Aircraft Maintenance, Repair, and Overhaul (MRO) operations are highly complex, involving coordination among multiple stakeholders including airlines, MRO providers, OEMs, and regulatory authorities. A significant challenge in this space is managing unplanned events such as Aircraft on Ground (AOG) conditions, where delays can lead to major financial losses to airlines and safety risks. Engineers must quickly diagnose the damage, evaluate compliance against regulatory limits, coordinate with OEMs, and make critical decisions—all while navigating a fragmented ecosystem of disconnected systems, diverse document types, and time-sensitive processes. This paper presents a real-world, intelligent MRO solution that addresses these challenges through the use of Agentic AI and context engineering. The system is designed to automate and augment key MRO workflows such as damage detection, repair pathway selection, compliance verification, and supplier coordination. At its core, the solution is

Abburu, Sunitha, G.V.V., Ravi Kumar, Poovalingam, Sundaresan, Vaderahobli, Devaraja Holla

Retrofit Vibration Mitigation of Launch Vehicle Structures Using Thin Viscoelastic Coatings: Acoustic and Modal Study

2026-26-0736

To be published on 06/01/2026

Acoustic-induced vibrations pose a significant risk to launch vehicle hardware and payload reliability during critical phases such as lift-off and transonic phase. Reducing such vibrations is especially challenging when the hardware has already been fabricated, limiting the possibility of structural redesign. This study demonstrates a practical post-fabrication solution using a thin viscoelastic polymer coating applied externally to fully assembled hardware. Comprehensive evaluations were conducted using both acoustic testing and Experimental Modal Analysis (EMA) before and after coating application. During acoustic test, a substantial decrease in structure response from 150Hz to 2000Hz, with a reduction of approximately 50% in the grms values was observed for the coated structure demonstrating significant vibration mitigation over a wide frequency range. In contrast, EMA measurements using impact excitation revealed that the response transfer functions did not show a significant

Avirah, Nohin K, Panda, Ajay Kumar, Shaikh, Altafhusen

Mitigating Cracking in COP Optics through Annealing and Step-Torquing

2026-26-0764

To be published on 06/01/2026

Polymeric optical materials such as Cyclo Olefin Polymer (COP) are adopted in aerospace lighting systems due to their excellent optical clarity, dimensional stability, moldability and weight saving advantages over glass. However, their relatively low toughness and the presence of residual molding stress make them prone to crack initiation during mechanical fastening. During its installation, crack formation was consistently observed around self-tapping screw interfaces, raising concerns over reliability, maintainability, and compliance with durability requirements. A structured Design of Experiments (DOE) was performed to identify root causes and evaluate potential mitigation methods. The investigation revealed that residual stresses in the COP material, combined with localized stress concentrations during screw tightening, were the primary drivers of crack initiation. Two complementary process improvements were identified and validated as part of mitigation plan: (i) annealing of the

S, Nikhil, Singh, Abhimanyu Kumar, Katageri, Praveen, SP, Pradeep, Chandra, Praveen

Non-Intrusive Fatigue Detection for Pilots

2026-26-0793

To be published on 06/01/2026

Pilot fatigue represents a critical concern in aviation safety, as it can significantly impair cognitive functions, decision-making abilities, and reaction times. In addition to decreasing performance, in-flight chronic fatigue has negative long-term health effects. Possible causes of fatigue include sleep loss, extended time awake, circadian phase irregularities and workload. Conventionally, the risk due to fatigue in aerospace is reduced by flight time limits and controlled rest requirements. Despite regulations limiting flight time and enabling optimal rostering, fatigue cannot be prevented completely. Hence, there is need to detect pilot fatigue in real time. There is ongoing research to detect pilot fatigue using devices that can capture Electroencephalogram (EEG) and Electrocardiogram (ECG). Though these devices have high fidelity, they are intrusive and can limit pilot activity. This limitation could potentially be overcome by non-intrusive devices such as a smart watch/wrist

Nyamagoudar, Vinayak, P R, Namratha, Ramachandran, Venkataramani

Integrating Human factors and Predictive Modeling for Enhanced Aviation Safety: A Data - Driven Approach to Risk Mitigation and System Design

2026-26-0795

To be published on 06/01/2026

This study presents a data-driven approach for strengthening aviation safety by integrating human factors assessment with modern predictive modeling techniques. The work focuses on understanding how human performance, operational conditions, and system-level interactions collectively influence safety risk, and how these interactions can be quantified to support improved design and decision-making. Unlike previous studies that address human factors or predictive modeling in isolation, this research offers a unified framework that links causal human factors indicators with statistical modeling, feature extraction, and machine learning based risk estimation. The novelty of this work lies in the structured pipeline that transforms raw categorical and narrative human factors information into measurable predictors that can be analyzed using structural modeling and machine learning. The methodology includes data preparation, dimensionality reduction, latent pattern discovery, dependence

Valiyaparambil, Praveen

Risk-Driven Program Management Framework for Avionics Development: Integration of Safety, Certification, and Cybersecurity Standards

2026-26-0716

To be published on 06/01/2026

Modern avionics programs contend with escalating complexity driven by concurrent safety certification, cybersecurity compliance, and multi-standard regulatory demands. Traditional program management approaches treat risk management as a parallel support function rather than a central governance mechanism, resulting in reactive responses that fail to prevent cost and schedule erosion. This paper introduces the Risk-Driven Program Management Framework (RD-PMF), an eight-phase governance model that embeds quantitative risk assessment, standards-risk mapping across DO-178C, DO-326A, ARP4754A, and ARP4761A, real-time digital dashboards, and earned value management within core program decision-making. The framework integrates probabilistic schedule analysis using Monte Carlo simulation with continuous risk exposure monitoring to enable proactive, data-driven governance. RD-PMF is demonstrated through a representative avionics program scenario modelled on a flight control system development

Rahul, Saurabh, Benikireddy, Raghunatha

AI-Led Sustainability Strategy: Driving Product Value from Birth to Disposal

2026-26-0781

To be published on 06/01/2026

Aerospace products operate within highly complex, safety-critical environments and endure extended lifecycles, often spanning decades. Sustaining their operational value requires rigorous management of Safety, Reliability, and Availability (SRA), while global Environmental, Social, and Governance (ESG) mandates demand parallel progress toward sustainability goals. This paper introduces an AI-driven strategy that integrates these dual imperatives—Sustenance Management and Sustainability Management—within a unified Product Lifecycle (PLC) framework. The proposed approach leverages Artificial Intelligence across five PLC phases: Generative Design, Detailed Design & Verification, Manufacturing & Industrialization, Operations & Maintenance, and End-of-Life Circularity. Anchored by a certified Digital Thread, this framework ensures seamless, auditable data flow from concept to disposal. Using Life-Limiting Parts (LLPs)—such as high-stress turbine discs—as a case study, the paper demonstrates

Srinivasan, Karthik, G.V.V., Ravi Kumar, Vaderahobli, Devaraja Holla, Bhate, Ujwal, Veluri, Sastry

Agentic Digital Thread for Managing the Non-Conformities in Manufacturing of Aerospace Products

2026-26-0763

To be published on 06/01/2026

Aerospace manufacturing operates within an intricate ecosystem where quality, compliance and traceability are critical to success. Conventional digital thread frameworks provide connectivity but remain largely passive, lacking the intelligence to autonomously manage complex non-conformities across the product lifecycle. This paper introduces an Agentic Digital Thread powered by Agentic AI, designed to transform non-conformity management into an adaptive, self-orchestrating system that actively drives decision-making and corrective actions [1, 4]. The proposed architecture employs a Master Agent to coordinate workflows and maintain end-to-end data continuity, while specialized Agents autonomously manage domain-specific tasks. In the pre-manufacturing phase, these agents proactively validate requirements, material conformity and process planning through integration with PLM, MES, ERP, QMS and supplier systems. In the post-manufacturing phase, the framework extends to concession

Veluri, Sastry, Gopala Krishnan, Kannan

Predictive Obsolescence Management

2026-26-0780

To be published on 06/01/2026

In the field of Aerospace, which has a long Life-Cycle process [20-30Years], Component Obsolescence has become a major problem as it prevents Maintenance & sustenance of a product with committed life-cycle period. Obsolescence Management plays a vital role by deriving strategic plans on proactive obsolescence where the system needs to be supported for several decades. This abstract analyzes the obsolescence challenges in the Aviation industry especially in Avionics System impacted by component obsolescence and present the possible proactive obsolescence management in terms of Engineering, Technology, and business/cost elements. The Obsolescence problem cannot be avoided but the impact of obsolescence and mitigate the risk can be minimized by planning and managing response. The obsolescence risk assessment for the Bill Of Materials (BOM) is a paramount activity to manage obsolescence proactively and cost-effectively. Digital Transformation of analyzing the component obsolescence status

Dharmananyala, Rohith, Munirathnam, Krishna, Marokeyfrancis, Joisyjose, Sadashivaiah, Nagesh, Kondamari, Harshitha

Integrating Formal Methods into Model Based Systems Engineering to Mitigate Requirement Escapes

2026-26-0712

To be published on 06/01/2026

The aerospace industry is undergoing a significant digital transformation in the way system requirements are defined, communicated, and managed. Major OEMs are moving towards fully model-based development processes, with plans to deliver requirements exclusively in the form of models. It is no longer sufficient to manage requirements using traditional document-based approaches; instead, organizations must adopt tools and processes that enable the consumption, interpretation, and implementation of model-based requirements. However, MBSE itself does not ensure that the requirements defined within the model are complete or consistent. Without rigorous validation techniques, even well-structured models can carry forward poorly defined or conflicting requirements — leading to errors that propagate throughout the development lifecycle. This work proposes an approach that integrates formal methods into MBSE workflows by enabling completeness and consistency checks of SysML-based requirements

Gupta, Chandan, Nakkeeran, Rupashree

Hybrid Digital Twin for Aero-Engine Bearing Prognostics: A Physics-Informed Machine Learning Approach to RUL Prediction

2026-26-0718

To be published on 06/01/2026

Unscheduled maintenance due to the failure of critical components, such as aero-engine rolling element bearings, is a leading cause of costly Aircraft-on-Ground (AOG) events; consequently, current time-based maintenance practices are inefficient and prone to risk. This paper develops a resource-efficient Hybrid Digital Twin (HDT) model for an engine bearing, focusing on the dynamic prediction of spall growth due to Rolling Contact Fatigue (RCF), thereby enabling a condition-based maintenance paradigm. The HDT architecture integrates two core models: (1) a physics-informed model that uses established life and fatigue theory to define initial degradation thresholds, and (2) a data-driven Recurrent Neural Network (RNN), specifically a Long Short-Term Memory (LSTM) network, for dynamic degradation rate modeling. The methodology utilizes a Monte Carlo simulation coupled with RCF progression equations to generate a large, high-fidelity synthetic run-to-failure dataset under varying

Mohamed, Abbas

Wear Resilience Characteristics of Silicon Nitride Strengthened AZ31 Magnesium Composite

2026-26-0740

To be published on 06/01/2026

To develop magnesium matrix composites, ceramic silicon nitride (Si3N4) particles are added to the magnesium (AZ31) matrix at 2 wt.%. The composite is produced via disintegrated melt deposition vacuum-stir-casting procedure. Microstructural studies reveal the presence of Si3N4 particles and their uniform spreading. An L9 orthogonal array, planned using Taguchi’s experimental design, is selected for three wear parameters; axial load (AL), rotational speed (RS), and time duration (TD) with trials as per the G99 standard in the pin-on-disc apparatus to assess the wear resilient of the composite. Experimental results show an increase in axial stress, and wear loss (WL) increases dramatically. Because the area of contact shrinks as RS increases, WL diminishes dramatically. When the AL is low, the friction coefficient (CoF) increases, and when the AL is large, CoF drops. When the RS is increased, CoF decreases. To optimize multiple responses effectively, the TOPSIS (Technique for Order

Senthilkumar, N., Dhinakar Raj, C K

Effect of Strap-On Geometry on the Aerodynamics of Multibody Launch Vehicle

2026-26-0727

To be published on 06/01/2026

Strap-on boosters play a crucial role in heavy launch vehicles by providing additional liftoff thrust without major changes to the baseline design, enabling launch with existing propulsion systems. However, strap-on boosters introduce additional pressure drag and alter the overall aerodynamics of the vehicle. While efforts have been previously made to derive empirical relationships to predict the aerodynamics of different strap-on configurations, most are case-specific and primarily limited to estimating drag coefficients (CD). The present study focuses on geometric parameters of strap-on such as length, diameter and radial gap between strap-on and core. The results are used to derive an empirical relationship which can be applied during preliminary design stage of a launch vehicle to predict axial force coefficient (CA), normal force coefficient (CN) and pitching moment coefficient (CPM), which are required for mission design and structural load estimation. In the current study

Muraleedharan, Archana P., G, Ramana Bharathi, S, Gnanasekar

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