Medical Equipment Maintenance and Fault Diagnosis Training Course
1Summary
When a ventilator or a patient monitor fails mid-shift, there is no time to improvise — the technician on call needs to diagnose the fault fast, safely and correctly, or patient care stops. As hospitals rely on an ever-growing range of complex, connected medical devices, that kind of readiness has become a core skill rather than a specialist extra.
The Medical Equipment Maintenance and Fault Diagnosis Training Course, delivered by the Arab British Fellowship Training Academy, builds exactly that readiness. Participants work through the technical fundamentals of medical devices and practise identifying, tracing and resolving faults using current diagnostic methods, so that technicians and engineers keep equipment running reliably and keep patients safe.
2Objectives and target group
Who Should Attend?
- Managers and department heads in health facilities, and anyone working in or entering the field of medical device engineering.
- Students and researchers specialising in medical engineering and the medical sciences.
- Anyone looking to build their skills in maintaining and troubleshooting medical equipment.
Course Objectives
By the end of the course, participants will be able to:
- Identify therapeutic and diagnostic devices and detect faults in them with confidence.
- Apply electrical safety standards and medical device examination procedures correctly.
- Build a risk-based maintenance programme for medical equipment.
- Evaluate the effectiveness of a maintenance and fault-management programme.
3Course Content
Module 1: Medical Devices and Why Maintenance Matters
- What counts as a medical device, and how they're classified by function (diagnostic, therapeutic, monitoring).
- Why routine maintenance reduces failures, and the difference between preventive, corrective and predictive maintenance.
- How technicians and clinical staff work together during maintenance.
Module 2: Inside a Medical Device — Components and Safety
- Electrical, mechanical, digital and software components.
- Preventing electrical hazards and using personal protective equipment.
- General safety guidelines that protect patients and technicians alike.
Module 3: Recognising Common Faults
- Electrical faults: power interruptions, damaged circuits.
- Mechanical faults: worn moving parts, fluid leaks.
- Electronic faults: signal loss, circuit board issues.
Module 4: Diagnosing the Root Cause
- Using voltmeters, multimeters and other measuring tools.
- Reading error messages and fault codes on device displays.
- Step-by-step diagnostic procedures, and reviewing operational records to spot recurring patterns.
Module 5: Repair, Replacement and Post-Repair Testing
- Selecting the right repair steps for the fault identified, and replacing parts to original specification.
- Testing the device after repair to confirm it performs correctly.
- Documenting maintenance and repair work for future reference.
Module 6: Tools of the Trade
- Essential diagnostic tools: multimeters, voltmeters, calibration devices.
- Hand tools: wrenches, screwdrivers, pliers.
- Advanced equipment such as soldering tools and specialised diagnostic instruments.
Module 7: Preventive Maintenance Programmes
- Building regular maintenance schedules for a facility.
- Preventive techniques that reduce future failures.
- Post-maintenance testing to confirm optimal performance.
Module 8: Maintaining Advanced and Life-Critical Devices
- Advanced diagnostic equipment such as MRI and X-ray machines.
- Advanced therapeutic devices such as ventilators and pacemakers.
- The particular challenges of maintaining complex, modern technologies.
Module 9: Communicating with Teams and Keeping Records
- Communicating clearly with medical and administrative teams.
- Preparing maintenance reports and keeping accurate documentation.
Module 10: Smart and Connected Medical Devices
- Internet of Things (IoT) devices in healthcare and how they're maintained.
- Challenges of integrating smart systems with medical equipment.
- The growing role of artificial intelligence in performance monitoring and fault detection.