Aircraft Reliability Engineering - 3 steps to decrease maintenance turnaround time
With the introduction of the MSG-3 maintenance philosophy, reliability monitoring became mandated for airlines in order to monitor the effectiveness of their approved maintenance programs. Today it has become common practice to have a role within the airline engineering department that is tasked to satisfy this regulatory requirement. So like clockwork, on a monthly basis every airline engineering department creates their monthly reliability report, holds a team meeting to go over the report and then afterwards go their separate ways in order to support troubleshooting or check if any new AD’s have come out.
In the last couple of years, we have seen multiple different airline engineering teams, across different continents and ranging from flag carriers, low-costs airlines, regional airlines, ACMI operators, cargo airlines and holiday charters. From this experience we have encountered two distinct scenarios on how airline engineering teams approach reliability management:
1. The reliability engineer as the engineering department’s own BI specialist
2. The maintenance program engineer does reliability monitoring as a side-job
The reliability engineer as the engineering department’s own BI specialist
Typically, the reliability engineer is one of the younger engineers on the team and knows its way around excel. This comes in well because he/she is tasked with retrieving all required information from various systems and departments in order to create a monthly reliability report that is intended to drive further improvements to the fleet and its organization. Most of them have the skills to establish well visualized dashboards. Adding to this mix the fact that on a day-to-day bases the reliability engineer is the person the engineering manager goes to in order to get answers to any KPI driven insight he might have as a manager.
The main effect of this approach is that a lot of reporting and dashboarding is made available in the engineering team and are used to drive actions to ensure issues remain under their indicated threshold KPI’s. For example:
As long as technical dispatch reliability remains somewhat within the boundaries of set targets, all is fine
If deferred defects are not exceeding target limits, all is fine
As a result, you see reliability engineering becoming more of an internal management KPI driven function rather than a function to continuously improve the actual reliability of the fleet.
The maintenance program engineer does reliability as a side-job
This scenario is typically encountered when the size of the fleet remains below 30 aircraft. An engineer within the engineering department is responsible for the managing the maintenance program of the fleet and as such is also tasked with creating monthly reliability statistics on items such as Technical Dispatch Reliability, Task card findings, Pilot complaints, Cabin defects, maintenance reports and unscheduled removals.
Typically, we see that this philosophy is paired with fairly new fleets of aircraft, hence real major reliability problems (other than the usual teething problems) have not really emerged. However, effectively reliability engineering in such a scenario has become a theoretical exercise to satisfy regulatory requirements and auditor questions once asked.
The ideal situation - automation of reliability reporting to focus on decreasing maintenance turnaround time
In both scenarios mentioned above, still much time is spend on the actual creation of the reliability report. However, the ideal situation would be that reliability engineers focus more on technical investigations for system or component improvements to decrease maintenance downtime rather than information gathering and building their own graphs. Latest technological development and the availability of different digital analytics platform enable the reliability engineer to follow this path and focus on the improvements that can decrease maintenance downtime.
In order to get to this point, below we highlight three steps that can be taken by engineering managers:
Step number 1
Firstly, is to eliminate the need of anyone in the engineering department being needed to collect data and create the actual reliability report. This is a process that can be automated by utilizing a reliability analytics software that is designed for aviation and follows the ATA Spec2000 Chapter 11 standard, such as EXSYN's AVILYTICS solution. This already greatly improves things as no valuable time is lost on data collection and report creation.
Step number 2
Secondly, is to make sure that the reliability engineer is equipped to perform technical investigations into items that are being flagged by reliability analysis. Think of:
1. Recurring defects
2. Component MTBUR’s
3. Maintenance task escalations / de-escalations
4. Defect root-cause analysis
Step number 3
Then ultimately, and as a third step, the reliability engineer can work with applicable system engineers or maintenance managers to establish engineering orders or maintenance policy changes that will improve aspects such as maintenance turnaround time and unscheduled aircraft defects and thereby ultimately improving fleet availability thru improved Technical Dispatch Reliability and shorter scheduled maintenance ground times.
How EXSYN can help
EXSYN's team of aircraft data and aviation experts utilize a proven framework and methodology for adoption of predictive analytics in aviation. It has been applied to numerous fleets and aircraft and includes:
EXSYN’s pre-build AVILYTICS environment of analysis modules, widgets, formulas and algorithms on a wide range of ATA chapters and components
Workshops to identify the specific maintenance complaints to be monitored for each fleet operated by your airline
Implementation of identified complaints per aircraft type and registration into the AVILYTICS environment. Including data mining, validation and user interface design.
Native integration of the AVILYTICS modules in your own platform or hosting in the myEXSYN.com digital environment in case your airline does not have a data warehouse yet
Training of identified user groups
Adoption workshops to support successful day-to-day usage of the predictive analytical techniques and business models
Machine Learning to identify future potential maintenance complaints to be monitored
Ongoing software maintenance support for modules implemented