AI-Driven Collaborative Maintenance Strategies for Repairable Parts: A Cost-Effective Solution for Pakistan’s Aviation Sector

Sajid Nazir ()
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Sajid Nazir: Lappeenranta-Lahti University Technology

A chapter in Artificial Humans, 2026, pp 203-216 from Springer

Abstract: Abstract The aviation industry in Pakistan is facing challenges due to decentralized maintenance practices. Currently, each airline independently interacts with the repair agencies for unserviceable (U/S) rotable parts repairing, even having the same fleets, which results in inefficiencies, increased costs, and affecting the environment sustainability. This study examines a collaborative innovation framework which aims to deal with these challenges via a centralized, AI-driven system that streamlines the repair orders, enhances transportation efficiency, and incorporates predictive maintenance characteristics. The findings indicate a potential for the Pakistani aviation sector to enhance its competitiveness in accordance with global sustainability trends and collaborative innovation practices. The proposed model allows cost savings using bulk negotiations and economies of scale, reduces the transportation costs through consolidated shipments, and decreases the carbon emissions, thereby promoting sustainability in the aviation sector of Pakistan.

Keywords: Collaborative innovation; Aviation sector; Collaborative practices; AI-enabled systems; Digitalization; Sustainability (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:fuobcp:978-3-032-06604-6_12

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DOI: 10.1007/978-3-032-06604-6_12

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