The use of SPC tools for a preliminary assessment of an aero engines' maintenance process and prioritisation of aero engines' faults

The purpose of this paper is to provide a relatively straightforward approach of implementing standard statistical process control (SPC) concepts while instituting problem‐solving intonations in aero‐engine maintenance processes.

The inspection workflow approach is presented in order to aid in collecting and monitoring critical aero‐engine data. Observed defects are categorized according to a Pareto analysis assisted by a cause‐and‐effect diagram. A binomial process capability analysis is performed on nonconforming aero‐engines based on operating curves produced specifically for this case study. The time frame for experimental analysis is reflected in a span of six months.

It is found that a significant number of aero‐engines may be benefited by entering a more progressive maintenance program relying on predictive maintenance on the way to establishing a more effective Total Productive Maintenance scheme.

The case study showcases an approach to aero‐engine rejection statistical rates by accepting the fact that maintenance process may not be viewed as a process that may be limited to constant sampling.

For a long time, total quality management (TQM) tools have been deeply rooted in design, manufacturing and assembling of airliners and jet fighters alike. However, a comprehensive study focusing on the maintenance function of such complex machines may prove worthwhile now that an unstable global economy may prohibit extensive replacement of aging flying fleets.

With the lack of a prior practical unfolding in the field of genuine aero‐engine maintenance, this presentation aims to fill in the gap for engine rejection treatment. The variant operating curve notion introduced in the text is also a unique idea espoused for variable sampling situations when a binomial distribution is adopted.