Maintenance and Reliability Engineering Training Course

Duration 10 days 16 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Reliability Engineers, Maintenance Engineers and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-ME-088

Before you join: Participants should understand basic industrial equipment, maintenance work orders and the operating context of the assets they support.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Maintenance performance is often constrained by recurring failures, weak work preparation, inaccurate asset data, poorly targeted preventive tasks and spare-parts shortages. These issues raise downtime, create production losses, increase safety exposure and consume maintenance budgets without improving equipment health. Reliability engineers and maintenance professionals need a structured way to decide which assets matter most, identify failure mechanisms, select effective maintenance tasks and prove that improvement actions are working.

This course develops the engineering and management practices used to build and improve a reliability-centred maintenance system. Participants apply criticality analysis, functional analysis, failure mode and effects analysis, reliability-centred maintenance, root cause analysis, condition monitoring selection, maintenance planning, shutdown preparation, spare-parts control and reliability performance measurement. They learn to distinguish time-based, condition-based, failure-finding and run-to-failure tasks, then connect these choices to asset risk, production requirements and lifecycle cost.

Instruction combines focused briefings with industrial case work, facilitated analysis, team decision-making and structured application to participants' own assets or equipment classes. Cases reflect process plants, utilities, transport fleets, facilities and manufacturing operations. Throughout the course, participants develop an asset reliability improvement pack containing a criticality ranking, failure analysis, maintenance strategy, KPI set, work-management controls and improvement roadmap. The final capstone requires participants to review and present the completed pack as they would to an operations or engineering leadership team.

The course suits maintenance engineers, reliability engineers, planners, supervisors and operations personnel who already work with physical assets and need a common technical method for improving availability, safety and maintenance value.

What you will be able to do

  • Classify assets using consequence-based criticality analysis and risk ranking
  • Develop failure mode analyses using FMEA, functional failure and failure-effect logic
  • Select maintenance tasks using reliability-centred maintenance decision criteria
  • Investigate recurring equipment failures using root cause analysis and evidence chains
  • Design condition-monitoring routes matched to failure modes and P-F intervals
  • Build weekly maintenance plans, schedules and backlog controls for critical work
  • Calculate reliability and maintenance indicators from work orders and operating data
  • Present an asset reliability improvement plan with priorities, controls and measures

Benefits of attending

For you

  • Produce maintenance strategies that address identifiable failure mechanisms
  • Diagnose recurring failures using structured evidence rather than assumptions
  • Prioritise engineering effort against safety, production and cost consequences
  • Improve credibility when presenting maintenance recommendations to operations leaders
  • Build reusable analyses for equipment upgrades, shutdowns and reliability reviews

For your organisation

  • Reduced repeat failures through targeted corrective actions and task redesign
  • Higher planned-work percentage from improved preparation and schedule discipline
  • Better maintenance spending decisions through criticality and lifecycle-cost evidence
  • Improved asset availability by matching maintenance tasks to failure behaviour
  • Clearer reliability reporting for production, engineering and asset-management decisions

Course modules

16 modules over 10 days

Participants can explain how maintenance decisions affect asset function, risk, availability and cost.

  • Asset functions, performance standards and functional failures defined precisely
  • Reliability, availability, maintainability and supportability relationships for physical assets
  • Failure consequences grouped into safety, environmental, operational and economic categories
  • Maintenance value drivers linked to production losses and risk exposure
  • The asset lifecycle from design acceptance through disposal decisions
  • Reliability engineer, planner, supervisor and operator accountabilities compared

Participants can construct an asset hierarchy and rank equipment by consequence and risk.

  • Asset register structures using system, subsystem and maintainable-item levels
  • Functional boundaries established between process units and supporting utilities
  • Criticality matrices scored for safety, production, environmental and repair consequences
  • Risk ranking combines consequence severity with failure likelihood estimates
  • Single-point failures identified within production and protection system configurations
  • Criticality results translated into maintenance strategy and spare-parts priorities

Participants can convert maintenance and operating data into useful reliability measures.

  • Failure definitions standardised before analysing work-order and downtime records
  • Mean time between failures calculated from operating hours and events
  • Mean time to repair separated from waiting and logistics delays
  • Availability calculated using uptime, downtime and planned outage assumptions
  • Pareto charts isolate dominant failure modes and downtime contributors
  • ISO 14224 data fields applied to equipment failure classification

Participants can develop an FMEA that connects functions, failures, causes and effects.

  • Functions written with required output, standard and operating context
  • Functional failures expressed as measurable losses of required performance
  • Failure modes distinguished from symptoms, causes and observed effects
  • FMEA worksheets record local effects, system effects and consequences
  • Severity, occurrence and detection ratings applied with defined scoring criteria
  • Failure mode prioritisation directs analysis toward material risk exposures

Participants can choose appropriate maintenance policies using RCM decision logic.

  • RCM decision logic links failure consequences to maintenance policy
  • Scheduled restoration assessed against age-related failure evidence
  • Scheduled discard selected where component life limits are credible
  • Condition-based tasks matched to detectable deterioration and P-F intervals
  • Failure-finding tasks assigned to hidden protective-function failures
  • Run-to-failure policies justified for low-consequence, economic failure modes

Participants can improve preventive maintenance tasks, intervals and work instructions.

  • Existing preventive maintenance tasks screened for technical applicability
  • Task intervals reviewed using failure history, duty cycle and condition evidence
  • Maintenance-induced failures considered when adding intrusive preventive work
  • Precision maintenance requirements embedded within lubrication, alignment and assembly tasks
  • Job plans specify access, isolation, tools, materials and acceptance criteria
  • Task rationalisation removes duplication, vague instructions and ineffective checks

Participants can select condition-monitoring methods for common equipment failure modes.

  • P-F interval concepts determine suitable inspection and monitoring frequencies
  • Vibration analysis identifies imbalance, misalignment, looseness and bearing defects
  • Infrared thermography detects electrical resistance and thermal insulation abnormalities
  • Oil analysis monitors contamination, wear debris and lubricant degradation
  • Ultrasound testing identifies leaks, lubrication defects and electrical arcing
  • Condition-monitoring alarms linked to response actions and work-order triggers

Participants can investigate repeat failures and define actions that prevent recurrence.

  • Problem statements separate observed facts from early assumptions
  • Five Whys analysis tests causal chains behind equipment failure events
  • Fault tree analysis maps combinations producing defined top events
  • Causal factor charts distinguish technical, human and organisational contributors
  • Evidence collection includes failed parts, trends, photographs and operator accounts
  • Corrective actions address physical causes, latent causes and control weaknesses

Participants can prepare maintainable, safe and resource-ready maintenance job plans.

  • Work requests screened for scope, priority and asset identification quality
  • Job plans define task sequence, labour hours and skill requirements
  • Permits, isolations and lockout-tagout requirements identified before scheduling
  • Materials lists distinguish stocked spares, consumables and external services
  • Standard job plans capture repeatable methods for recurring maintenance work
  • Ready-for-scheduling criteria prevent avoidable delays during execution

Participants can control maintenance backlog and create realistic weekly work schedules.

  • Backlog classified by priority, age, craft, readiness and asset criticality
  • Weekly schedules balance available labour, access windows and production constraints
  • Schedule compliance measured against approved weekly work commitments
  • Break-in work controlled through defined urgency and authorisation rules
  • Daily coordination resolves permit conflicts, material shortages and access restrictions
  • Planned-work percentage tracked as a leading maintenance management measure

Participants can set spare-parts controls based on equipment criticality and supply risk.

  • Bill of materials structures connect equipment records to replaceable spares
  • Critical spares identified using consequence, lead time and failure probability
  • Min-max levels set from consumption patterns and replenishment lead times
  • Interchangeability, preservation and shelf-life requirements recorded for stored parts
  • Obsolescence risks assessed for controls, electronics and specialised components
  • Kitting processes improve planned-work readiness before scheduled maintenance

Participants can prepare a risk-based shutdown scope, schedule and control process.

  • Shutdown scope developed from statutory work, inspections and reliability priorities
  • Work packs sequenced around isolation plans, access and critical paths
  • Critical path method identifies schedule constraints and float consumption
  • Scope freeze controls late additions and protects execution readiness
  • Contractor interfaces managed through clear responsibilities, permits and quality checks
  • Post-shutdown reviews capture defects, delays and future scope improvements

Participants can interpret Weibull results to support maintenance interval and replacement decisions.

  • Failure distributions distinguish random, early-life and wear-out behaviour
  • Weibull shape parameter indicates changing failure rate characteristics
  • Weibull scale parameter estimates characteristic life for analysed components
  • Probability plots test whether field data supports selected distributions
  • Censored data handled when equipment remains operating at analysis close
  • Replacement decisions compare failure risk, outage cost and intervention cost

Participants can compare maintenance, repair and replacement options using lifecycle cost evidence.

  • Maintenance costs separated into labour, materials, services and production losses
  • Lifecycle cost models include acquisition, operation, maintenance and disposal
  • Repair-versus-replace decisions consider reliability, lead time and risk exposure
  • Bad-actor assets identified through repeated cost, downtime and failure patterns
  • Capital improvement cases quantify avoided failures and expected benefit
  • Decision records document assumptions, uncertainty and approval requirements

Participants can establish reliability measures, review routines and improvement governance.

  • Leading indicators include planned-work percentage, schedule compliance and overdue PMs
  • Lagging indicators include downtime, repeat failures and maintenance cost
  • KPI definitions specify formulas, data sources, owners and review frequency
  • Control charts distinguish normal variation from meaningful performance deterioration
  • Reliability review meetings assign actions, deadlines and benefit measures
  • Management of change protects maintenance strategies after equipment modifications

Participants can build, review and present a complete asset reliability improvement plan.

  • Selected asset system defined with functions, boundaries and operating requirements
  • Criticality ranking establishes the case for focused reliability improvement
  • FMEA and RCM decisions produce an evidence-based maintenance strategy
  • Root cause findings prioritise defect-elimination actions and engineering changes
  • Implementation roadmap assigns owners, milestones, resources and performance measures
  • Peer review tests technical logic, practicality and business case assumptions

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Asset criticality assessment template
  2. FMEA and RCM decision worksheet
  3. Preventive maintenance optimisation checklist
  4. Maintenance planning and scheduling control model
  5. Reliability KPI dashboard specification
  6. Asset reliability improvement plan

Who should attend

  • Reliability Engineers — need disciplined methods for preventing repeat failures and improving asset performance
  • Maintenance Engineers — need to convert equipment knowledge into effective maintenance strategies
  • Maintenance Planners — need stronger job planning, scheduling and backlog-control practices
  • Maintenance Supervisors — need practical controls for executing planned work and improving quality
  • Operations Engineers — need to balance production risk, equipment availability and maintenance windows
  • Asset Managers — need evidence-based priorities for maintenance investment and lifecycle decisions

Skills and tools covered

Asset criticality analysisReliability-centred maintenanceFailure mode analysisMaintenance work managementCondition monitoring selectionReliability performance measurement

Tools and standards

ISO 14224, Reliability-Centred Maintenance, Failure Modes and Effects Analysis, Weibull analysis

How the course runs

Training methodology

The course uses short technical briefings followed by equipment-based cases, group analysis and facilitated decision sessions. Participants work through asset criticality ranking, FMEA, RCM task selection, root cause investigations, planning scenarios and KPI calculations using realistic maintenance records. Simulations test how planning quality, spare availability and schedule compliance affect downtime. Trainers provide structured templates and feedback while participants build an application pack for an asset class, production line, utility system or fleet relevant to their work.

Requirements and prerequisites

Participants should understand basic industrial equipment, maintenance work orders and the operating context of the assets they support. Experience in maintenance, operations, engineering, planning, inspection or asset management is expected. Participants should be comfortable reading simple equipment drawings, reviewing maintenance histories and discussing production or service risks. Prior knowledge of reliability-centred maintenance, Weibull analysis, vibration analysis, ISO standards or specialist software is not required. The course explains the required methods before participants apply them to cases and their own equipment examples.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should have practical familiarity with industrial assets, maintenance work or operations. You do not need prior training in RCM, FMEA, Weibull analysis, condition monitoring or specialist maintenance software.

Bring a laptop if possible and non-sensitive information about an asset class, recurring failure or maintenance challenge from your workplace. Equipment lists, sample work orders, downtime records or existing preventive maintenance tasks are useful but not essential.

It is intended for maintenance and reliability engineers, planners, supervisors, operations engineers and asset managers. It is most useful for people responsible for improving equipment availability, maintenance effectiveness or repeat-failure performance.

Condition monitoring courses focus mainly on diagnostic technologies such as vibration, oil analysis and thermography. Asset management courses focus more broadly on governance and lifecycle value; this course concentrates on engineering maintenance strategies, work management and reliability improvement.

You can use the templates to rank asset criticality, review preventive maintenance tasks, investigate repeat failures and establish reliability measures. The capstone plan provides a practical starting point for a focused improvement project.

The first part establishes asset criticality, failure analysis, RCM and condition-monitoring selection. The later modules develop planning, spares, shutdown, reliability analysis, KPI control and a completed reliability improvement plan; each training day runs from 08:30 to 16:30 with about 6.5 contact hours.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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