Developing a non-routine maintenance load forecasting procedure in maintenance, repair and overhaul (MRO) XYZ company: A case study of B737NG aircraft

Abstract

Turn Around Time (TAT) is one of the most important performance indicators in a Maintenance, Repair, and Overhaul (MRO) company. MRO companies need a high percentage of on-time TAT to compete in the industry. In 2019, there is a 29% difference between the planned and the actual TAT in MRO XYZ. Based on observations in MRO XYZ, there is no planning to perform non-routine maintenance. 54% of the total maintenance loads is a non-routine maintenance, therefore, it needs to be planned. The first step of the research is to identify routine maintenance tasks that dominate the non-routine maintenance loads based on ATA Chapter and CAMP Number using Pareto Analysis. The next step is to develop a procedure which determines the variables and the mathematical model to estimate the Non-Routine Ratio (NRR) workloads. The last step is to implement the procedure to obtain the NRR estimation model, which is also as the validation of the developed procedure. Several routine maintenance tasks dominate Non-routine maintenance loads are categorized by ATA Chapter, CAMP Number, and task types. Dominant ATA Chapters are ATA 53, 25, and 57. Dominant CAMP numbers are 53-140-00, 53-800-00, and 53-866-00. Dominant task categories are DVI for the system, internal GVI for structure, and external inspection for zonal. The NRR forecasting model for B737NG C-Check is composed of C-Check number, aircraft’s age, the ratio of ATA 53, the ratio of ATA 25, and the ratio of ATA 57. The NRR forecast model can be improved by adding some variables, such as Flight Hours (FH) and Flight Cycles (FC).