for Predictive Maintenance with Data Analytics.

Prerequisites

No formal prerequisite is required. Relevant professional experience is helpful; technical courses may assume basic familiarity with the operating environment.

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Course Outline

Day01

Predictive Maintenance with Data Analytics: Foundations and Operating Context

  • Scope, terminology and professional context of Predictive Maintenance with Data Analytics
  • Current practices and emerging trends in Predictive Maintenance with Data Analytics
  • Roles, responsibilities and stakeholder expectations in Predictive Maintenance with Data Analytics
  • Diagnostic assessment of current Predictive Maintenance with Data Analytics practices
Day02

Core Methods and Tools for Preventive & Predictive Maintenance

  • Failure patterns
  • Preventive maintenance logic
  • Time-based maintenance
  • Usage-based maintenance
Day03

Applied Practice in Predictive Maintenance with Data Analytics

  • Condition-based maintenance
  • Vibration monitoring
  • Oil analysis
  • Thermography
Day04

Performance, Risk and Control in Predictive Maintenance with Data Analytics

  • Ultrasound
  • Inspection intervals
  • P-F curve
  • Predictive analytics
Day05

Predictive Maintenance with Data Analytics: Integrated Workshop and Implementation

  • Maintenance optimization
  • False positives and missed failures
  • Data quality
  • Sensor strategy
04

What You Will Receive

Programme learning materials
Practical resources and templates where applicable
Kaizen completion certificate
Participant support throughout the learning week
Kaizen European Academy

Executive & Professional Development across selected European destinations.

CONTACT & INFORMATION

Website: www.kaizeneurope.academy
Contact: www.kaizeneurope.academy/#contact