Maintenance Error Decision Aid (MEDA)

Maintenance Error Decision Aid (MEDA) is a tool for investigating the factors that contribute to maintenance errors. The MEDA process provides thorough and consistent investigations, determining factors that lead to an event and making improvements to reduce the likelihood of future incidents. Maintenance errors cost millions of dollars each year in rework, on-time performance and lost revenue, and have the potential to present hazards to safety.

Boeing developed the MEDA process to assist maintenance organisations identify why these events occur and how to prevent them in the future. The MEDA philosophy is based on three assumptions: People want to do the best job possible and do not make errors intentionally. A series of factors is likely to contribute to an error.

Most contributory factors to an error can be managed. The findings of a particular error investigation often have much wider significance for the occurrence of errors generally. Addressing just some of the identified factors will probably significantly reduce the likelihood of the error recurring. MEDA involves the employees close to an error in the investigation and helps to establish how to manage the issues. Processes can be changed, procedures improved or corrected, facilities enhanced and best practices shared.

Objectives

Following the course, delegates will be able to:

• Identify the responsibilities of a maintenance error investigator
• Understand the process to for implementation of MEDA
• Identify the contributory factors of an event, in order to make the system resistant to similar errors
• Perform effective maintenance error investigations
• Contribute to an organisational culture of error reduction
• Use effective interview techniques
• Confidently manage challenging situations
• Comply with MEMS requirements of EASA Pt 145 & CAP562

MEDA Course Syllabus

• Role and responsibilities of a MEDA investigator
• Root Cause Analysis
• Using the MEDA tool effectively
• Investigation & interview skills
• Report writing
• Trend analysis
• Linking MEDA with SMS and human factors