The Dynamics of the Profit Margin in a Component Maintenance, Repair, and Overhaul (MRO) within the Aviation Industry: An Analytical Approach Using Gradient Boosting, Variable Clustering, and the Gini Index

Uslu N. Ş., BÜYÜKLÜ A. H.

Sustainability (Switzerland), cilt.16, sa.15, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 15
  • Basım Tarihi: 2024
  • Doi Numarası: 10.3390/su16156470
  • Dergi Adı: Sustainability (Switzerland)
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Aerospace Database, Agricultural & Environmental Science Database, CAB Abstracts, Communication Abstracts, Food Science & Technology Abstracts, Geobase, INSPEC, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: aircraft, aircraft components, aviation, cluster analysis, data analytics, data science, Gini index, gradient boosting, interactive grouping, maintenance, repair, and overhaul, MRO, profit
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

This study focuses on the dynamics of the profit margin within the aviation MRO industry, using operational data from a small and medium-sized enterprise (SME) MRO company between 2013 and 2021. Especially in SME MROs, profit margin analysis provides an advantage in competing with the large companies that dominate the industry. Therefore, the operational data were prepared for analysis to identify the variables related to the profit margin. This study’s data cleaning and transformation processes can serve as a guideline for similarly sized companies. The research aims to address the complex relationships among the factors influencing profit margins in this industry. The objective is to utilise these factors in making strategic decisions to increase the profit margin of an SME MRO company. Applying gradient boosting algorithms as the analytical framework should allow identifying the correct relationships between the profit margin and input variables according to time for the SME MRO company. Another important aspect of this study is to increase the accuracy of the gradient boosting model by utilising the interactive grouping methodology. The variable selection was performed by using the Gini indexes of the variables using interactive grouping as a criterion in selecting the variables to be included in the model. After the data cleaning, transformation, and selection, the input variables for the gradient boosting model were Part Description, Parts Billed Current (part cost), Labour Billed Current (labour cost), Diff Shipping Entry (turnaround time (TAT)), Diff Quote Entry (time to quotation (TTQ)), Manager, Department, and Status. In this study, the profitability model indicates that the SME MRO company should initially focus on part numbers and the departments, secondly on standardisation of and expertise in preferred workshop units, and lastly, on highly qualified and effective technical department leaders and increasing labour. The aviation industry emerges as a sector that requires such analytical studies. It is hoped that the study will serve as a foundational work for SME MRO companies in the aviation industry.