Browse Topic: Quality control

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Manufacturing Process Automation for Construction equipment Industry2025-28-0253To be published on 11/06/2025
The adoption of automation in construction equipment manufacturing is becoming increasingly vital for boosting efficiency, productivity, and safety. By taking over repetitive and hazardous tasks, automation helps mitigate labor shortages and allows human workers to concentrate on more complex activities. It ensures consistent quality control, reduces production costs, and provides the flexibility to adapt to changing market demands. Although the initial investment in automation technology can be substantial, the long-term benefits include enhanced workplace safety, lower error rates, and overall cost savings. This paper examines various automation technologies utilized in construction equipment factories and their role in driving the industry's future growth. Key Technologies discussed in this paper: 1. Material handling for construction equipment structures 2. Latest developments in robot welding for construction equipment 3. Cobot welding for high variety, low volume components 4
BHAKUNI, TANUJ, Bhorge, Pankaj, Saseendran, Unnikrishnan
Transformative Deep Learning for Image Colorization with Machine Learning-Based Classification2025-28-0317To be published on 11/06/2025
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 existing grayscale 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
Khalid, Maaz, Akarte, Anurag, Kale, Aniket, Rajmane, Gayatri, Nalawade, Komal
Comprehensive Warranty Data Analytics: A Blend of Conventional & Advanced Methods2025-28-0299To be published on 11/06/2025
In today’s competitive landscape, industries are relying heavily on the use of warranty data analytics techniques to manage and improve the warranty processes. Warranty analytics is important since it provides valuable insights into product quality and reliability. It must be noted here that by systematically looking into the warranty claims and related information, industries can identify patterns and trends that indicate potential issues with the products. This analysis helps in early detection of defects, enabling timely corrective actions that improve product performance and customer satisfaction. This paper introduces a comprehensive framework that combines conventional methods with advanced machine learning techniques to provide a multifaceted perspective on warranty data. The methodology leverages historical warranty claims and product usage data to predict failure patterns, identify root causes, and optimize warranty policies. By integrating these diverse methods, the framework
Quadri, Danishuddin S.F., Soma, Nagaraju
Technology Driven Solutions for Effective Tool Management.2025-28-0249To be published on 11/06/2025
IoT is revolutionizing the asset tracking industry, transforming it from manual entries in spreadsheets and logs to real-time, data-driven, foolproof solutions that boost manufacturing efficiency. Technical advancements are occurring in the IOT architecture. Leveraging a combination of cost-effective sensors such as LoRa -WAN and UWB provides data precision and accuracy by replacing traditional benchmark hardware solutions. Protocols like MQTT and Kafka enhance the data connectivity layer, enabling rapid data flow and logging, instantaneous insights, and agile decision-making. In the context of manufacturing, real-time indoor tracking ensures that equipment, tools, and products are located more accurately, resulting in improved operational matrices like productivity, availability, etc. This aligns with digital LEAN manufacturing principles such as Continuous Improvement (CI), Equipment Utilization factor, and just-in-time inventory management.
Patel, Shravani Prashant
A Strategic TQM Approach to Enhance Passenger Cabin Comfort Using T-Matrix2025-28-0423To be published on 10/30/2025
This study demonstrates the application of the T-Matrix, a Total Quality Management (TQM) tool to improve thermal comfort in automotive climate control systems. Focusing on the commonly reported customer issue of insufficient cabin cooling, particularly relevant in hot and congested Indian driving conditions, the research systematically investigates 36 failure modes identified across the product lifecycle, from early design through production and post-sale customer usage. Root causes are first categorized using an Ishikawa diagram and then mapped using the T-Matrix across three critical stages: problem creation, expected detection, and actual detection. This integrated approach reveals process blind spots where existing validation and inspection systems fail to catch known risks, particularly in rear-seat airflow performance and component variability from suppliers. By applying this TQM methodology, the study identifies targeted improvement actions such as improved thermal targets
Jaiswara, Prashant, Kulkarni, Shridhar, Deshmukh, Ganesh, Nayakawadi, Uttam, Joshi, Gaurav, Shah, Geet, Jaybhay, Sambhaji
A Novel Simulation Method for Vehicle Brake Wear Emissions2025-01-0361To be published on 09/15/2025
The effective reduction of particulate emissions from modern vehicles has shifted the focus toward emissions from tire wear, brake wear, road surface wear, and re-suspended particulate emissions. To meet future EU air quality standards and even stricter WHO targets for PM2.5, a reduction in non-exhaust particulate (NEP) emissions seems to be essential. For this reason, the EURO 7 emissions regulation contains limits for PM and PN emissions from brakes and tire abrasion. Graz University of Technology develops test methods, simulation tools and evaluates technologies for the reduction of brake wear particles and is involved in and leads several international research projects on this topic. The results are applied in emission models such as HBEFA (Handbook on Emission Factors). In this paper, we present our brake emission simulation approach, which calculates the power at the wheels and mechanical brakes, as well as corresponding rotational speeds for vehicles using longitudinal dynamics
Landl, Lukas, Ketan, Enis, Hausberger, Stefan, Dippold, Martin
DLR Tire and Road Wear Particle Emission Testing Methodology–Collection System Influence and Repeatability Assessments2025-24-009209/07/2025
Tire and road wear particles (TRWP) have emerged as air quality hazardous matters and significant sources of airborne microplastic pollution, contributing to environmental and human health concerns. Regulatory initiatives, such as the Euro 7 standards, emphasize the urgent need for standardized methodologies to quantify TRWP emissions accurately. Despite advancements in measuring tire abrasion rates, critical gaps persist in the characterization of airborne TRWP, particularly regarding the influence of collection system design and influencing parameters on measurement accuracy and repeatability. This study addresses these challenges by designing a controlled methodological framework that aims to minimize the influencing effects and ensure comparability in TRWP emission quantification results. At the German Aerospace Center (DLR) dynamometer testbench in Stuttgart, Germany, a methodical framework was established to ensure the repeatability and comparability of TRWP measurements
Celenlioglu, Melis Seren, Epple, Fabius, Reijrink, Nina, Löber, Manuel, Reiland, Sven, Vecchi, Roberta, Philipps, Franz
Introduction to Technical Standards1352408/07/2025
This video series brought to you by SAE International will show you what a standard is, how to interpret what you're reading, and how to differentiate technical standards from other information types.
Patterson, Lori
Leaf Springs in Focus: Integrated Validation of Material, Process, and Performance in Mechanical Suspensions2025-36-031208/01/2025
The continuous improvement of validation methodologies for mobility industry components is essential to ensure vehicle quality, safety, and performance. In the context of mechanical suspensions, leaf springs play a crucial role in vehicle dynamics, comfort, and durability. Material validation is based on steel production data, complemented by laboratory analyses such as tensile testing, hardness measurements, metallography, and residual stress analysis, ensuring that mechanical properties meet fatigue resistance requirements and expected durability. For performance evaluation, fatigue tests are conducted under vertical loads, with the possibility of including "windup" simulations when necessary. To enhance correlation accuracy, original suspension components are used during testing, allowing for a more precise validation of the entire system. Additionally, dynamic stiffness measurements provide valuable input for vehicle dynamics and suspension geometry analysis software, aiding in
Zahn, André N., Graebin, Matheus, Malacarne, Rodrigo, Toniolo, Juliano C.
Manufacturing and Inspection Standards for Preformed Packings (O-Rings)AS871B (Current)07/16/2025
This specification controls surface condition, manufacturing defects and inspection requirements, and defines methods of measurement for elastomeric toroidal sealing rings (O-rings) for static (including gasket) applications.
A-6C2 Seals Committee
Methodology for Fast-Running, Time-Resolved Simulation of Non-Exhaust Particle Emissions from Brake Wear Abrasion2025-01-027507/02/2025
Non-exhaust particle emissions, particularly those generated by brake wear, are a significant source of fine particulate matter in urban environments. These emissions contribute to air pollution and pose serious health risks, particularly in densely populated areas. While vehicle exhaust emissions have been extensively studied and regulated, the contribution of non-exhaust sources, including brake wear, remains a critical factor in air quality management. This paper presents a novel methodology for fast-running, time-resolved simulation of non-exhaust particle emissions, specifically those from brake wear abrasion. A 3D CFD model computes the turbulent flow field around the disc brake. The resulting information on the convective air cooling is applied as boundary conditions on a 3D thermal model. This thermal simulation setup is compared and verified with experimental data from literature. The 3D numerical models produce data and boundary conditions for an efficient 1D numerical
Herkenrath, Ferris, Lückerath, Moritz, Günther, Marco, Pischinger, Stefan
Grease: Wide Temperature Range Lithium or Lithium Complex Thickened for Aircraft Wheel BearingsAMS3058B (Current)06/30/2025
This specification covers grease for use on aircraft wheel bearings. It also defines the quality control requirements to assure batch conformance and materials traceability and the procedures to manage and communicate changes in the grease formulation and brand. This specification invokes the Performance Review Institute (PRI) product qualification process. Requests for submittal information may be made to the PRI at the address in 2.2, referencing this specification. Products qualified to this specification are listed on a qualified products list (QPL) managed by the PRI. Additional tests and evaluations may be required by individual equipment builders before a grease is approved for use in their equipment. Approval and/or certification for use of a specific grease in aero and aero-derived marine and industrial applications is the responsibility of the individual equipment builder and/or governmental authorities and is not implied by compliance with or qualification to this
AMS M Aerospace Greases Committee
Castings, Leaded Bronze, Sand and Centrifugal, 80Cu - 10Sn - 9.5Pb, As CastAMS4842G (Current)06/17/2025
This specification covers a leaded bronze in the form of sand and centrifugal castings (see 8.6).
AMS D Nonferrous Alloys Committee
Aluminum Bronze, Centrifugal and Chill Castings, 85Cu - 11Al - 3.6Fe, As CastAMS4870G (Current)06/17/2025
This specification covers an aluminum bronze alloy in the form of centrifugal and chill castings (see 8.5).
AMS D Nonferrous Alloys Committee
Multi-Objective Robust Optimization for a Parallel Link Steering System: A Six Sigma and Monte Carlo Approach2025-01-503606/03/2025
The steering system is one of the most important assemblies for the vehicle. It allows the vehicle to steer according to the driver’s intention. For an ideal steering system, the steering angle for the wheel on the left and right side should obey the Ackman equation. To achieve this goal, the optimization method is usually initiated to determine the coordinates of the hard points for the steering system. However, the location of hard points varies due to the manufacturing error of the components and wear caused by friction during their working life. To decrease the influence of geometry parameter error, and system mass, and improve the robust performance of the steering system, the optimization based on Six Sigma and Monte Carlo approach is used to optimize the steering system for an off-road vehicle. At last, the effect is proved by the comparison of other methods. The maximum error of the steering angle is decreased from 7.78° to 2.14°, while the mass of the steering system is
Peng, Dengzhi, Deng, Chao, Zhou, Bingbing, Zhang, Zhenhua
Cobots Repair and Refurbish Electronic Appliances for a Sustainable FutureTBMG-5321306/01/2025
Repartly, a startup based in Guetersloh, Germany, is using ABB’s collaborative robots to repair and refurbish electronic circuit boards in household appliances. Three GoFa cobots handle the sorting, visual inspection and precise soldering tasks enabling the company to enhance efficiency and maintain high quality standards.
Predictive Modeling of Surface Roughness, Tool Wear, and Cutting Temperature in High-Speed Turning under Sustainable Machining Environments05-19-01-000705/24/2025
The utilization of Inconel 718 is increasing daily in stringent operating conditions such as aircraft engine parts, space vehicles, chemical tanks, and the like due to its physical properties such as maintaining strength and corrosion resistance at higher temperature conditions. Besides, Inconel 718 is one of the difficult materials for machining because of maintaining its strength at elevated temperature, which generates higher cutting force leading to observed multiple tool wear mechanisms that affect the surface quality; lower thermal conductivity of materials produces high temperature generation that impacts the tool performance by reducing tool life. In addition, the presence of carbides and high hardness of IN 718 affects the machining performance. Therefore, in this view, this article describes the effect of cutting environments and machining parameters on the machining of Inconel 718 and optimizes the cutting conditions for sustainable machining. Three input parameters namely
Mane, Pravin Ashok, Dhawale, Pravin A., Nipanikar, Suresh, Khadtare, Avinash N.
Localisation of Ultra-Short Sound Emissions from Automotive Components by Using the Sound Field Scanning Method2025-01-009205/05/2025
Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras. A time resolution of less than 1ms eventually allows for the true localization of the initial and subsequent sound events as well as a clear separation of direct from
Rittenschober, Thomas
Research on Shift Sound Quality Control Strategy for Active Sound Generation System in Automobile2025-01-001905/05/2025
The active sound synthesis system of electric vehicles plays an important role in improving the sound perception and transmission of working condition information inside the vehicle. Nowadays, the active sound synthesis system inside the vehicle has become standard equipment in electric vehicles of major electric vehicle manufacturers to meet the user groups' demand for driving and riding experience. In order to enrich the driving experience of electric vehicles and automatic transmission vehicles, the sound performance should be close to the immersiveness and dynamic feedback brought by traditional manual transmission fuel vehicles. Based on the active sound synthesis algorithm in the car, this paper proposes an adaptive shift sound quality control strategy suitable for complex and changeable working conditions, with the aim of simulating the real shift sound of the engine. First, the motor speed offset is accurately calculated based on the transmission ratio of each gear of the
Zhou, Xilong, Liu, Zhien, Xie, Liping, Yu, Shangbo, Lu, Chihua, Gao, Xiang, Yongsheng, Wang
Implementing Lean Six Sigma in the Medical Device IndustryTBMG-5316305/01/2025
A continuous effort to improve reliability and efficiency of processes is at the forefront of any successful business. One methodology that can have a crucial impact in this effort is Lean Six Sigma (LSS), which aims to reduce variability and wasteful activities within a company’s processes, in turn leading to improvements in areas such as customer satisfaction, employee morale, regulatory compliance, and profitability. In the medical device industry, where a seemingly minor error could be life-threatening, LSS can play a pivotal role in patient safety. This article presents a case study illustrating the benefits of LSS for a medical device manufacturing company, as well as one of its key customers.
AESQ Quality Management System Requirements for Aero Engine Design and Production OrganizationsAS13100A (Current)04/14/2025
This SAE Aerospace Standard (AS) establishes supplemental requirements for 9100 and 9145 and applies to any organization receiving it as part of a purchase order or other contractual document from a customer. AS13100 also provides details of the reference materials (RM13xxx) developed by the SAE G-22 AESQ committee and listed in Section 2 that can also be used by organizations in conjunction with this standard.
G-22 Aerospace Engine Supplier Quality (AESQ) Committee
SPC based Critical Parameters Monitoring of Vendor Supplied Parts by Auto OEM for Quality Control2025-01-833404/01/2025
In Automobile manufacturing, maintaining the Quality of parts supplied by vendor is crucial & challenging. This paper introduces a digital tool designed to monitor trends for critical parameters of these parts in real-time. Utilizing Statistical Process Control (SPC) graphs, the tool continuously tracks Quality trend for critical parts and process parameters, predicting potential issues for proactive improvements even before parts are supplied. The tool integrates data from all Supplier partners across value chain into a single ecosystem, providing a comprehensive view of their performance and the parts they supply. Suppliers input data into a digital application, which is then analyzed in the cloud using SPC techniques to generate potential alerts for improvement. These alerts are automatically sent to both Suppliers 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
Sahoo, Priyabrata, Garg, Ishan, Rawat, Sudhanshu, Narula, Rahul, Gupta, Ankit, Bindra, Ritesh, Rao, Akkinapalli VN, Garg, Vipin
Material Selection of a Parcel Shelf for Structural Performance and Perceived Quality Improvement through an Assessment of a Wide Range of Composite and Sustainable Materials2025-01-824904/01/2025
This paper addresses the need for improved material selection in parcel shelves, a key component in passenger vehicles used to conceal the trunk area. The focus is on weight optimization, structural integrity, and perceived quality improvement using sustainable and ultra-lightweight composite materials. Traditional materials such as PET Woodstock, while durable, contribute significantly to vehicle weight, which is a drawback in the context of electric vehicles (EVs). The proposed composite material alternatives offer a high strength-to-weight ratio and have been shown to improve the load vs. deflection ratio, enhance aesthetics, and reduce manufacturing complexity and costs. This study outlines the testing and evaluation process of varying GSM and thicknesses of composite materials, demonstrating superior stiffness, reduced deflection under load, and enhanced ease of assembly. This work contributes to the ongoing efforts to achieve lightweighting, cost efficiency, and sustainability in
Kinthala, Nareen Kumar, Patnaik, Manga, Khandelwal, Mohit, Kakani, Phani Kumar, Palaniappan, Elavarasan
Structural Seam Weld Optimization with Efficient Approach of DFSS2025-01-824804/01/2025
In automotive engineering, seam welds are frequently used to join or connect various parts of structures, frames, cradles, chassis, suspension components, and body. These welds usually form the weaker 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 will present the case testimony to show the approach throughout
Qin, Wenxin, Li, Fan, Pohl, Kevin J., Pentapati, Venkat
Automated Analysis and Cleaning of Manufacturing Data: The Power of Automation Playbooks2025-01-833204/01/2025
High-efficiency manufacturing involves the transmission of copious amounts of data, exemplified both by trends in the automotive industry and advances in technology. In the automotive industry, products have been growing increasingly complex, owing to multiple SKUs, global supply chains and the involvement of many tier 2 / Just-In Time (JIT) suppliers. On top of that, recalls and incidents in recent years have made it important for OEMs to be able to track down affected vehicles based on their components. All of this has increased the need for OEMs to be able to collect and analyze component data. The advent of Industry 4.0 and IoT has provided manufacturing with the ability to efficiently collect and store large amounts of data, lining up with the needs of manufacturing-based industries. However, while the needs to collect data have been met, corporations now find themselves facing the need to make sense of the data to provide the insights they need, and the data is often unstructured
Jan, Jonathan, Preston, Joshua, Juncker, John
A Proposed RE-Method for Redesigning Damaged CAM Gears in Automotive Engines Using Image Processing and 3D CAD Model2025-01-863404/01/2025
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 projects 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
Ali, Salah H. R., Ehab, Eslam, Barakat, Ebrahim, Younes, Abdelrahman, Ali, Amr S.H.R.
Comparison of Gasoline Particulate Indices Using U.S. Market Gasoline Samples2025-01-844904/01/2025
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
The Logistic Lasso and Ridge Regression Algorithm-Based Airline Passenger Satisfaction Prediction Model2025-01-716803/19/2025
Airline passenger satisfaction is important for airline operation service quality management. When airline companies carry out advertisement campaigns or plan a marketing strategy, the resources and budgets are not unlimited. Thus, an airline can only focus on improving a few factors that drive passenger satisfaction. To understand the key satisfies for the young and the old adults, respectively, we leverage five airline passenger satisfaction methods to identify the key factors that explain the airline service satisfaction of different passengers. In particular, we investigate and compare the ridge and the Lasso regularization in terms of the resulting model’s sparsity and computational efficiency. The top three important factors that influence the old’s satisfaction are departure and arrival time convenience, legroom service, and baggage handling. Our findings indicate that the young people place a higher value on entertainment, while the old adults place a higher value on usefulness
Ma, Jie, Hu, Song, Wang, Haipeng
Probabilistic Analysis Approach to Evaluate Gear Tooth Strength in the Hypocycloid Engine03-18-02-001503/08/2025
This study introduces a probabilistic analysis approach to evaluate the gear tooth strength for the hypocycloid engines, which are particularly significant in internal combustion (IC) engine applications due to their unique design and critical requirements for both efficiency and durability. The research utilizes the stress–strength interference (SSI) theory within a “design for reliability” framework to develop a robust methodology for designing the internal gear mechanism required for the hypocycloid gear mechanism (HGM) engine, in accordance with American Gear Manufacturers Association (AGMA) standard gear rating practices. This approach incorporates probabilistic factors to address variations in HGM component parameters, gear material properties, and engine operational conditions. To validate the design and ensure accuracy, a finite element method (FEM)-based verification is employed, to identify potential failure points and enhance the overall reliability of the HGM engine. The
ElBahloul, Mostafa A., Aziz, ELsayed S., Chassapis, Constantin
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
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
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
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
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
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
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
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
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
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
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
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
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
Development of Lubricants Using Re-Refined Base Stocks—An Effort toward Circular Economy04-18-02-000812/06/2024
Re-refining of used lubricating oil is an economically attractive and effective recycling method that contributes significantly to resource conservation and environmental protection. The effective re-refining process of used lubricating oil undergoes thorough purification to remove contaminants and to produce high yield and good quality base oil suitable for reuse in lubricant formulation. Used lubricating oils have various hazardous materials, these can be processed with safe and efficient methods required to recover high-quality base oil products. Typically, used lubricating oil is a mixture of various types of additives, base oils, and viscometric grades as per the different types automotive and industrial applications. Re-refined base oils can be re-used to produce lubricants such as industrial and automotive lubricants like passenger car motor oils, transmission fluids, hydraulic oils, and gear oils. API classified base oils into two categories namely mineral base oils API Group I
Maloth, Swamy, Joshi, Ratnadeep S., Mishra, Gopal Swaroop, Samant, Nagesh N., Bhadhavath, Sanker, Seth, Sarita, Bhardwaj, Anil, Paul, Subinoy, Arora, Ajay Kumar, Maheshwari, Mukul
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
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
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
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
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
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
Product Governance and Management for Software-defined Battery Electric VehiclesEPR202402510/21/2024
In recent years, battery electric vehicles (BEVs) have experienced significant sales growth, marked by advancements in features and market delivery. This evolution intersects with innovative software-defined vehicles, which have transformed automotive supply chains, introducing new BEV brands from both emerging and mature markets. The critical role of software in software-defined battery electric vehicles (SD-BEVs) is pivotal for enhancing user experience and ensuring adherence to rigorous safety, performance, and quality standards. Effective governance and management are crucial, as failures can mar corporate reputations and jeopardize safety-critical systems like advanced driver assistance systems. Product Governance and Management for Software-defined Battery Electric Vehicles addresses the complexities of SD-BEV product governance and management to facilitate safer vehicle deployments. By exploring these challenges, it aims to enhance internal processes and foster cross
Abdul Hamid, Umar Zakir
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