Sofema Online (SOL) Takes a Deep Dive into MEDA Best Practices
Developing effective and corrective actions is the ultimate goal of any MEMS investigation. The MEDA process is specifically designed to facilitate this by having investigators, typically using the MEDA Results Form, uncover the why behind the error- the contributing factors.
Issues and Concerns in Developing Corrective Actions
- Superficial Blaming (Attribution Bias): The most significant pitfall is a tendency to stop the investigation at the individual level (e.g., “technician was careless”) and prescribe “re-training” as the corrective action. This ignores the systemic factors and ensures the error is likely to recur.
- Vague Corrective Actions: Using non-specific language in recommendations (e.g., “improve procedures” or “inadequate supervision”) prevents targeted and measurable improvements.
- Proximity Bias: Over-labelling factors close in time or space to the error as causal, potentially missing long-term organisational or management factors (e.g., staffing decisions, budget cuts).
- Lack of Stakeholder Involvement: Corrective actions developed solely by management without input from the technicians who perform the work often fail because they don’t account for the practical realities of the job.
Improvements and Best Practices (MEDA Principles)
- Systemic Focus (Ask ‘Why’ Five Times): Investigators must trace the causal chain of events back to the organisational and environmental factors that management controls. The “ask why five times” rule-of-thumb helps trace the issue to the correct level for a systemic fix, not just an individual one.
Example: Why was the procedure not used? Because it was stored in an inconvenient location. Why was it inconvenient? Because the new workflow didn’t account for accessibility…
- Non-Punitive and Trust-Based Investigation: The MEDA philosophy is built on the assumption that people want to do a good job. A non-punitive culture encourages technicians to be open and honest about contributing factors and to suggest solutions, which is vital to the development of effective corrective actions.
- Specific and Measurable Actions: Corrective actions should be specific, explaining precisely what is being changed (e.g., “Revise Section 4.5 of the AMM to include a photograph of the correct torque wrench setup,” instead of “Improve manual quality”).
- Involving the Frontline: Technicians who made the error or were involved should be encouraged to suggest Error Prevention Strategies (Section V of the MEDA form), making them part of the solution and increasing buy-in.
- Track and Follow-Up: A robust MEMS requires a mechanism for tracking, implementing, and verifying the effectiveness of all corrective actions to ensure the issue is truly resolved and does not reappear.
Strategies to Improve Procedures, Training, and Resource Allocation
These three areas represent key organisational factors directly linked to maintenance error and are the primary targets for systemic corrective actions.
Procedures (Work Instructions)
- Issue: Procedures are often poorly written, illogical, difficult to access (e.g., requiring long walks to a terminal), or not kept current with the latest configuration changes.
- Strategies:
- Human Factors Review: Have procedures reviewed by human factors specialists or, more practically, by a diverse group of technicians for clarity, flow, and practicality.
- Digital/Interactive Documentation: Implement electronic work cards and mobile access to manuals to improve accessibility at the point of work and allow for rich media (photos, videos) and interactive sign-offs/checklists.
- “Stop the Line” Feedback: Empower technicians to immediately flag confusing or incorrect procedures without fear of reprisal, and establish a rapid update process for essential documentation.
Training
- Issue: Training is often compliance-focused (“check-the-box”) or narrowly focused on technical skills, neglecting human factors principles and non-routine task performance.
- Strategies:
- Scenario-Based/Simulation Training: Use hands-on or virtual reality simulations to train for high-risk, low-frequency tasks and to manage error-prone situations such as interruptions, time pressure, or fatigue.
- Human Factors/Error Management Training: Move beyond basic initial training to integrate advanced concepts like the Skill-Rule-Knowledge (SRK) model of behaviour (understanding slips, lapses, and mistakes) into recurrent training for all maintenance staff.
- Competency-Based Assessment: Shift from time-in-service to demonstrated competency, ensuring technicians are proficient in both technical skills and error-reduction techniques before performing complex tasks unsupervised.
Resource Allocation
- Issue: Inadequate staffing, time pressure from unrealistic schedules, lack of proper tools, and ill-equipped facilities (e.g., poor lighting, noise) are frequent contributing factors in MEDA investigations.
- Strategies:
- Data-Driven Scheduling: Use historical data from MEMS/MEDA to accurately estimate task times, build in a buffer for unexpected issues, and support realistic maintenance schedules.
- Proactive Tool/Equipment Management: Ensure specialised tools are readily available, calibrated, and their locations are transparently tracked to reduce time lost to searching or improvising.
- Ergonomic Workplace Design: Invest in improving environmental factors in the hangar and work area, such as better lighting, reduced noise, and improved access to required systems, to reduce physical and cognitive strain.
Implementing Human Factors-Driven Solutions
Human factors is the scientific discipline concerned with the understanding of interactions among humans and other elements of a system. A HF-driven solution seeks to change working conditions, not the human condition.
Key Elements of HF-Driven Solutions
- Non-Punitive/Just Culture: This is foundational. It distinguishes between blameless error (slips, lapses), at-risk behaviour (deviations where the risks are not clearly understood or justified), and reckless behaviour (deliberate, high-risk disregard). Errors are treated as learning opportunities, while reckless acts are managed with disciplinary action.
- Error-Proofing (System Redundancy): Implementing layers of protection, or “hard barriers,” to prevent an error from occurring or to catch it before it has an adverse consequence.
- Examples: Checklists (a simple but effective barrier), mandated double-checks for critical tasks, colour-coding, or unique tool sets to prevent part mix-ups.
- Reducing Error-Provoking Factors (EPFs): Directing corrective actions at the most common EPFs identified in the MEDA checklist:
- Fatigue Management: Implementing controlled rest policies, managing shift handovers, and utilising bio-mathematical models to predict and mitigate fatigue risk.
- Distraction/Interruption Control: Designing “sterile cockpit” type rules for critical maintenance phases and using visual cues (e.g., vests, signs) to signal when a technician should not be interrupted.
- Workload and Staffing: Ensuring adequate staffing levels based on workload analysis, avoiding the overallocation of highly complex or safety-critical tasks to junior staff.
Balancing Safety, Cost, and Operational Efficiency
The central challenge for a successful MEMS is moving beyond the false choice between safety and operational goals. Safety is a prerequisite for efficiency and cost control. Errors are expensive, causing delays, costly rework, cancellations, and potentially catastrophic losses.
Strategies for Balance
By using the structure of MEDA to uncover the root causes of maintenance events, a MEMS transforms reactive incidents into proactive, systemic improvements that inherently improve safety while simultaneously boosting efficiency and lowering long-term operating costs by reducing costly errors and delays.
Next Steps
Sofema Aviation Services and Sofema Online deliver Maintenance Error Management System (MEMS) and Maintenance Event Decision Aid (MEDA) training as Classroom, Webinar and Online training. For details, please see the websites or email [email protected]
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MEDA, MEMS, SAS blogs, AviationSafety, ContinuousImprovement, AviationTraining, RegulatoryCompliance, HumanFactors, SafetyCulture, AviationMaintenance, MaintenanceErrorManagement, RootCauseAnalysis
