Work

Classifying MRP Strategy of Aircraft Spare Parts Using Supervised Machine Learning

Year: 2024

Type: conference-paper

Abstract: Spare-parts provisioning strategy is crucial for airlines or Maintenance Repair Overhauls (MRO). The strategy is divided into multiple classes that refer to several criteria, then uses Material Requirements Planning (MRP) to run those strategies. However, classifying spare parts into a strategy is onerous and requires innovation. Therefore, we employ three algorithms: Decision Tree, Random Forest, and Support Vector Machine (SVM), and use spare parts and aircraft utilization data to classify the strategy and optimize spare parts provisioning of MRO over time. The results showed Random Forest performs best by accuracy, sensitivity, and specificity with a score of more than 97%.

Source: Procedia Computer Science

DOI: 10.1016/j.procs.2024.03.029

Authors: Nafiurridha, Achmad Choiruddin

Institution: Institut Teknologi Sepuluh Nopember

Language: English

Topic: Supply Chain and Inventory Management

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Institut Teknologi Sepuluh Nopember