Evaluating Digital Spare Parts and Local On-Demand Manufacturing for the Saudi Aviation Sector: A Simulation-Based Decision Framework

Background: Aviation spare parts management faces unpredictable demand, long lead times, strict airworthiness requirements, and high inventory costs, which drive aircraft-on-ground events and operational disruption. Digital spare parts, enabled by digital warehousing and local on-demand manufacturing, offer a potential response, but no standardized framework exists for selecting items for digital warehousing in aviation. Methods: This study develops a modified Spare Parts Interchangeability Record framework incorporating digital readiness, manufacturability, and production-based lead times, coupled to a stochastic discrete-event simulation. Twenty candidate Airbus A320 components are screened, and three supply configurations are compared over a one-year horizon: physical warehousing with OEM procurement, fully digital warehousing with local production, and a hybrid strategy. Results: The hybrid configuration performs best. Relative to the baseline, total waiting time falls by 67.7%, demand-weighted aircraft-on-ground duration from 1089 to 316 h, operational cost by 19.7%, and transport-related emissions by 50%, while service level rises from 86.5% to 95.8%. A fully stockless configuration proves contingent on production capacity, leaving 32.3% of demand unserved at the capacity assumed; twenty simultaneous production slots are identified as the viability threshold. Conclusions: Technical suitability alone does not establish strategic viability. Results derive from simulation rather than field implementation.

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Journal
Logistics
Published
2026-09-24
DOI
https://doi.org/10.3390/logistics10100223
Primary Topic
Forecasting Techniques and Applications
Type
article
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article

Evaluating Digital Spare Parts and Local On-Demand Manufacturing for the Saudi Aviation Sector: A Simulation-Based Decision Framework

Abdelhakim Abdelhadi, Idriss El‐Thalji, Khalid Alotaibi
Logistics
Forecasting Techniques and Applications
article

Evaluating Digital Spare Parts and Local On-Demand Manufacturing for the Saudi Aviation Sector: A Simulation-Based Decision Framework

Abdelhakim Abdelhadi, Idriss El‐Thalji, Khalid Alotaibi
article en

Abstract

Background: Aviation spare parts management faces unpredictable demand, long lead times, strict airworthiness requirements, and high inventory costs, which drive aircraft-on-ground events and operational disruption. Digital spare parts, enabled by digital warehousing and local on-demand manufacturing, offer a potential response, but no standardized framework exists for selecting items for digital warehousing in aviation. Methods: This study develops a modified Spare Parts Interchangeability Record framework incorporating digital readiness, manufacturability, and production-based lead times, coupled to a stochastic discrete-event simulation. Twenty candidate Airbus A320 components are screened, and three supply configurations are compared over a one-year horizon: physical warehousing with OEM procurement, fully digital warehousing with local production, and a hybrid strategy. Results: The hybrid configuration performs best. Relative to the baseline, total waiting time falls by 67.7%, demand-weighted aircraft-on-ground duration from 1089 to 316 h, operational cost by 19.7%, and transport-related emissions by 50%, while service level rises from 86.5% to 95.8%. A fully stockless configuration proves contingent on production capacity, leaving 32.3% of demand unserved at the capacity assumed; twenty simultaneous production slots are identified as the viability threshold. Conclusions: Technical suitability alone does not establish strategic viability. Results derive from simulation rather than field implementation.

LogisticsVol. 10(10)
Prince Sultan University (SA)
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
Forecasting Techniques and Applications
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Evaluating Digital Spare Parts and Local On-Demand Manufacturing for the Saudi Aviation Sector: A Simulation-Based Decision Framework — Abdelhakim Abdelhadi, Idriss El‐Thalji, et al. · Logistics (2026) | TGRS Research Map | TGRS