Browse Topic: Maintenance and Aftermarket

Items (10,153)
Find
Dynamic Stiffness Prediction in Cracked Cantilever Beams Using Enhanced ANN Techniques2026-28-0050To be published on 02/01/2026
This research paper presents an in-depth investigation into the application of Artificial Neural Networks (ANN) for predicting the dynamic stiffness characteristics of cantilever beams affected by cracks of varying depths and positions. Structural failure due to vibration remains a critical concern, and this study focuses on how crack-induced changes in modal stiffness compromise structural reliability. A significant research gap identified in previous studies is the limited consideration of crack location; this work addresses that gap by analyzing how both crack depth and position influence the natural frequency of the beam. Using modal analysis on cantilever beams with identical dimensions but different crack configurations, it was observed that deeper cracks and cracks near the fixed support led to a marked reduction in natural frequency, making the structure more vulnerable to resonance. Cracks located at the free end, however, showed negligible impact. To model and predict these
SB, Harshini, Rajkumar, Manjari, R, Krithika, K, Anusha, K, Divya, Bhaskara Rao, Lokavarapu
Parameter Selection Strategies for High-Performance WAAM Structures in Automotive Engineering2026-28-0033To be published on 02/01/2026
Wire Arc Additive Manufacturing (WAAM) has gained traction as an advanced fabrication technique for producing large, structurally demanding components in the automotive industry. Achieving high-performance WAAM structures requires precise control and selection of key process parameters, which directly influence mechanical strength, dimensional accuracy, and surface quality. This study investigates the effect of critical process variables—including wire feed rate, travel speed, current, voltage, and inter-layer cooling time—on the structural integrity of WAAM-fabricated components designed for automotive use. A systematic experimental approach, supported by statistical modeling and optimization tools, was employed to identify parameter combinations that yield optimal results. The outcomes demonstrate improved microstructural uniformity, reduced residual stresses, and enhanced tensile properties in the fabricated parts. The findings serve as a foundation for developing robust parameter
V, Aravind
Intelligent Driver Behavior Analytics for Enhanced Road Safety2026-28-0054To be published on 02/01/2026
The present work on Intelligent Driver Behavior Analytics System that monitors and analyzes road users to ensure road safety and regulatory compliance, the system developed by using machine learning algorithms with the help of Raspberry Pi micro controller. It is said that most road accidents are caused by driver incompetency, yet, dangerous driving behavior is hard to detect on the road; this system monitors dangerous driving and other related behaviors that cause road accidents as well as contribute to noise pollution. It also alerts vehicle pauses on high-risk areas like road edges and also compares the routes planned to routes traveled on the GPS to alert any route slippage. Drivers, fleet managers and fleet operators get real-time feedback, and they are encouraged to take corrective action immediately. The system is expandable and is applicable to transportation agencies, public safety organizations and individuals who own vehicles and need to hone road safety and performance
Prasad, Gvl
A Scalable ArTOP-Based In-House Toolchain for Automated AUTOSAR Configuration2026-26-0682To be published on 01/16/2026
The rising software complexity in Automotive industry demands reusable, hardware-agnostic development frameworks. AUTOSAR (Automotive Open System Architecture) provides a standardized, scalable ECU software architecture but cost-effective tooling and modern workflows are critical for broad adoption and competitiveness. One such area is for AUTOSAR configuration and authoring of Autosar architecture. Current solutions include commercial offerings which are often built on top of ARTOP (ArTOP is an eclipse-based ecosystem maintained by AUTOSAR consortium) and open-source python implementations. Commercial tools are prohibitive in cost, have complicated development workflows, are difficult to automate and lack quick integration with other tools. Python-based solutions are often community driven with small developer teams and face many challenges. These tools are not mature enough, have staggered development, security concerns, liability issues, lack of approvals etc. These libraries do not
Daware, Kartik, Garg, Mudit, Pasupuleti, Raju
Cybersecurity threats for connected passenger EV Buses of state transport units in India.2026-26-0610To be published on 01/16/2026
There are several chances to enhance fleet management, passenger safety, and operational efficiency by integrating connected technology into electric passenger buses, especially in Indian state transport agencies. But this connectivity also brings with it a fresh set of cybersecurity threats that might jeopardize these cars' dependability and security. With an emphasis on India's state-run bus fleets, this study examines the cybersecurity risks unique to connected electric vehicles (EVs) utilized for public transportation. Vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and fleet management communication systems are examined for key vulnerabilities. Potential attack vectors are highlighted, including data interception, GPS spoofing, unauthorized access, and cyberattacks on charging stations. We also look at how these cybersecurity threats affect public safety, operational disruptions, and passenger privacy. This paper also assesses the difficulties Indian state transport
Mokhare, Devendra Ashok
AI-powered intelligent cognitive lens for driver monitoring for safe transportation and increased fleet efficiency2026-26-0634To be published on 01/16/2026
The rapid evolution of intelligent transportation systems has made drivers’ attentiveness and adherence to safety protocols more critical than ever. Traditional monitoring solutions often lack the adaptability to detect subtle behavioral changes in real time. This paper presents an advanced AI-powered Driver Monitoring System designed to continuously assess driver behavior, fatigue, distractions, and emotional state across various driving conditions. By providing real-time alerts and insights to vehicle owners, fleet operators, and safety personnel, the system significantly enhances road safety. The system integrates lightweight AI/ML algorithms, image processing techniques, perception models, and rule-based engines to deliver a comprehensive monitoring solution for multiple transportation modes, including automotive, rail, aerospace, and off-highway vehicles. Optimized for edge devices, the models ensure real-time processing with minimal computational overhead. Alerts are communicated
Chikhale, Shraddha, Sing, Sandip, Hivarkar, Umesh, Mardhekar, Amogh
Rear Wiper Motor with Nozzle Integration for Improved wiping performance and Perceived Quality2026-26-0600To be published on 01/16/2026
In the current modern days of driving, rear wiping performance plays a crucial role in safe driving. This study focuses on improving the rear wiping with add on benefits like improved BSR performance, cost saving and perceived quality. This new concept has the rear wiper motor assembly which accommodates the nozzle also thereby making it a single unified assembly with reduced system complexity. This concept eliminates the complex hose routing of washer system for rear wiping which is usually packaged at spoiler or HMSL. It also helps in improved spray coverage and reduced dry wiping which in turn enhances system reliability with clean & quiet operation. This integrated nozzle concept is much more compact than the available products in the market with minimum number of end items. Also, this design comes with non-return valve which ensures there is no delay in the spray execution. And it improves the cleaning efficiency by maintaining consistent fluid pressure. This concept comes with
Dhage, Prashant, K, NAGARAJAN, G, Sabari Rajan
Optimization of Battery Mixing Strategies to Enhance Electric Vehicle Performance and Efficiency2026-26-0209To be published on 01/16/2026
Fleet operators increasingly contend with a patchwork of battery‑pack generations that remain electro‑chemically compatible yet differ markedly in capacity, internal resistance and residual life. Conventional “like‑for‑like” replacement policies oblige service providers to retain costly legacy inventories or to install brand‑new packs in ageing vehicles—both scenarios inflating warranty exposure and material waste. Deploying a rational mixing strategy for packs of different vintages therefore offers a compelling path to lower costs and improve sustainability, but industry‑wide guidance is limited and confidence in performance impacts remains low. This paper presents an optimisation‑driven framework that determines when and how heterogeneous packs can be paired at the moment of integration while maintaining vehicle performance targets and minimising life‑cycle cost. The methodology combines: a physics‑based electro‑thermal performance model parameterised for discrete state‑of‑health
Nair, Sandeep R., Ravichandran, Balu Prashanth, Hallberg, Linus
Auto Braking system for preventing commercial vehicle overloading.2026-26-0032To be published on 01/16/2026
Overloading in commercial vehicles is a widespread issue that creates serious safety, operational, and regulatory concerns. Excessive loads can result in mechanical breakdowns, diminished braking performance, accelerated tire wear, and a higher likelihood of accidents, posing risks to drivers and other road users. Moreover, overloading accelerates road deterioration and increases infrastructure maintenance costs. To tackle this pressing problem, this study introduces a novel integrated system that merges advanced load-sensing technology with the vehicle's braking system. The system utilizes high-precision sensors placed at key locations, such as the suspension or axle, to monitor the vehicle's load in real time. These sensors send data to a central control unit, which triggers the braking mechanism if the load surpasses a predetermined safety limit. Importantly, the braking system activates only when the vehicle is stationary, ensuring it does not disrupt normal driving operations. The
RAJ, AMRITESH, Pujari, Sachin, Londhe, Mahesh, Shirke, Sumeet, Shinde, Akshay
System-Level Simulation to Design a Hydrogen Powered Refuse Collection Vehicle Based on Real-World Fleet Operational Data2026-26-0399To be published on 01/16/2026
This study, addresses one of the challenges in the energy transition of heavy-duty vehicles by converting a diesel Refuse Collection Vehicle (RCV) into a hydrogen-powered prototype. The research is part of the VeH2Dem project funded by NextGenerationEU and focuses on dimensioning the complete hydrogen propulsion system for a RCV, including the energy storage capacity, without compromising payload or operational functionality. The development of the propulsion system was based on a comprehensive analysis of operational data extracted from fleet management systems, complemented by detailed instrumental monitoring of various collection routes. This methodology ensured that the prototype maintained performance equivalent to the original internal combustion engine vehicle across all evaluated scenarios. The vehicle performance objectives were established following a comparative analysis with solutions currently available in the RCV market, incorporating statistical analyses to ensure
Cano, Pablo, Barrio, Roberto, Roche, Marina, de-Lima, Daniela, Batista, Sara, Bertolí, Xavier
EV Powertrain Systems Diagnostics & Prognostics utilizing AI & ML (LLM) based approach2026-26-0664To be published on 01/16/2026
This study introduces a novel Large Language Model (LLM)-driven approach for comprehensive diagnosis and prognostics of vehicle faults, leveraging Diagnostic Trouble Codes (DTCs) in line with industry-standard automation protocols. The proposed model represents a significant advancement in automotive diagnostics by not only identifying fault codes but also reasoning through the root causes behind them, thereby enhancing fault interpretability and maintenance efficiency. The LLM is trained on extensive service manuals, sensor datasets, historical fault logs, and OEM-specific DTC definitions, enabling context-aware understanding and correlation of faults. Analytical validation has been performed using real-world vehicle datasets from multi-brand platforms, demonstrating the model’s ability to detect complex fault chains and accurately predict probable root causes. By utilizing time series based projection of vehicle pattern, model could also predict the potential future faults basis the
Pandey, Suchit, Joshi, Pawan, KONDHARE, MANISH, CH, Sri Ram, Gajbhiye, Abhishek, S, Adm Akhinlal
Dog Clutch Engagement Probability Simulation for Heavy-Duty Automated Mechanical Transmissions2026-26-0437To be published on 01/16/2026
This study presents a simulation-based approach to estimate the dog clutch engagement probability maps under different vehicle operating conditions. The developed probability function incorporates multiple critical parameters including initial speed differential between engaging components, application of countershaft brake, dog tooth quantity, friction coefficients at tooth interfaces, applied actuation force, dog tooth geometry, and component inertia. Using MATLAB and Simulink, comprehensive simulation models were developed to analyse engagement dynamics and produce detailed probability maps at different vehicle speeds, effectively outlining optimal operational zones for successful engagement while identifying critical regions prone to tooth clash and engagement failure. The effect of tooth geometry on engagement probability has been investigated using simulation model results. The resulting engagement maps serve as valuable diagnostic tools for identifying potential system
Khan, Mohammad Adeeb, KHAN, Dr. NURUZZAMA MEHADI, Koona, Rammohan
A Centralized Framework for Sustaining Safety-Critical Vehicle Systems Through Periodic Servicing2026-26-0003To be published on 01/16/2026
As vehicles are becoming more complex, maintaining the effectiveness of safety critical systems like adaptive cruise control, lane keep assist, electronic breaking and airbag deployment extends far beyond the initial design and manufacturing. In the automotive industry these safety systems must perform reliably over the years under varying environmental conditions. This paper examines the critical role of periodic maintenance in sustaining the long-term safety and functional integrity of these systems throughout the lifecycle. As per the latest data from the Ministry of Road Transport and Highways (MoRTH), in 2022, India reported a total of 4.61 lakh road accidents, resulting in 1.68 lakh fatalities and 4.43 lakh injuries. The number of fatalities could have been reduced by the intervention of periodic services and monitoring the health of safety critical systems. While periodic maintenance has contributed to long term safety of the vehicles, there are a lot of vehicles on the road
HN, Sufiyan Ahmed, Khan, Furqan, Srinivas, Dheeraj
Self-supervised diagnostics & prognostics framework for predictive maintenance in electric vehicles2026-26-0673To be published on 01/16/2026
Predictive maintenance is essential for enhancing the reliability, safety, and operational efficiency of connected vehicles. However, traditional supervised learning approaches for fault prediction depend heavily on large, labeled datasets of failure events, which are often scarce and expensive to obtain in real-world automotive environments. This paper proposes an original self-supervised anomaly detection framework that predicts emerging failures using only healthy operational data, eliminating the need for explicit failure labels. The approach employs self-supervised pretext tasks, such as masked signal reconstruction and future telemetry prediction, to learn robust representations of normal multi-sensor behavior (e.g., temperature, pressure, current, vibration). An unsupervised anomaly detection model then identifies deviations from these learned patterns. This integrated with data-informed predictive models enable early detection of faults across critical subsystems such as
Kumar, Pankaj, Deole, Kaushik, Hivarkar, Umesh
From Vision to Reality - Automotive UI/UX Concept Development at Magna2026-26-0477To be published on 01/16/2026
The development of automotive UI/UX relies on the latest technologies and features in modern vehicle design, focusing on enhancing user interaction. The Magna UI/UX team uses innovative tools to streamline the development of user interaction features. Our process is accessible to all stakeholders and applicable to all UI/UX projects. With extensive experience working with both new entrants and traditional OEMs, we leverage diverse insights and methodologies to create state-of-the-art user experiences. Beginning with the UI strategy, Magna defines the overall display and interaction strategy based on the latest UI/UX trends and benchmarking criteria for user experience. In this phase, Magna uses online clickdummies to evaluate initial wireframes and sketches, documenting UI elements (buttons, typography, colors, icons) and simulating feature interactions like music control. To develop a UI/UX concept based on customer vision, Magna creates the base screen layout and operation flow
Lechner, Michael
Data analytics methodology for vehicle quality complaint analysis2026-26-0654To be published on 01/16/2026
Automobiles have become a part of people's everyday life. Customers base their trust on a brand's reputation while making a buying decision. With the evolving trends, feature advancements, automobiles have become a complex system. Ensuring product quality amidst system complexities is necessary to maintain the brand value & ensure customer satisfaction. Efficient addressal of customer quality complaints is pivotal in maintaining product quality. Until recent times, manual analysis using traditional data processing tools has been used for vehicle complaint analysis. However, considering the large quantum of data in new age vehicles with more number of control units, it becomes time-consuming, expertise dependent and susceptible to human errors. Given this & the advent of new age machine learning techniques & data analysis tools that can handle large amount of data, it is imperative to adopt them for vehicle complaint analysis. This research paper puts forth a method to analyze vehicle
Venkatesan, Prasanna, Raju, Vivek
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Introduction to Aerospace Fiber Optics Technician, Quality Assurance Inspector, or Engineer Hands-on CompetenciesARP5602/8 (Current)11/12/2025
This document establishes training guidelines applicable to fiber optic technician, quality assurance, or engineer technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Aerospace Fiber Optics Quality Assurance Knowledge CompetenciesARP5602/9 (Current)11/12/2025
This document establishes training guidelines applicable to fiber optic quality assurance technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Introduction to Aerospace Fiber Optics Installer Hands-on CompetenciesARP5602/6 (Current)11/12/2025
This document establishes training guidelines applicable to fiber optic installer technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Logisticians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Shipping Receiving Production Purchasing
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Aerospace Fiber Optics Technician Knowledge CompetenciesARP5602/7 (Current)11/12/2025
This document establishes training guidelines applicable to fiber optic technician technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Aerospace Fiber Optics Engineer Knowledge CompetenciesARP5602/10 (Current)11/12/2025
This document establishes training guidelines applicable to fiber optics engineer technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Trainers/Instructors Third Party Maintenance Agencies Production
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Aerospace Fiber Optics Installer Knowledge CompetenciesARP5602/5 (Current)11/11/2025
This document establishes training guidelines applicable to fiber optic installer technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
AS-3 Fiber Optics and Applied Photonics Committee
Optimization System of E-commerce Logistics Distribution Path Based on Data Analysis2025-99-010811/11/2025
With the rapid development of e-commerce, the logistics industry also presents new features such as multi-level, integrated upstream-downstream operations, increasingly perfect service quality and low logistics costs. The exponential growth in online transactions and consumer expectations for faster, more reliable deliveries intensifies the pressure on logistics systems. The last-mile service network refers to the logistics nodes that have direct contact with consumers, and its geographical location and quantity will directly affect the service level, cost and customer service mode of the distribution network. However, with the rapid growth in the number of online shoppers and their imbalance on the Internet, these factors have gradually become an important basis for influencing the layout of terminal outlets. This imbalance, coupled with dynamic urban traffic conditions, renders traditional distribution planning methods inadequate. Therefore, in the e-commerce environment, how to
Tong, Tong, Gu, Xuefei, Li, Lingxiao
Evaluating the Influence of Material Properties and Hardness on Tightening Torque2025-28-025511/06/2025
Earthmoving machines are equipped with a variety of ground-engaging tools that are joined by bolted connections to improve serviceability. These tools are made from heat-treated materials to enhance their wear resistance. Attachments on earthmoving machines, including buckets, blades, rippers, augers, and grapples, are specifically designed for tasks such as digging, grading, lifting, and breaking. These attachments feature ground-engaging tools (GET), such as cutting bits or teeth, to protect the shovel and other earthmoving implements from wear. Torquing hardened plates of bolted joint components is essential to ensure uniform load distribution and prevent premature failure. Therefore, selecting the proper torque is an important parameter. This study focuses on analyzing various parameters that impact the final torque on the hardened surface, which will help to understand the torque required for specific joints. Several other parameters considered in this study include hardware
Parameswaran, Sankaran Potti, Bhosale, Dhanaji, Kumar, Rajeev
Virtual Reality Application in CFD Data Analysis for after Treatment Systems2025-28-032911/06/2025
Virtual reality (VR), Augmented Reality (AR) and Mixed reality (MR) are advanced engineering techniques that coalesces physical and digital world to showcase better perceiving. There are various complex physics which may not be feasible to visualize using conventional post processing methods. Various industrial experts are already exploring implementation of VR for product development. Traditional computational power is improving day-by-day with new additional features to reduce the discrepancy between test and CFD. There has been an increase in demand to replace actual tests with accurate simulation approaches. Post processing and data analysis are key to understand complex physics and resolving critical failure modes. Analysts spend a considerable amount of time analyzing results and provide directions, design changes and recommendations. There is a scope to utilize advanced features of VR, AR and MR in CFD post process to find out the root cause of any failures occurred with
Savitha, Bhuduri, Sharma, Sachin
Transformative Deep Learning for Image Colorization with Machine Learning-Based Classification2025-28-031711/06/2025
Imagine a user opening a technical manual, eager to troubleshoot an issue, only to find a mix of stark black-and-white illustrations alongside a few color images. This inconsistency not only detracts from the user experience but also complicates understanding. For technicians relying on these documents, grayscale graphics hinder quick interpretation of diagrams, extending diagnostics time and impacting overall productivity. Producing high-quality color graphics typically requires significant investment in time and resources, often necessitating a dedicated graphics team. Our innovative pipeline addresses this challenge by automating the colorization and classification of colored graphics. This approach delivers consistent, visually engaging content without the extensive investment in specialized teams, enhancing the visual appeal of materials and streamlining the diagnostic process for technicians. With clearer, more vibrant graphics, technicians can complete tasks more efficiently
Khalid, Maaz, Akarte, Anurag, Kale, Aniket, Rajmane, Gayatri, Nalawade, Komal
Connected Aftermarket Services for Off-Highway Vehicles: Enhancing Fleet Management Through Real-Time Data and Predictive Maintenance2025-28-030711/06/2025
Off-highway vehicles (OHVs) are essential in heavy-duty industries like mining, agriculture, and construction, as equipment availability and efficiency directly affect productivity. In these harsh settings, conventional maintenance plans relying on set intervals frequently result in either early component replacements or unexpected breakdowns. This document presents a Connected Aftermarket Services Platform (CASP) that utilizes real-time data analysis, predictive maintenance techniques, and unified e-commerce functionalities to evolve OHV fleet management into a proactive and smart operation. The suggested system integrates IoT-enabled telematics, cloud-based oversight, and AI-powered diagnostics to gather and assess machine health indicators such as engine load, vibration, oil pressure, and usage trends. Models for predictive maintenance utilize both historical and real-time data to produce advance notifications for component failures and maintenance requirements. Fleet managers get
Vashisht, Shruti
Leveraging AI for Autonomous Vehicle Simulations in SIL and HIL Frameworks2025-28-027111/06/2025
This paper offers recent ideas and its implementation on leveraging AI for off highway Autonomous vehicle Simulations in SIL and HIL frameworks. Our objective is to enhance software quality and reliability while reducing costs and efforts through advanced simulation techniques. We employed multiple innovative solutions to build a System of Systems Simulation. Physics based models are a prerequisite for detailed and accurate representation of the real-world system, but it poses challenges due to its computational complexity and storage requirements. Machine learning algorithms were used to create surrogate/reduced order models to optimize by preserving the expected fidelity of models. It helped to speed up simulation and compile model code for SIL & HIL Targets. Built AI driven interfaces to bridge windows, Linux and Mobile Operating systems. Time synchronization was the key challenge as multiple environments were needed for end-to-end solutions. This was resolved by reinforcement
Karegaonkar, Rohit P., Aole, Sumit, Dasnurkar, Swapnil, Singh, Vishwajeet, Saha, Soumyadeep
Predictive Maintenance Solution with Real-Time Insights and Cost Estimation for Machine Health Management2025-28-030211/06/2025
This paper introduces a comprehensive solution for predictive maintenance, utilizing statistical data and analytics. The proposed Service Planner feature offers customers real-time insights into the health of machine or vehicle parts and their replacement schedules. By referencing data from service stations and manufacturer advisories, the Service Planner assesses the current health and estimated lifespan of parts based on metrics such as days, engine hours, kilometers, and statistical data. This approach integrates predictive analytics, cost estimation, and service planning to reduce unplanned downtime and improve maintenance budgeting, aligning with SAE expectations for review-ready manuscripts. The user interface displays current part health, replacement due dates, and estimated replacement costs. For example, if air filter replacement is recommended every six months, the solution uses manufacturer advisories to estimate the remaining life of the air filter in terms of days or
Chaudhari, Hemant Ashok
Customer Support – Failure and Warranty Analysis in Off-Highway Vehicles2025-28-030011/06/2025
The reliability and durability of off-highway vehicles are crucial for industries like construction, mining, and agriculture. Failures in such machines not only disrupt operations but can also lead to significant economic losses and safety concerns. Effective failure and warranty analysis processes are essential to improve customer support, minimize downtime, and enhance equipment life cycle. This paper outlines a comprehensive 7-step failure analysis methodology tailored for off-highway vehicles, accompanied by warranty analysis using Weibull, 6MIS, and 12MIS IPTV. It details the process from problem identification through permanent solution implementation, emphasizing tools and techniques necessary for sustainable improvements. The structured approach provides an actionable blueprint for OEMs and service teams to enhance customer satisfaction, support sustainable development goals, and maintain regulatory compliance.
Mulla, Tosif, Thakur, Anil, Tripathi, Ashish
E-Motor Thermal Management Using 2D-3D Coupling2025-28-022511/06/2025
In the electrical machines, detrimental effects resulted often due to the overheating, such as insulation material degradation, demagnetization of the magnet and increased Joule losses which result in decreased lifetime, and reduced efficiency of the motor. Hence, by effective cooling methods, it is vital to optimize the reliability and performance of the electric motors and to reduce the maintenance and operating costs. This study brings the analysis capability of CFD for the air-cooling of an Electric-Motor (E-Motor) powering on Deere Equipment's. With the aggressive focus on electrification in agriculture domain and based on industry needs of tackling rising global warming, there is an increasing need of CFD modeling to perform virtual simulations of the E-Motors to determine the viability of the designs and their performance capabilities. The thermal predictions are extremely vital as they have tremendous impact on the design, spacing and sizes of these motors.
Singh, Bhuvaneshwar, Tirumala, Bhaskar, Badgujar, Swapnil, HK, Shashikiran
Design IQ: An Integrated System for Smart Engineering Metrics2025-28-032711/06/2025
Weight and cost are pivotal factors in new product development, significantly impacting areas such as regulatory compliance and overall efficiency. Traditionally, monitoring these parameters across various stages involves manual processes that are often time-intensive and prone to delays, thereby affecting the productivity of design teams. In current workflows, designers must manually extract weight and center of gravity (CG) data for each component from disparate sources such as CAD models or supplier documents. This data is then consolidated into reports typically using spreadsheets before being analyzed at the module level. The process requires careful organization, unit consistency, and manual calculations to assess the impact of each component on overall system performance. These steps are not only laborious but also susceptible to human error, limiting agility in design iterations. To address these challenges, there is a conceptual opportunity to develop a system that could
Patil, Vivek, Sahoo, Abhilash, Ballewar, Sachin, Chidanandappa, Basavaraj, Chundru, Satyanarayana
Smart Fleet Management for Mechanical Tillage Implements2025-28-031211/06/2025
Tillage, a fundamental agricultural practice involving soil preparation for planting, has traditionally relied on mechanical implements with limited real-time data collection or adjustment capabilities. The lack of real-time data and implement statistics results in fleet managers struggling to track performance, driver behavior, and operational efficiency of the implements. Lack of data on vehicle performance can result in unexpected breakdowns and higher maintenance costs, ensuring compliance with regulations is challenging without proper data tracking, potentially leading to fines and legal issues. Bluetooth-enabled mechanical implements for tillage operations represent an emerging frontier in precision agriculture, combining traditional soil preparation techniques with modern wireless technology. Implement mounted battery powered BLE (Bluetooth Low Energy) modules operated by solar panel based rechargeable batteries to power microcontroller. When Implement is operational turns
Kaniche, Onkar, Rajurkar, Kartik, Gokhale, Sourabha, Vadnere, Mohan
Eyes of Robot Operating System for Future Hands2025-28-024611/06/2025
This paper presents a novel approach to automated robot programming and robot integration in manufacturing domain and minimizing the dependency on manual online/offline programming. Traditional industrial robots programming is typically done by online programing via teach pendants or by offline programming tools. This presents a major challenge as it requires skilled professionals and is a time-consuming process. In today’s competitive market, factories need to harness their full potential through smart and adaptive thinking to keep pace with evolving technology, customer demand, and manufacturing processes. This requires ability to manufacture multiple products on the same production line, minimum time for changeovers and implement robotic automation for efficiency enhancement. But each custom automation piece also demands significant human efforts for development and maintenance. By integrating the Robot Operating System (ROS) with vision-based 3D model generation systems, we address
Hepat, Abhijeet
Arcing Simulation for Automatic Transfer Switches using In-House UDF2025-28-028411/06/2025
Automatic transfer switches (ATS) play an important role in the providing uninterrupted power to various applications like data Centre, hospitals etc. They can be connected between two utility sources, two gensets or a combination of them. It operates when one of the sources to which the load is connected is not available or the preferred source is up. While they do their job smoothly, they internally see harsh conditions. When an active source disconnects, an arc is generated between the contacts. The arc forms when the current jumps through the small air gap breaking it into ions and electrons at very high temperatures, typically above 10000K. This arc needs to be quenched quickly to avoid damage to the contacts and current carrying conductors. This paper throws light on an in-house methodology that is developed using the commercial tool Ansys Fluent. The physics of arc consisting of flow, thermal and electromagnetic fields are modelled. This paper includes the simulation of arc
Gaikwad, Nikhil Ravindra, Badhe, Vivek
AI Negotiator: Intelligent Chatbot for Seamless Negotiations2025-28-034711/06/2025
Autonomous negotiation systems, powered by artificial intelligence, are transforming supply chain management by optimizing supplier interactions. This paper proposes a framework for autonomous supplier negotiation using Statistical hypothesis testing to evaluate multiple negotiation strategies under uncertain conditions. Paper models supplier price negotiations with Random simulations, incorporating supplier cost variability and negotiation dynamics. Three strategies—distributive, integrative, and hybrid—are tested across diverse scenarios, with performance measured by negotiated price outcomes. Statistical hypothesis testing is applied to compare strategy effectiveness, identifying the hybrid approach as optimal for balancing cost savings and supplier relationships. The framework offers actionable insights into implementing autonomous negotiation systems in procurement as Agents negotiating with suppliers.
Panda, Dinesh Abhimanyu
Monitoring of Long Drill Wear Status through Vibration Analysis Using Time and Frequency Domain2025-28-025211/06/2025
Hard carbon steel is used for drilling deep holes, such as C19, which has dimensions of 630 mm in length, 50 mm in breadth, and 125 mm in depth. Long twist drills with a diameter of 8 mm are used. Such drills are manufactured with larger helix than the traditional drills for increasing penetration efficiency. But, Prediction of long drill & tool replacement strategies during metal cutting are mostly depend on conservative estimation given by manufacturer’s catalog. Hence, long drill while drilling cam shaft in automobile applications may be underutilized or over utilized. Now a day, Diagnostics software in advanced CNC machines are indicating hours of utilization of tools in bar chart. On the other hand, Utilization of long drill wear beyond the recommended range affects the quality of workpiece. As a result, several researchers have proposed the reliable approach of vibration-based online monitoring of drill flank wear over the past 20 years. In these works, the vibration sensor is
R. S., Nakandhrakumar, Raja, Selvakumar, Elumalai, Sangeethkumar, Velmurugan, Ramanathan, M, Ramakrishnan
Technology Driven Solutions for Effective Tool Management2025-28-024911/06/2025
Tool management remains a persistent challenge in manufacturing, where misplaced or poorly calibrated tools such as torque guns and screwdrivers cause downtime, quality defects, and compliance risks. The Internet of Things (IoT) is transforming tool management from manual entries in spreadsheets and logs to real-time, data-driven solutions that enhance operational efficiency. With ongoing advancements in IoT architecture, a range of cost-effective tracking approaches is now available, including Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), Wi-Fi, RFID, and LoRaWAN. This paper evaluates these technologies, comparing their trade-offs in accuracy, scalability, and cost for tool-management scenarios such as high-precision station tracking, zonal monitoring, and wide-area yard visibility. Unlike prior work that focuses on asset tracking in general, this study provides an ROI-driven, scenario-based comparison and offers recommendations for selecting appropriate technologies based on
Patel, Shravani Prashant
Analysis of Artificial Intelligence in Biofuel Industry: A Case Study2025-28-034111/06/2025
Increasing reservations about the mass consumption of fossil fuels because of their hazardous impact on ecosystem has led to an increased focus to look for renewable alternative. In the last decade, much research is made on production of biodiesel for blending with diesel to reduce diesel consumption in the transport sector. Studies suggest that biofuel do not provide any harm to environment because of their availability from natural resources. Biofuel production and its further utilization requires identifying unknown parameters having nonlinear relationships with each other. Accurate and better predictive tools are required at different stages during its usage. AI technique is one such tool that can provide support during production and utilization. The technique is utilized in designing, monitoring, predicting, decision making and optimizing systems. The present research investigates the areas of AI usage which makes use of models for designing better production strategies, accurate
KUMAR, VIVEK, Vashist, Devendra
Prognostic Framework for Failure Analysis and Smart Farming2025-28-034011/06/2025
Prognostics and Health Management (PHM) is framework for electrical/mechanical components in heavy machines represents a transformative approach that harnesses cutting-edge sensing technologies and analytics to predict and elevate reliability and efficiency of agricultural/construction machinery. By using advanced data collection and sophisticated analytics, PHM achieves real-time monitoring of critical performance parameters such as voltage, current, temperature, and operational cycles, along with field data mapped with GPS coordinates as well as environmental conditions. This capability allows for the early detection of anomalies and potential failures, thereby enhancing operational reliability. Data collected from the machine will be pushed to the server periodically and whenever any failure is detected advanced AI algorithms on machine and server will analyze the information and link to collected data which will be used to identify possible failures or assess the safety of the
Shinde, Ketan Kishor
Enhancing Diagnostic Efficiency and Customer Support for Off-Highway Vehicles in India2025-28-030111/06/2025
Off-highway vehicles (OHVs) are vital for India’s construction, mining, agriculture, and infrastructure sectors. With growing demand for productivity and sustainability, the need for efficient customer support and precise diagnostic techniques has become paramount. This paper presents a comprehensive study of challenges faced in India, current and emerging diagnostic technologies, troubleshooting techniques, and strategies for effective customer support. Case studies, tables, and diagrams illustrate practical solutions.
Mulla, Tosif, Thakur, Anil, Tripathi, Ashish
CRIMPING TOOLS, TYPE 1, TERMINAL, HAND, WIRE TERMINATION FOR WIRE BARREL SIZES 20 THROUGH 28AS22520/2C (Current)11/04/2025
AE-8C2 Terminating Devices and Tooling Committee
Assessment of Electrification Potential for Hand-Held Powertools and Two-Wheelers2025-32-009411/03/2025
The reduction of the CO2 footprint of transport vehicles is a major challenge to minimize the harmful impact of technology on the environment. Beside passenger cars and light and heavy-duty vehicles, this affects also the two-wheeler category and the non-road mobile machinery (NRMM). One promising path for the de-carbonization is the transition from fossil-fuel powered ICE powertrains to electric powertrains. Several examples of electrified powertrains showcase possibilities for small hand-held power-tools or small mopeds and scooters. As the powertrain categories two-wheeler and NRMM are very diversified and consist of various sub-categories and sub-classes with many different applications, the feasibility of electrification for the whole category cannot be judged by few examples. In this publication, a methodology for assessing the electrification potential of hand-held power tools and two-wheelers is shown. The method uses 4 different factors, which determine the feasibility for
Schmidt, Stephan, Schacht, Hans-Juergen, Weller, Konstantin, Absenger, Johann Friedrich
Clean Cuts, Clear Conscience: Advanced Engines, Optimized Tools, Eco-Friendly Fuels2025-32-008711/03/2025
Handheld outdoor power equipment is utilized globally to shape and maintain the environment, serving as daily assistants in forestry under demanding conditions. In the power tool sector, the transition from petrol to battery-powered products is already well underway, particularly for consumer applications. However, internal combustion engines will continue to be indispensable for professional users of power tools, who place the highest demands on their equipment in terms of performance and energy density. These power tools are often used in remote locations and thus far away from a possible charging infrastructure. To contribute to climate protection, biofuels and RFNBOs are crucial. The continuous optimization of engine technology and its overall system, including cutting tools (such as saw chains and cutting wheels), is a key development goal for STIHL. The optimized interaction between the saw chain, guide bar, and power train is necessary for efficient work progress and ergonomic
Beck, Kai W., Maier, Georg, Müller, Matthias, Lux, Thomas, Kölmel, Armin, Lochmann, Holger, Melder, Jens
Design and Development of Fiber Optic Vibration Sensor for Automobile Applications2025-28-037110/30/2025
This work goals at designing and developing a vibration sensor based on fiber optics and it is a component of the Structural Health Monitoring (SHM) system. The main component of the SHM system is a network of sensors (strain, vibration, acoustic, etc.) that can track the physical condition of the structures in real time and assist in identifying the beginning of any damage. During flight, launch vehicles typically experience extreme dynamic stresses such shock, random vibration, aerodynamic, and thermal. The assessment of health and the detection of any part detachment or loosening of sub- assemblies are greatly aided by vibration monitoring. Compared to traditional electrical sensors (such piezoelectric or capacitive), SHM systems based on fiber optic sensors show promise because of their EMI resistance, ease of integration into structures, and widespread sensing capabilities. Multiplexing capability of optical fibers is the main additional benefit for system monitoring the numerous
P, Geetha, Koppala, Neelima, Nagarajan, Sudarson
Analysis of Maintenance Strategies of Electrical Systems of Electric Bus Charging Station2025-28-040710/30/2025
Charging management has a profound impact on the reliability and safety of electric bus (EB) services. However, the actual charging operation of EB fleets is a critical challenge due to uncertain energy consumption, limited charging resources and other factors. At present there are no operational and maintenance guidelines present for operation of EB charging stations since the running and operation of these facilities are at the initial stages of development. There is a need to develop these strategies that provides smooth operation of these newly developed facilities. In the present work maintenance strategies of electrical systems of Electric bus charging station were designed. The complete maintenance is divided into quarterly and annual maintenance based on the requirements and nature of work for smooth operation. Quarterly Maintenance is devised on detecting early signs of wear through visual inspections of key components, including transformers and ventilation systems while
Soam, Kumaresh, Vashist, Devendra
A Guideline for Aerospace Platform Fiber Optic Training and Awareness EducationARP5602 (Current)10/23/2025
This document establishes training guidelines applicable to fiber optic safety training, technical training and fiber awareness for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Logisticians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Shipping Receiving Production Purchasing
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Aerospace Fiber Optics Fabricator Hands-on CompetenciesARP5602/4 (Current)10/23/2025
This document establishes training guidelines applicable to fiber optic fabricator technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Aerospace Fiber Optics Fabricator Knowledge CompetenciesARP5602/3 (Current)10/23/2025
This document establishes training guidelines applicable to fiber optic fabricator technical training for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Production
AS-3 Fiber Optics and Applied Photonics Committee
A Guideline for Aerospace Platform Fiber Optic Training and Awareness Education Introduction to Aerospace Fiber Optics Knowledge CompetenciesARP5602/1 (Current)10/23/2025
This document establishes training guidelines applicable to fiber optic safety training, technical training and fiber awareness for individuals involved in the manufacturing, installation, support, integration and testing of fiber optic systems. Applicable personnel include: Managers Engineers Technicians Logisticians Trainers/Instructors Third Party Maintenance Agencies Quality Assurance Shipping Receiving Production Purchasing
AS-3 Fiber Optics and Applied Photonics Committee
Items per page:
1 – 50 of 10153