Introduction
The programme “Training in Smart and Digital Maintenance” develops professional practice in Maintenance. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from training design and measurement of learning transfer to mechanical equipment analysis and fault diagnosis, with practical work on maintenance planning, work orders, and execution measurement, designing digital transformation and developing services, reliability, predictive maintenance, and failure analysis. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Design a training intervention that begins with a performance gap and ends with evidence of application in an application related to “Training in Smart and Digital Maintenance”.
- Build a maintenance plan and work order connecting asset criticality, resources, and documentation.
- Assess digitization opportunities and define implementation requirements that improve a service or process.
- Analyze asset failure and condition data to define a justified warning and maintenance intervention.
- Interpret mechanical equipment performance and identify fault hypotheses and safe verification steps.
Learning areas
1. Training Design and Measurement of Learning Transfer
- Analyze performance gaps at organizational, job, and individual levels, and verify that training addresses a cause related to knowledge or skill.
- Write observable learning objectives, define entry requirements, and link each objective to a training activity and assessment evidence.
- Build a sequence of content, activities, and practical cases, balancing explanation, experimentation, and feedback within the available time.
- Select suitable learning methods, face-to-face delivery, and digital learning, and ensure accessibility, material quality, and delivery instructions.
- Design pre- and post-learning assessments and a follow-up plan with the line manager to measure application and identify additional support needs. The application examines a case related to “Training in Smart and Digital Maintenance”.
2. Maintenance Planning, Work Orders, and Execution Measurement
- Inventory assets and build a hierarchy, coding system, technical data, and maintenance history, classifying criticality by safety, service, and cost.
- Select a mix of preventive, condition-based, and corrective maintenance, connecting the decision to failure modes, data, and manufacturer instructions.
- Plan the work order's scope, resources, materials, time, isolation, and permits, and define readiness conditions before scheduling.
- Organize schedules, shutdowns, and equipment handovers between operations and maintenance, recording actual work, causes, parts, and time.
- Analyze backlog, recurrence, plan compliance, and reliability, and propose documented adjustments to maintenance tasks and their frequency.
3. Designing Digital Transformation and Developing Services
- Distinguish information digitization, step automation, and business model transformation, and identify the problem targeted by the digital intervention.
- Map the beneficiary journey, touchpoints, and repeated data requests, and identify opportunities for simplification before selecting technology.
- Analyze readiness across procedures, skills, data, and technical infrastructure, and document gaps and dependencies on existing systems.
- Specify solution, integration, access permission, usability, and accessibility requirements, and establish testable acceptance criteria.
- Design a limited-scope pilot with indicators for time, quality, and use, and define conditions for continuing, adjusting, or stopping.
4. Reliability, Predictive Maintenance, and Failure Analysis
- Define the asset's function, functional failure, and usage context, and assess the effects of failure modes before selecting a maintenance task type.
- Organize fault, downtime, repair, and condition reading histories, checking the quality of timestamps, classifications, and record completeness.
- Analyze trends, vibration, temperature, or other appropriate condition indicators, linking alerts to documented thresholds and specialist technical review.
- Distinguish correlation and prediction from proof of a failure's cause, and assess false and missed alarms and warning lead time before intervention.
- Design a condition monitoring pilot for a training asset, with escalation criteria and documentation of the maintenance decision, and verify the intervention's effect on reliability.
5. Mechanical Equipment Analysis and Fault Diagnosis
- Read training equipment data and diagrams, identifying function, operating conditions, design limits, and key measurement points.
- Analyze relationships between load, flow, pressure, temperature, and vibration, and review measurement quality before interpreting performance deviations.
- Identify failure modes involving components, seals, bearings, alignment, and lubrication, and connect fault symptoms to multiple testable hypotheses.
- Select inspections and diagnostic methods suited to the condition and criticality, and refer to manufacturer instructions and isolation and permit procedures before any intervention.
- Prepare a diagnostic report showing readings, evidence, possibilities, the next verification step, and the limits of conclusions from the available data.
Practical outputs
- A needs analysis, concise learning package, and application evaluation plan.
- A maintenance plan, work schedule, work order card, and monitoring indicators.
- A digital transformation roadmap covering the beneficiary journey and implementation requirements.
- A failure mode analysis, condition monitoring plan, and alert and review rules.
- An equipment profile, fault diagnosis tree, and preliminary inspection plan.
Who should attend
- Engineers, technicians, supervisors and operations staff whose work relates to the programme subject.
- Managers and teams working in maintenance, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Training in Smart and Digital Maintenance” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “Training in Smart and Digital Maintenance” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.