Browse Topic: Quality, Reliability, and Durability

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Freedom from Interference Challenges for Adaptive Autosar Based Platform2025-01-8074To be published on 04/01/2025
Keyword - Autonomous & Connected Vehicles, Functional Safety, ISO26262, Freedom from Interference, Adaptive Autosar, Operating System, Safety mechanisms, Hypervisor, MPU, MMU, PHM. Adaptive AUTOSAR is extensively utilized in the development of autonomous and connected vehicles, where functional safety is paramount. This framework ensures that critical safety requirements are met, providing a reliable and secure platform for advanced vehicular functionalities. The paper delves into challenges and mechanisms for ensuring Freedom from Interference in Adaptive AUTOSAR-based platform, emphasizing strategies for managing complexities and adhering to ISO 26262 standards. This study focuses on managing Memory, Timing, and Execution challenges within Adaptive AUTOSAR-based Platform. In Classic AUTOSAR, robust safety mechanisms ensure Freedom from Interference (FFI). Memory protection is achieved through Memory Protection Unit configuration and memory partitioning. Timing Protection mechanisms
Jain, Yesha
Technical Paper
A Proposed RE-Method for Redesigning Damaged Cam Gear in Automotive Engines using Image Processing and 3D CAD Model2025-01-8634To be published on 04/01/2025
Cam gear is a critical component of the timing system in an internal combustion engine, ensuring the synchronized opening of the engine valves, pistons, and rotating parts, but their unavailability may result in long-term downtime or expensive replacement. Reverse engineering (RE) systems also play an important role in promoting sustainable practices in automotive technologies. The study focuses on presenting a proposed method for redesigning damaged parts in engines using image processing technology by creating an accurate CAD model. In addition to clarifying of the expected causes that led to cam gear damage. The proposed method involves taking a high-resolution image of the damaged part, then applying advanced image processing algorithms to analyze and reconstruct the geometry of the part. The data is then converted into a high-resolution 3D CAD model. This approach aims to address the challenges of replicating worn or broken parts, providing a cost-effective maintenance and
Ali, Salah H. R., Ehab, Eslam, Barakat, Ebrahim, Younes, Abdelrahman, Ali, Amr S.H.R.
Technical Paper
Development of a new concept structure for 4-way electric headrest adjustment2025-01-8620To be published on 04/01/2025
In car seats, various adjustment mechanisms are provided to accommodate passengers of different body sizes, ensuring a comfortable posture. In premium vehicle models, customer convenience is further enhanced by enabling electric operation for these adjustments. Among these, electric headrest adjustment systems are increasingly being adopted in premium vehicle models. This paper discusses the development of a new 4-way (up/down/left/right) electric headrest concept that aims to improve cost competitiveness while addressing existing quality issues. The current headrest mechanism consists of an X-link structure, where a motor rotates the X-link around its axis to adjust the mechanism forward and backward. However, this design involves many components, resulting in high costs, and the tolerance caused by screw thread gaps at the center of the X-link makes quality assurance difficult. Additionally, the reliance on a lead screw for operation causes issues with play and load concentration. To
Yu, Sanguk
Technical Paper
Automated Analysis and Cleaning of Manufacturing Data: The Power of Automation Playbooks2025-01-8332To be published on 04/01/2025
High-efficiency manufacturing relies heavily on an extensive suite of software applications, including those for order handling, quality control, trace management, PLC communication, Andon boards, and scheduling. This reliance is particularly pronounced in facilities operating under tight schedules with stringent production targets and close collaboration with Just-In-Time (JIT) suppliers. Ensuring the continuous operation of these software systems is crucial; any downtime can result in delayed or lost units, potentially leading to significant revenue losses amounting to millions annually. Regular patching and rebooting of servers and applications are essential to maintaining system uptime, as the risk of failure increases with prolonged operation. Therefore, frequent resets and health checks are necessary, but these processes are both complex and time-consuming due to the multitude of servers and narrow scheduling windows involved. The integration of automation into these maintenance
Jan, Jonathan, Preston, Joshua, Juncker, John
Technical Paper
Accuracy of Time Stamps in Digital and Network Video Recorders2025-01-8690To be published on 04/01/2025
Video analysis plays a major role in many forensic fields. Many articles, publications, and presentations have covered the importance and difficulty in properly establishing frame timing. In many cases, the analyst is given video files that do not contain native metadata. In other cases, the files contain video recordings of the surveillance playback monitor which eliminates all original metadata from the video recording. These “video of video” recordings prevent an analyst from determining frame timing using metadata from the original file. However, within many of these video files, timestamp information is visually imprinted onto each frame. Analyses that rely on timing of events captured in video may benefit from these imprinted timestamps, but for forensic purposes, it is important to establish the accuracy and reliability of these timestamps. The purpose of this research is to examine the accuracy of these timestamps and to establish if they can be used to determine the timing
Molnar, Benjamin, Terpstra, Toby, Voitel, Tilo
Technical Paper
Structural Weld Optimization with Efficient Approach of DFSS2025-01-8248To be published on 04/01/2025
Structural Weld Optimization with Efficient Approach of DFSS Abstract In automotive engineering, welds are frequently used to join or connect various parts of structures, frames, cradles, chassis, suspension components, and body. These welds usually form the weakest material link for durability and impact loads, which are measured by lab-controlled durability and crash tests, as well as real-world vehicle longevity. Consequently, designing robust welded components while optimizing for material performance is often prioritized as engineering challenge. The position, dimensions, material, manufacturing variation, and defects all affect the weld quality, stiffness, durability, impact, and crash performance. In this paper, the authors present best practices based on studies over many years, a rapid approach for optimizing welds, especially seam welds, by adopting Design For Six Sigma (DFSS) IDDOV (Identify, Define, Develop, Optimization, and Verification) discrete optimization approach. We
Qin, Wenxin (Daniel)
Technical Paper
Comparison of Gasoline Particulate Indices Using U.S. Market Gasoline Samples2025-01-8449To be published on 04/01/2025
Simulated distillation (SimDis) uses wide bore capillary gas chromatography (GC) to provide a detailed volatility profile of blended gasoline. The boiling point distribution from SimDis analysis is correlated to the hydrocarbon contents of spark ignition fuels and provide the resolution necessary to characterize the compositions of the fuel. Recent publications on simulated distillation applied to spark ignition fuel reveal the merits of indexing a gasoline fuel so that it can be correlated to the tendency of particulate emissions from vehicles. With this in mind, SimDis can be a useful and quick tool in assessing the PM-formation potential of market gasolines. Heavy aromatic compounds are compounds identified as having at least 10 Carbons and 1 aromatic ring. These compounds that are present in spark ignition fuels are major contributors to vehicle particulate emissions. These compounds can be found in the higher boiling portion (T70+) of the distillation profiles. As demonstrated in
Goralski, Sarah, Geng, Pat, Dozier, Jon, Butler, Aron
Technical Paper
A Time-Aware Shaper-Based Method for Addressing Traffic Bursts and Out-of-Order Induced by IEEE 802.1CB in In-Vehicle Networks2025-01-8079To be published on 04/01/2025
The trends of intelligence and connectivity are continuously driving innovation in automotive technology. With the deployment of more safety-critical applications, the demand for communication reliability in in-vehicle networks (IVNs) has increased significantly. As a result, Time-Sensitive Networking (TSN) standards have been adopted in the automotive domain to ensure highly reliable and real-time data transmission. IEEE 802.1CB is one of the TSN standards that proposes a Frame Replication and Elimination for Reliability (FRER) mechanism. With FRER, streams requiring reliable transmission are duplicated and sent over disjoint paths in the network. FRER enhances reliability without sacrificing real-time data transmission through redundancy in both temporal and spatial dimensions, in contrast to the acknowledgment and retransmission mechanisms used in traditional Ethernet. However, previous studies have demonstrated that, under specific conditions, FRER can lead to traffic bursts and
Luo, Feng, Ren, Yi, Zhu, Yian, Wang, Zitong, Guo, Yi, Yang, Zhenyu
Technical Paper
Empirical Analysis on Machine Vision Recognition of Green Bike Lanes for Vulnerable Road Users Safety2025-01-8017To be published on 04/01/2025
Deliberate modifications to infrastructure can significantly enhance machine vision recognition of road sections designed for Vulnerable Road Users, such as green bike lanes. This study evaluates how green bike lanes, compared to unpainted lanes, enhance machine vision recognition and vulnerable road users safety by keeping vehicles at a safe distance and preventing encroachment into designated bike lanes. Conducted at the American Center for Mobility, this study utilizes a vehicle equipped with a front-facing camera to assess green bike lane recognition capabilities across various environmental conditions including dry daytime, dry nighttime, rain, fog, and snow. Data collection involved gathering a comprehensive dataset under diverse conditions and generating masks for lane markings to perform comparative analysis for training Advanced Driver Assistance Systems. Quality measurement and statistical analysis are used to evaluate the effectiveness of machine vision recognition using
Ponnuru, Venkata Naga Rithika, Das, Sushanta, Grant, Joseph, Naber, Jeffrey, Bahramgiri, Mojtaba
Technical Paper
SPC based Critical Parameters Monitoring of Vendor Supplied Parts by Auto OEM for Quality Control2025-01-8334To be published on 04/01/2025
In Automobile manufacturing, maintaining the Quality of vendor-supplied parts is crucial. This paper introduces a digital tool designed to monitor critical parameters of these parts in real-time. Utilizing Statistical Process Control (SPC) graphs, the tool continuously tracks essential parts and process parameters, predicting potential issues for proactive improvements even before parts are supplied. The tool integrates data from all vendor partners into a single platform, providing a comprehensive view of their performance and the parts they supply. Vendors input data into a digital application, which is then analyzed in the cloud using SPC techniques to predict potential alerts for improvement. These alerts are automatically sent to both vendors and relevant personnel at the OEM, enabling proactive measures to address any quality deviations. 100% data is visualized in an integrated dashboard which acts as a single source of truth for all stakeholders. Real-time monitoring is done
Sahoo, Priyabrata, Garg, Ishan, Rawat, Sudhanshu, Narula, Rahul, Gupta, Ankit, Bindra, Ritesh, Rao, Akkinapalli VN, Garg, Vipin
Technical Paper
Evaluation of Several Tesla Dashcam Angles for Model 3 and Y Via Reverse Project Photogrammetry2025-01-8700To be published on 04/01/2025
Tesla Model 3 and Model Y vehicles come equipped with a standard dash-camera feature with the ability to record video in four directions called TeslaCam. Additional views have been known to be recorded under specific circumstances, often triggered in impacts, and available to some owners through data requests to Tesla. Prior research into TeslaCam either did not fully explore all known camera views across multiple vehicles or the metadata associated with genuine copies of TeslaCam video. Testing and analysis of real-world crashes revealed a reliable methodology to conducting photogrammetry analysis utilizing the front, rear, and side cameras found on Tesla Model 3 and Model Y vehicles, how to verify the likelihood of any copy of TeslaCam being a genuine original video discovered during the course of an investigation, and how to examine ever changing video properties as new software becomes available for the vehicles. Moving and stationary Tesla vehicles captured frames of GPS
Jorgensen, Michael, Swinford, Scott, Imada, Kevin, Farhat, Ali
Technical Paper
Aspects for the optimization of car production regarding efficiency, availability and sustainability2025-01-8609To be published on 04/01/2025
Nowadays, more than in the recent decades, the design process for the body in white for passenger cars is driven by efficiency. This results in the enhanced usage of large-scale cast components made of aluminum for the battery compartment, the front or rear body and other components. While automotive industry is striving towards even larger structures made with so-called “Giga Casting” challenges in the casting and supply chain processes but also maintenance and repair processes of these large structures arise. Other tasks to solve might follow from controlling local microstructures and thus strength of the parts when flow length of the molten metal increase with component size especially in relation to an increased fraction of recycling aluminum. Within the Fraunhofer-internal project “FutureCarProduction” the emphasis is directed towards understanding what drives efficiency, availability and sustainability of modern processes for the production of a body in white. Moreover, the
Bleicher, Christoph, Qaralleh, Ahmad, Lehmhus, Dirk, Haesche, Marco, Fernandes Gomes, Leonardo, Pintore, Manuel, Kleinhans, Robert, Sommer, Silke, Tlatlik, Johannes
Technical Paper
Research on Noise Optimization Control based on the New Dead Zone Compensation in Dual Motor Hybrid System2025-01-8516To be published on 04/01/2025
In a three-phase voltage source inverter, in order to prevent the direct short circuit of the upper and lower tubes of the bridge arm and ensure the normal operation of the inverter, microsecond-level dead time needs to be added when the power devices are turned on and off. However, due to the dead-time effect, slight distortion may occur in the inverter within the modulation period, and this distortion will eventually lead to harmonic components in the output current after accumulation, thereby generating torque ripple. Against the above background, implementing dead-time compensation strategies is very important. To compensate for the voltage error caused by the dead-time effect, current polarity determination is required first. Then, the dead time is compensated, thereby indirectly compensating for the voltage error caused by the dead-time effect. Regarding the dead-time compensation time, without changing the hardware, this paper proposes a solution to turn off the dead-time
Jing, Junchao, Zhang, Junzhi, Zuo, Botao, Liu, Yiqiang, Yang, Tianyu, Zhu, Lulong
Technical Paper
Material selection of a Parcel shelf for structural performance and Perceived quality improvement through an assessment of wide range composite and sustainable materials.2025-01-8249To be published on 04/01/2025
In passenger vehicles, a parcel shelf is used to conceal luggage in the trunk compartment. Conventionally, materials used in new product development are heavy, making products less competitive in the market. As the automotive industry increasingly prioritizes lightweight products for EV, it is essential to find new alternative materials and technologies that meet performance standards and add value to the product. This research paper focuses on weight optimization, sustainable material section and cost reduction of the parcel shelf without compromising durability, stiffness, and load-bearing capabilities. The proposed material consists of ultra-lightweight composite materials available in various GSM and thicknesses, offering a high strength-to-weight ratio that contributes to: 1. Improved load vs. deflection ratio. 2. Enhanced aesthetics and perceived quality. The proposed material combination and strategy for the parcel shelf will result in a product that is half the weight of
Kinthala, Nareen Kumar, Patnaik, Manga, Khandelwal, Mohit, Kakani, Phani Kumar, Palaniappan, Elavarasan
Technical Paper
Application of AI/ML based Image Analytics in Auto Component Fracture Analysis2025-01-8228To be published on 04/01/2025
This paper introduces an innovative digital solution for the categorization and analysis of fractures in Auto components, leveraging Artificial Intelligence and Machine Learning (AI/ML) technologies. The proposed system automates the fracture analysis process, enhancing speed, reliability, and accessibility for users with varying levels of expertise. The platform enables users to upload images of fractured parts, which are then processed by an AI/ML engine. The engine employs an image classification model to identify the type of fracture and a segmentation model to detect and analyze the direction of the fracture. The segmentation model accurately predicts cracks in the images, providing detailed insights into the direction and progression of the fractures. Additionally, the solution offers an intuitive interface for stakeholders to review past analyses and upload new images for examination. The AI/ML engine further examines the origin of the fracture, its progression pattern, and the
Sahoo, Priyabrata, Rawat, Sudhanshu, Garg, Vipin, Naidu, Garima, Sharma, Amit, Narula, Rahul, Bindra, Ritesh, Khera, Pankaj, Goel, Pooja, Mondal, Arup
Technical Paper
Experimental Case Study of Sonic Perception of a First-Generation Electric Truck14-14-02-000802/24/2025
The sound generated by electric propulsion systems differs compared to the prevalent sound generated by combustion engines. By exposing listeners to various sound situations, the manufacturer can start understanding which direction to take to achieve compelling battery electric vehicle trucks from a sound perspective. The main objective of this study is to understand what underlying aspects decide the experience and perception of heavy vehicle–related sounds in the context of electrified propulsion. Using a thematic analysis of data collected at a listening experiment conducted in 2020, factors affecting the perception of novel sounds generated by a first-generation electric truck are investigated. A hypothesis is that the experience of driving or being a passenger in electric trucks will affect the rating and response differently compared to listeners not yet experienced with this sound. The results show that the combination of individual preference and experience, hearing function
Nyman, Birgitta, Fagerlönn, Johan, Nykänen, Arne
Journal Article
Port Node Importance and Risk Assessment in Shipping Networks Based on An Improved PageRank Approach and Reliability Analysis2025-01-718302/21/2025
Since the rapid development of the shipping and port industries in the second half of the twentieth century, the introduction of container technology has transformed cargo management systems, while simultaneously increasing the vulnerability of global shipping networks to natural disasters and international conflicts. To address this challenge, the study leverages AIS data sourced from the Vessel Traffic Data website to extract ship stop trajectories and construct a shipping network. The constructed network exhibits small-world characteristics, with most port nodes having low degree values, while a few ports possess extremely high degree values. Furthermore, the study improved the PageRank algorithm to assess the importance of port nodes and introduced reliability theory and risk assessment theory to analyze the failure risks of port nodes, providing new methods and perspectives for analyzing the reliability of the shipping network.
Li, Ding, Cheng, Cheng, Zhao, Xingxi, Li, Zengshuang
Technical Paper
Intelligent Detection Technologies for Pre-Paving Asphalt Pavement2025-01-717902/21/2025
This paper presents advanced intelligent monitoring methods aimed at enhancing the quality and durability of asphalt pavement construction. The study focuses on two critical tasks: foreign object detection and the uniform application of tack coat oil. For object recognition, the YOLOv5 algorithm is employed, which provides real-time detection capabilities essential for construction environments where timely decisions are crucial. A meticulously annotated dataset comprising 4,108 images, created with the LabelImg tool, ensures the accurate detection of foreign objects such as leaves and cigarette butts. By utilizing pre-trained weights during model training, the research achieved significant improvements in key performance metrics, including precision and recall rates. In addition to object detection, the study explores color space analysis through the HSV (Hue, Saturation, Value) model to effectively differentiate between coated and uncoated pavement areas following the application of
Hu, Yufan, Fan, Jianwei, Tang, Fanlong, Ma, Tao
Technical Paper
Space-Time Evolution of Temperature of Asphalt Mixture during Transportation2025-01-717102/21/2025
Temperature segregation significantly affects the compaction of asphalt mixtures and the durability of the asphalt pavement layer. Uneven cooling of the mixture during transportation is a key factor contributing to temperature segregation. This study uses finite element simulations to analyze the temporal and spatial temperature evolution during the transportation of asphalt mixtures. A temperature segregation evaluation index (TSIv) is proposed to assess the significance of various factors affecting segregation. Support vector regression (SVR), random forest regression (RFR), and extreme gradient boosting (XGBoost) models are employed to predict temperature changes during transportation and optimize the predictive models. The results indicate that the proportion of areas with a temperature difference of less than 10°C is consistently the highest, followed by areas with a temperature difference greater than 25°C, and then those with temperature differences in the ranges of 10-16°C and
Cheng, Hao, Ma, Tao, Tang, Fanlong, Fan, Jianwei
Technical Paper
Mobile Laser Scanning for Tunnel Inspection2025-01-715402/21/2025
Monitoring the safety and structural condition of tunnels is crucial for maintaining critical infrastructure. Traditional inspection methods are inefficient, labor-intensive, and pose safety risks. With its non-contact, high-precision, and high-efficiency features, mobile laser scanning technology has emerged as a vital tool for tunnel monitoring. This paper presents a mobile laser scanning system for tunnel measurement and examines techniques for calculating geometric parameters and processing high-resolution imaging data. Empirical evidence demonstrates that mobile laser scanning offers a reliable solution for evaluating and maintaining tunnel safety.
Lianbi, Yao, Zhang, Kaikun, Duan, Wei, Sun, Haili
Technical Paper
Thermal Buckling Analysis of Axially Layered Aluminium Zirconia Functionally Graded Beam2025-28-012002/07/2025
This study investigates the thermal buckling behavior of axially layered functionally graded material (FGM) thin beams with potential applications in automotive structures. The FGM beam is constructed from four axially stratified sections, with the proportional amount of metal and ceramic fluctuating through the thickness. The buckling analysis is carried out for three different support configurations: clamped-clamped, simply supported-simply supported, and clamped-simply supported. The primary objective is to identify the optimal thermal buckling temperature of the FGM thin beam using the Taguchi optimization method. Beam arrangements are established using a Taguchi L9 orthogonal array and analyzed using finite element software (ANSYS). Layers 1-4 of the axially layered beam are considered process parameters, while the thermal buckling temperature is the response parameter. Minitab software performs an Analysis of Variance (ANOVA) with a 95% confidence level to identify the most
Pawale, Deepak, Bhaskara Rao, Lokavarapu
Technical Paper
Predictive Grey-ANFIS Model for High-Precision Machining of Nimonic Alloy in Automobiles2025-28-004302/07/2025
The aim of this study is to create an Adaptive Neuro-Fuzzy Inference System (ANFIS) model for the Electrochemical Machining (ECM) process using Nimonic Alloy material, with a specific focus on several performance aspects. The optimization strategy utilizes the combination of the Taguchi method and ANFIS integration. Nimonic Alloy is widely employed in the aerospace, nuclear, marine, and car sectors, especially in situations that are susceptible to corrosion. The experimental trials are designed according to Taguchi's method and involve three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This study investigates performance indicators, such as the rate at which material is removed, the roughness of the surface, and geometric characteristics, including overcut, shape, and tolerance for orientation. Based on the analysis, it has been determined that the feed rate is the main component that influences the intended performance criteria. In order to
Natarajan, Manikandan, Pasupuleti, Thejasree, C, Navya, Kiruthika, Jothi, Silambarasan, R
Technical Paper
Advanced AI Tools for Haste Alloy Machining: ANFIS Approach to Advanced Machining Optimization2025-28-015602/07/2025
The intention of this exploration is to evolve an optimization method for the Electrochemical Machining (ECM) process on Haste alloy material, taking into account various performance characteristics. The optimization relies on the amalgamation of the Taguchi method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Haste alloy is extensively utilized in the aerospace, nuclear, marine, and car sectors, specifically in situations that are prone to corrosion. The experimental trials are organized based on Taguchi's principles and involve three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This examination examines performance indicators, including the pace at which material is removed and the roughness of the surface. It also includes geometric factors such as overcut, shape, and tolerance for orientation. The results suggest that the rate at which the feed is supplied is the most influential element affecting the necessary performance standards
Pasupuleti, Thejasree, Natarajan, Manikandan, Ramesh Naik, Mude, Somsole, Lakshmi Narayana, Silambarasan, R
Technical Paper
Optimization of Fused Deposition Modeling Using Taguchi-Based Grey Relational Analysis for TPU Used in Auto Parts2025-28-015802/07/2025
Fused Deposition Modeling (FDM) is a highly adaptable additive manufacturing method that is extensively employed for creating intricate structures using a range of materials. Thermoplastic Polyurethane (TPU) is a highly versatile material known for its flexibility and durability, making it well-suited for use in industries such as footwear, automotive, and consumer goods. Hoses, gaskets, seals, external trim, and interior components are just a few of the many uses for thermoplastic polyurethanes (TPU) in the automobile industry. The objective of this study is to enhance the performance of Fused Deposition Modeling (FDM) by optimizing the parameters specifically for Thermoplastic Polyurethane (TPU) material. This will be achieved by employing a Taguchi-based Grey Relational Analysis (GRA) method. The researchers conducted experimental trials to examine the impact of key FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical responses
Pasupuleti, Thejasree, Natarajan, Manikandan, Ramesh Naik, Mude, Silambarasan, R, D, Palanisamy
Technical Paper
Comparative Study to Identify and Bridge the Gap between Physical and Virtual Durability Testing on a Real Fatigue Acceleration Track and Its Digital Twin of the Vehicle/Surface2025-28-006502/07/2025
India has seen a significant boost in automotive research and development, specific to Vehicle Dynamics active safety systems and ADAS. To develop these systems, without excessive reliance on full working prototypes, vehicle manufacturers are relying on virtual models to better fine tune the design parameters. For this, there is a real requirement of digital twins of the proving grounds. This virtual testing surfaces will help in reducing test costs, test times and increase iteration counts, leading to fine-tuned prototype vehicle and finally a market leading product. National Automotive Test Tracks (NATRAX) is already playing a crucial role in the testing and development of these technologies, on its test tracks. Recognizing the need to assist in virtual testing for Indian automotive manufacturers, NATRAX is taking steps to develop virtual proving grounds to complement physical testing and reduce the development time. This paper targets a comparative analysis of dynamic parameters
S J, Srihari, Umorya, Divyansh, Patidar, Deepesh, Jaiswal, Manish
Technical Paper
Investigating Mechanical Properties of Jute Fiber and Alumina-Reinforced Epoxy Composites: Application of Taguchi and Grey Analysis for Automotive Components2025-28-011302/07/2025
Natural fiber composites (NFC’s) have considerable promise for a wide range of technological applications due to their exceptional features, which include notable weight reduction, high strength, and affordability. The aforementioned materials are also biodegradable and sustainable, which makes them appealing for use in sustainable engineering methods. This research focuses on evaluating the mechanical features of jute fiber and Al₂O₃ particle fortified polymer composites, exploring their potential for advanced engineering uses. The Taguchi technique is used with a L9 orthogonal array, integrating three-level, three-parameter approach, to systematically examine potential combinations of process variables in the manufacturing of these polymer composites. The primary goal is to optimize the mechanical attributes of the composites, which include tensile modulus, tensile stress, and weight percentage increase. Detailed investigations are conducted to interpret the effects of these process
Somsole, Lakshmi Narayana, Natarajan, Manikandan, Pasupuleti, Thejasree, Katta, Lakshmi Narasimhamu, Vivekananda, Soma
Technical Paper
Data-Driven Optimization of Titanium Grade 7 Machining for Automotive Applications2025-28-014302/07/2025
Electrochemical machining (ECM) is a highly efficient method for creating intricate structures in materials that conduct electricity, irrespective of their level of hardness. With the rising demand for superior products and the necessity for quick design modifications, decision-making in the industrial sector becomes increasingly complex. This study specifically examines Titanium Grade 7 and suggests creating prediction models through regression analysis to estimate performance measurements in ECM. The experiments are formulated based on Taguchi's ideas, utilizing a multiple regression approach to deduce mathematical equations. The Taguchi method is utilized for single-objective optimization in order to determine the ideal combination of process parameters that will maximize the material removal rate. ANOVA is a statistical method used to determine the relevance of process factors that affect performance measures. The suggested prediction technique for Titanium Grade 7 exhibits
Natarajan, Manikandan, Pasupuleti, Thejasree, Kumar, V, Krishnamachary, PC, Somsole, Lakshmi Narayana, Silambarasan, R
Technical Paper
Structural Analysis of Two-Wheeler Handlebars under Varied Loads2025-28-005302/07/2025
This study presents a comprehensive structural analysis of a two-wheeler handlebar subjected to various loading conditions, aiming to evaluate its strength, durability, and safety. During operation, two-wheelers encounter multiple forces, making the handlebar a critical component for rider control and safety. The analysis begins by investigating the different types of loads experienced during typical riding scenarios, including static loads when the bike is stationary, and dynamic loads arising from rider movements, braking, and handling. The primary objective is to understand how these loads impact the handlebar's structural integrity. To achieve this, critical load cases are identified and categorized. Braking loads, which apply force primarily in the forward direction due to deceleration, are examined. Manhandling loads are analyzed to understand the multidirectional forces acting on the handlebar during transportation and parking. Additionally, vertical loads are assessed
Prajapati, Akash, Rathore, Avijit Singh, Bhaskara Rao, Lokavarapu
Technical Paper
Optimization of Vibrational Characteristics Using Taguchi Method for CNT Reinforced Composite Plates2025-28-017402/07/2025
The integration of carbon nanotubes (CNT) into composite materials has revolutionized various high-performance industries, including aerospace, marine, and defense, for their exceptional thermal, mechanical, and electrical properties. The critical nature of these applications demands precise control over the manufacturing process to ensure the optimal performance of the CNT-reinforced composites. This study employs the Taguchi approach to systematically investigate and determine the optimal proportion of CNT volume fraction, fiber volume fraction, and stacking sequence in composite materials to achieve the optimal fundamental frequency. The Taguchi method, known for its efficiency in optimizing design parameters with a minimal number of experiments, enables the identification of the most influential factors and their optimal levels for enhancing material properties. Our findings demonstrate that the proper arrangement and proportioning of these components significantly improve the
B, Srivatsan, Balakrishna Sriganth, Pranav, Bhaskara Rao, Lokavarapu, Biswas, Sayan
Technical Paper
Multi-Objective Optimization for Contemporary Drilling of Nimonic Alloy Using Taguchi-Grey Relational Analysis2025-28-005002/07/2025
The objective of this research is to develop an optimization strategy for the Electrochemical Drilling process on Nimonic alloy material, taking into account various performance factors. The optimization strategy relies on the integration of the Taguchi method with Grey Relational Analysis (GRA). Nimonic is extensively utilized in aerospace, nuclear, and marine industries, specifically in situations that are prone to corrosion. The experimental trials are structured based on Taguchi's principle and encompass three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This inquiry examines performance indicators like the rate of material removal, surface roughness, as well as geometric parameters such as overcut, shape, and orientation tolerance. Based on the investigation, it is determined that the feed rate is the primary factor that directly affects the intended performance criteria. In order to enhance the accuracy of predictions, multiple regression
Pasupuleti, Thejasree, Natarajan, Manikandan, D, Palanisamy, Silambarasan, R, Krishnamachary, PC
Technical Paper
Thermal Buckling Analysis of Axially Layered Aluminium Silicon Nitride Functionally Graded Thin Beam using Taguchi Method2025-28-017202/07/2025
This research examines the thermal instability of slender beams composed of functionally graded materials (FGMs), with a specific focus on their suitability for engine hood components. The FGM combines the durability of aluminum with the heat tolerance of silicon nitride. The study aims to determine the maximum temperature the beam can withstand without buckling under various support conditions, simulating the uneven heat distribution experienced by engine hoods in actual use. The FGM structure comprises four longitudinally arranged layers, where the ceramic and metallic components gradually shift across the thickness. Finite element modeling software (ANSYS) is utilized to examine the buckling response under diverse temperature conditions. To enhance the thermal performance of the engine hood panel, the Taguchi L9 orthogonal array methodology is employed utilizing Minitab 19 software. The first four layers of the FGM beam are defined as process variables, while the critical buckling
Pawale, Deepak, Bhaskara Rao, Lokavarapu
Technical Paper
Investigating the Influence of Fiber Orientation on the Natural Frequency of Laminated Composite Plates2025-28-018302/07/2025
This study investigates the frequency response characteristics of laminated composite rectangular plates, focusing on the influence of fiber orientation. The composite plates, composed of 12 layers of glass fiber reinforced polymer composites (GFRP), were chosen for their superior mechanical properties and broad applicability in engineering fields, including the automotive sector. In automotive engineering, these composites are valued for their lightweight properties and high strength, contributing to enhanced performance and fuel efficiency. The analysis employed a combination of finite element methods and Taguchi experimental design techniques to understand how fiber orientation affects the dynamic behavior of these plates. To systematically explore the impact of fiber orientation on the frequency response, the study utilized Taguchi's orthogonal array design. Specifically, the L9 (3^3) and L16 (4^4) orthogonal arrays were employed to structure the experimental runs effectively
N, Suhas, C V, Prasshanth, U, Anish Kumar, Bhaskara Rao, Lokavarapu
Technical Paper
Degradation Analysis of Aged Fuel Cell Stack via Polarization Change Curve2025-01-709001/31/2025
A 20-cell self-humidifying fuel cell stack containing two types of MEAs was assembled and aged by a 1000-hour durability test. To rapidly and effectively analyze the primary degradation, the polarization change curve is introduced. As the different failure modes have a unique spectrum in the polarization change curve, it can be regarded as the fingerprint of a special degradation mode for repaid analysis. By means of this method, the main failure mode of two-type MEAs was clearly distinguished: one was attributed to the pinhole formation at the hydrogen outlet, and another was caused by catalyst degradation only, as verified by infrared imaging. The two distinct degradation phases were also classified: (i)conditioning phase, featuring with high decay rate, caused by repaid ECSA change from particle size growth of catalyst. (ii) performance phase with minor voltage loss at long test duration, but with RH cycling behind, as in MEA1. Then, an effective H2-pumping recovery is conducted
Pan, Chenbing, Wu, Hailong, Ruyi, Wang
Technical Paper
Formulation of Power Spectral Density of Fuel Cell Stacks in Different Vehicle Models Based on Road Driving Conditions2025-01-708301/31/2025
The durability of fuel cell vehicle (FCV) has always been one of the key factors affecting its large-scale application. However, the durability test methods of FCV and its key components, fuel cell stack (FCS), are incomplete all over the world, especially the lack of vibration test method on FCV. Focused on the FCS, this paper collects the road load spectrum of different vehicle models in their typical working conditions, so as to obtain the power spectral density of FCS of different vehicle models, which is used as the input signal of durability test. Through the FCS testing and analysis of fuel cell passenger car, bus, tractor and cargo van, the results show that the vibration intensity in three directions of FCS of different models is basically less than that of power battery, and only the FCS of fuel cell bus is greater than that of power battery in the direction of vehicle travel.
Wang, Guozhuo, Wu, Zhen, Guo, Ting, Wu, Shiyu, Liang, Rongliang, Nie, Zhenyu
Technical Paper
Fault Diagnosis Strategy for Proton Exchange Membrane Fuel Cells Based on PSO-BP Neural Network Using Particle Swarm Optimization Algorithm2025-01-708501/31/2025
This paper presents a fault diagnosis strategy that integrates model-based and data-driven approaches for a 115 kW proton exchange membrane fuel cell used in vehicles. First, a stack subsystem model was developed in the MATLAB/Simulink platform based on the working principles and structure of PEMFC, and validated with experimental data. Subsequently, faults in the air and hydrogen inlet pipelines were simulated, and the resulting fault data were subjected to preprocessing steps, including cleaning, normalization, and feature extraction, to enhance the efficiency of subsequent data processing. Finally, a BP neural network optimized by particle swarm optimization was employed to achieve fault tree-based classification diagnosis. Experimental results indicate that the diagnosis accuracy of the BP neural network reached 96.04%, with an additional accuracy improvement of approximately 2.4% after PSO optimization.
Wang, Ze, Zhu, Shaopeng, Chen, Ping, Li, Congxin, Zhou, Wenhua
Technical Paper
Research on Accelerated Testing Method for Durability and Reliability Test Field of Fuel Cell Vehicles Based on User Association2025-01-707901/31/2025
Currently, the application scope of fuel cell vehicles is gradually expanding. There is currently no durability testing method for the entire vehicle level in its research and development design process. In this article, a certain fuel cell passenger car is taken as the research object. The load spectrum data of its key components is collected. A ‘user goal test field’ multi-channel multi-dimensional load correlation optimization model is established. The goal is to minimize the difference in pseudo damage of special components such as the fuel cell vehicle stack structure under the user’s full life cycle target load and the test field test load. The characteristics of the multi-dimensional load of the fuel cell components corresponding to the optimized solution in the rainflow distribution and frequency domain distribution are calculated. And a durability reliability acceleration testing specification for fuel cell vehicle test fields for special components such as the stack structure
Wu, Shiyu, Guo, Ting, Wang, Yupeng, Wu, Zhen, Wang, Guozhuo
Technical Paper
Utilizing High-Performance Thermoplastics to Improve Durability and Efficiency in Automotive Instrument Panels2024-01-524501/28/2025
The present research explores the potential of high-performance thermoplastics, Polymethyl Methacrylate and Polyurethane, to enhance the passive safety of automotive instrument panels. The purpose is to evaluate and compare the passive safety of these two materials through the conduct of the Charpy Impact Test, Tensile Strength Test, and Crush Test —. For this, five samples were prepared in the case of each material via injection moulding, which enabled reliability, and consistency of the findings. As a result, it was found that in the case of the Charpy Impact Test, the average impact resistance varies with PMMA exhibiting a level of 15.08 kJ/m2 as opposed to the value of 12.16 kJ/m2 for PU. The Tensile Strength Test produced the average tensile strength of 50.16 for PMMA and 48.2 for PU, which implied superior structural integrity under tension for the first type of thermoplastic. Finally, the Crush Test showed that PMMA is more resistant to crushes on average than PU with the
Natrayan, L., Kaliappan, Seeniappan, Mothilal, T., Balaji, N., Maranan, Ramya, Ravi, D.
Technical Paper
Performance Specification Anti-Seize Thread Compound, High Temperature - Copper OnlyAMS3050/1 (Current)01/22/2025
The foundation specification (AMS3050) and this category specification (AMS3050/1) cover anti-seize greases conforming to the requirements but using the anti-seize ingredient Copper only.
AMS M Aerospace Greases Committee
Material Specification
Battery Electric Vehicle Design Specifications to Overcome Barriers in Developing Countries2024-36-018912/20/2024
The path towards clean mobility points in the direction of battery electric vehicles (BEVs) as a possible transportation solution. Despite a growing market penetration worldwide, emerging countries are struggling to successfully adopt BEV with current vehicle models. The literature presents an embracing discussion about BEV barriers but lacks into suggesting practical actions into BEV design. Based on a product development methodology and value analysis, this research aims to review factors holding back the BEV adoption in developing countries and to apply these factors into BEV features and design specifications. The literature was systematically reviewed based on the Brazilian case scenario to cast customer requirements for numerical evaluation through the Mudge Method. These were later translated into design requirements and ranked according to their relative importance with the quality function deployment (QFD). The results show that vehicle safety, pricing, and range anxiety are
Colpo, Leonardo R., Nora, Macklini Dalla, Romano, Leonardo N., Glufke, Ronaldo M., Rech, Cassiano
Technical Paper
Methodology to Obtain the Operation Reaction Loads in Automotive Fuel Filler Door2024-36-010712/20/2024
During the development phase of any product, it is crucial to ensure functionality and durability throughout their whole lifecycle. Physical tests have been traditionally used as the main tool to evaluate the durability of a product, especially in the automotive industry. And the evolution of computational methods combined with the Engineering Fundamentals allowed Computer Aided Engineering (CAE) simulations to predict failures in considering different conditions without building a prototype to perform a test. The use of virtual product validation using CAE simulations leads to product design flexibility on early development phase and both development costs and time reduction. This paper presents a methodology for computing the operation reaction loads in an automotive fuel filler door, which is an input needed to virtually validate the subsystem in terms of durability. The methodology is based on rigid body motion assumptions and the result shows good accuracy when comparing the
Pereira, Rômulo Franco, Espinosa-Aguilar, Jonathan, Silva, Lucas, Sarmento, Alisson, Chou, Chun Heng
Technical Paper
Evaluation of Superficial Damage of Mechanical Components through Digital Image Analysis Using Deep Learning Framework2024-36-003412/20/2024
Mechanical component failure often heralds superficial damage indicators such as color alteration due to overheating, texture degradation like rusting or false brinelling, spalling, and crack propagation. Conventional damage assessment relies heavily on visual inspections performed by technicians, a practice bogged down by time constraints and the subjective nature of human error. This research paper delves into the integration of deep learning methodologies to revolutionize surface damage evaluation, addressing significant bottlenecks in diagnostic precision and processing efficiency. We detail the end-to-end process of developing an intelligent inspection system: selecting appropriate deep learning architectures, annotating datasets, implementing data augmentation, optimizing hyperparameters, and deploying the model for widespread user accessibility. Specifically, the paper highlights the customization and assessment of state-of-the-art models, including EfficientNet B7 for
Cury, Rudoniel, Gioria, Gustavo, Chandrasekaran, Balaji
Technical Paper
AI-Driven Diagnostic System for Vehicles: Leveraging AI for Accurate and Efficient Automotive Problem Solving2024-01-522512/10/2024
Traditional vehicle diagnostics often rely on manual inspections and diagnostic tools, which can be time-consuming, inconsistent, and prone to human error. As vehicle technology evolves, there is a growing need for more efficient and reliable diagnostic methods. This paper introduces an innovative AI-based diagnostic system utilizing Artificial Intelligence (AI) to provide expert-level analysis and solutions for automotive issues. By inputting various details such as the vehicle’s make, model, year, mileage, problem description, and symptoms, the AI system generates comprehensive diagnostics, identifies potential causes, suggests step-by-step repair solutions, and offers maintenance tips. The proposed system aims to enhance diagnostic accuracy and efficiency, ultimately benefiting mechanics and vehicle owners. The system’s effectiveness is evaluated through various experiments and case studies, showcasing its potential to revolutionize vehicle diagnostics.
Sasikala, T., Swathi, B., Raj, J. Joshua Daniel, Shetty, G. Shreyas, Didagur, Darshan
Technical Paper
Impact of Lean Manufacturing Strategies and Success Factors on Performance Improvement—A Case Study05-18-02-001612/10/2024
LM (Lean manufacturing) is the manufacturing strategy focused on continuous improvement of manufacturing operations. This study has been carried out in manufacturing industry of northern India to assess important success factors, LM strategies applied, and important benefits of both LM strategies and approach. Questionnaire survey has been performed to achieve the desired objectives. Results indicated that manufacturing organizations have great affinity for LM strategies viz. small incremental improvements (kaizen) for strategic success. Production rates are highly improved after implementing LM approach. Mediating role of every success factor have been measured using regression analysis and structural equation modeling. Moreover, correlation shows the highly significant relations between LM strategies and benefits of the LM approach.
Kumar, Rajesh, Kumar, Ashwini, Kumar, Rajender
Journal Article
An Innovative Method to Measure Tapered Roller Bearing Preload in Manual Transmission & Identification of Crucial Influencing Parameters2024-28-019712/05/2024
In manual transmission, bearing preload is a vital factor for optimum durability and performance of tapered roller bearings (TRB). To achieve better optimization of bearing preload, a precise measurement method is a minimum requisite. This technical paper investigates multiple ideas and develops a novel methodology for accurate bearing preload measurement, overcoming the challenges produced by the complexity of transmission design. This paper provides a systematic approach to bearing preload measurement in manual transmission along with identification of key parameters responsible for influencing bearing preload, such as rigidity and fit of the components. A comprehensive experimental study at both part level and system level was conducted to quantify the effects of above-mentioned parameters on preload and transmission performance. Furthermore, the paper explores the effect of bearing preload optimization on the durability performance of the transmission unit.
Gaurav, Kumar, Kumar, Arun, Singh, Maninder Pal, Dhawan, Soumil, Singh, Kulbir, Kumar, Krishan, Singh, Manvir
Technical Paper
Comparative Analysis of BIW Subassembly Simulation Techniques AutoForm vs LS-DYNA2024-28-016912/05/2024
Assembly simulation plays a pivotal role in predicting and optimizing the distortion of an assembly, particularly in the automotive industry where precision and efficiency are paramount. In BIW parts assembly, factors such as clamping, mechanical & thermal joining, and loading direction are important. These factors affect the quality of the final assembly. Predicting and optimizing these parameters in the early design stage can help reduce development time, cost and improve the quality of the final product. Currently, LS-DYNA is used for closures like doors, hoods, and fenders. However, the pre-processing, computation and post-processing time is significantly high in LS-DYNA making it challenging to use for the Entire BIW. Employing a comprehensive approach, authors assess the distortion results, preprocessing, calculation, and post-processing time of both simulation techniques. Notably, the study reveals that AutoForm offers over 50%-time savings across all stages compared to LS-DYNA
Talawar, Vaishnavchandan, Nalam, Swaroop Raju, Dhanajkar, Narendra, Kumar, Ajay, Pasupathy, Vivekanand, Chava, Seshadri
Technical Paper
Leveraging Welding Spot Quality Control Using Camera Vision System2024-28-026412/05/2024
Spot welds are integral to automotive body construction, influencing vehicle performance and durability. Spot welding ensures structural integrity by creating strong bonds between metal sheets, crucial for maintaining vehicle safety and performance. It is highly compatible with automation, allowing for streamlined production processes and increased efficiency in automotive assembly lines. The number and distribution of spot welds directly impact the vehicle's ability to withstand various loads and stresses, including impacts, vibrations, and torsion. Manufacturers adhere to strict quality control standards to ensure the integrity of spot welds in automotive production. Monitoring spot weld count and weld quality during manufacturing processes through advanced inspection techniques such as Image processing by YOLOv8 helps identify the number of spots and quality that could compromise safety. Automating quality control processes is paramount, and machine vision offers a promising
Kadam, Shubham Narayan, Dolas, Aniket, Mishra, Jagdish
Technical Paper
Vehicle Underbody Grommets Detection Using Computer Vision and Co-ordinate System2024-28-019012/05/2024
Manual installation of vehicle underbody Grommets is tedious task which sometimes results in incomplete & inaccurate installation. Based on process quality guidelines, this comes under potential defect category at End of line inspection area for which few hours of manual efforts are required for identifying location of error & doing rework activity. Existing deep learning & image comparison method falls short in identifying error location. To overcome this challenge, deep learning algorithm with co-ordinate system developed which comprises of identifying class or category of entities present in test and reference image and indexing it as Grommet or Hole. This further comprises of determining 2D position in terms of X and Y co-ordinate of each indexed hole & Grommet between reference & test image. This approach results in precise comparison & identification of error in terms of missing or misplacing of Grommets which also offers significant saving in manual installation and rework
Dhumal, Abhishek Trimbak, Mishra, Jagdish, Tote, Anuj, Nurukurthi, Lakshmi, Kumar, Prakash
Technical Paper
Optimization and Regression Modeling of Additive Manufacturing (Fused Deposition Modeling) of PETG Material for Automobile Applications2024-28-023412/05/2024
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has become a highly promising method for creating intricate shapes using different materials. Polyethylene Terephthalate Glycol (PETG) is a highly utilized thermoplastic that is recognized for its exceptional strength, resistance to chemicals, and effortless processing. This study aims to optimize the process parameters of the FDM technique for PETG material using Taguchi Grey Relational Analysis (GRA). An empirical study was carried out to examine the impact of various FDM process parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on important outcome variables like dimensional accuracy, surface quality, and mechanical properties. The Taguchi method was used to systematically design a series of experiments, while GRA was used to optimize the process parameters and performance characteristics. The results unveiled the most effective parameter combinations for attaining
Natarajan, Manikandan, Pasupuleti, Thejasree, Kiruthika, Jothi, D, Palanisamy, Silambarasan, R
Technical Paper
Optimization of Wire Electrical Discharge Machining Parameters for Cupronickel Using Taguchi-Based Grey Relational Analysis2024-28-023512/05/2024
Wire Electrical Discharge Machining (WEDM) is an important method engaged to make intricate shapes in conductive materials like Cupronickel, which is well-known for its ability to resist corrosion and conduct heat. The intention of this exploration is to enhance the effectiveness and accuracy of Wire Electrical Discharge Machining (WEDM) for Cupronickel material by utilizing a Taguchi-based Grey Relational Analysis (GRA). The study examines the impact of WEDM parameters, specifically pulse-on time, pulse-off time, and discharge current, on key machining outcomes such as surface roughness (Ra), material removal rate (MRR). A comprehensive dataset is generated for analysis through a systematic series of experiments designed using the Taguchi method. Grey relational grades are assessed to measure the connections between the input parameters and machining responses, making it easier to determine the best parameter settings. The Taguchi-based GRA approach provides a systematic approach for
Pasupuleti, Thejasree, Natarajan, Manikandan, Kiruthika, Jothi, Ramesh Naik, Mude, Silambarasan, R
Technical Paper
Optimization of Wire Electrical Discharge Machining Parameters for SAE 1010 Material Using Taguchi-Based Grey Relational Approach2024-28-023112/05/2024
Wire Electrical Discharge Machining (WEDM) has attracted considerable attention in contemporary manufacturing because of its capacity to accurately form conductive materials. This study aims to optimize the parameters of Wire Electrical Discharge Machining (WEDM) for SAE 1010 material, which is a commonly used low-carbon steel. The Taguchi-based Grey Relational Approach (GRA) is employed for this purpose. The goal is to optimize machining efficiency and quality while minimizing production costs. The research methodology combines the Taguchi method for experimental design with the GRA for multi-response optimization. The Taguchi L27 orthogonal array is utilized to carry out experiments, taking into account three controllable factors: pulse-on time, pulse-off time, and discharge current. In addition, the performance characteristics to be optimized include surface roughness (Ra) and material removal rate (MRR). The experimental results are analyzed using the GRA (Grey Relational Analysis
Natarajan, Manikandan, Pasupuleti, Thejasree, Kiruthika, Jothi, Krishnamachary, PC, Silambarasan, R
Technical Paper
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