Browse Topic: Production

Items (7,981)
Roller bearings are used in many rotating power transmission systems in the automotive industry. During the assembly process of the power transmission system, some types of roller bearings (e.g., tapered roller bearings) require a compressive preload force. Those bearings' rolling resistance and lifespan strongly depend on the preload set during the installation process. Therefore, accurate preload setting can improve bearing efficiency, increase bearing lifespan, and reduce maintenance costs over the life of the vehicle. A new method for bearing preload measurement has shown potential for high accuracy and fast cycle time using the frequency response characteristics of the power transmission system. One open problem is the design of the production controller, which relies on a detailed sensitivity study of the system frequency response to changes in the bearing and system design parameters. Recently, an analytical model was developed for multi-row tapered roller bearings that includes
Gruzwalski, DavidMynderse, James
The advance of regulatory emission standards for light-duty vehicles, trucks and motorcycles, coupled with rising sustainability concerns, particularly United Nations' Sustainable Development Goal 12 (responsible consumption and production), has created an urgent need for lighter, stronger, and more ecological materials. Polylactic acid (PLA), a biodegradable polymer derived from plant sources, offers promising mechanical tensile strength and processability. Nanocomposites, a solution that combines a base matrix with a nanoreinforcing filler, provides a path toward developing sustainable materials with new properties. Cellulose nanofibrils (CNF) are a valuable nanofiller obtained through industrial waste or vegetal fibers, offer a promising avenue for strengthening PLA-based materials. Additive manufacturing (AM) has gained popularity due to its ability to create complex parts, prototyping designs, and to evaluate new nanocomposite materials such as PLA/CNF, showing significant
de Oliveira, ViníciusHoriuchi, Lucas NaoGoncalves, Ana PaulaDe Andrade, MarinaPolkowski, Rodrigo
In-Mold Graining (IMG) is an innovative production technology applied to the skin wrapping of automotive interior components. In the design of automotive interior components of door panels and instrument clusters, to overcome process-related problems, such as the thinning of grain patterns and excessive reduction in thickness, simulation of the skin vacuum forming process is required. The Thermoplastic Olefin (TPO) skin material is investigated in this paper, and a viscoelastic mechanical model for this material is established. Dynamic Mechanical Analyzer (DMA) is utilized to perform scan for frequency and temperature, and the tested data is used to obtain key model parameters of the viscoelastic constitutive model. Based on the experimental data, the study explores how to calculate the relaxation time spectrum to describe the viscoelastic properties of TPO material during the vacuum forming process. Numerical simulation of the vacuum forming process of TPO material is conducted using
Chai, BingjiGuo, YimingXie, XinxingZhang, Qu
Wind tunnel calibration is necessary for repeatable and reproducible data for all industries interested in their output. Quantities such as wind speed, pressure gradients, static operating conditions, ground effects, force and moment measurements, as well as flow uniformity and angularity are all integral in an automotive wind tunnel’s data quality and can be controlled through appropriate calibration, maintenance, and statistical process control programs. The purpose of this technical paper is to (1) provide a basis of commonality for automotive wind tunnel calibration, (2) help customers and operators to determine the calibration standards best suited for their unique automotive wind tunnel and, (3) complement the American Institute of Aeronautics and Astronautics recommended practice R-093-2003(2018) Calibration of Subsonic and Transonic Wind Tunnels as specifically applied to the automotive industry. This document compiles information from various automotive wind tunnel customers
Bringhurst, KatlynnBest, ScottNasr Esfahani, VahidSenft, VictorStevenson, StuartWittmeier, Felix
Opening a tailgate can cause rain that has settled on its surfaces to run off onto the customer or into the rear loadspace, causing annoyance. Relatively small adjustments to tailgate seals and encapsulation can effectively mitigate these effects. However, these failure modes tend to be discovered relatively late in the design process as they, to date, need a representative physical system to test – including ensuring that any materials used on the surface flow paths elicit the same liquid flow behaviours (i.e. contact angles and velocity) as would be seen on the production vehicle surfaces. In this work we describe the development and validation of an early-stage simulation approach using a Smoothed Particle Hydrodynamics code (PreonLab). This includes its calibration against fundamental experiments to provide models for the flow of water over automotive surfaces and their subsequent application to a tailgate system simulation which includes fully detailed surrounding vehicle geometry
Gaylard, Adrian PhilipWeatherhead, Duncan
A new method for bearing preload measurement has shown potential for both high accuracy and fast cycle time using the frequency response characteristics of the power transmission system. One open problem is the design of the production controller, which relies on a detailed sensitivity study of the system frequency response to changes in the bearing and system design parameters. Recently, an analytical model was developed for multi-row tapered roller bearings that includes all appropriate bearing and power transmission system design parameters. During the assembly process, some of the parameters related to the roller positions cannot be controlled. These parameters include the actual position of the first roller compared to the vertical axis, the relative position of the rollers between the bearing rows, and others. This work presents a sensitivity analysis of the effects of those uncontrollable parameters on the analytical model. The sensitivity study determines the percentage change
Gruzwalski, DavidMynderse, James
Since aluminum alloys (AA) are widely used as structural components across various industries, higher requirements for shape-design, load-bearing, and energy-absorption capacity have been put forward. In this paper, we present the development of a numerical model, integrated with a compensation method, that effectively predicts processing defects in the bumper beam of a vehicle, resulting in a marked improvement in its forming quality. Specifically, different constitutive models are investigated for their applicability to the beam, enabling a precise evaluation of its structural performance under large deformation. The Johnson-Cook failure model is introduced to better characterize the fracture behavior of the beam under severe structural damage. The three-point bending experiment served as a rigorous examination, demonstrating good consistency between the experimental and simulation results. Furthermore, a prediction model for assessing the forming quality during the bending process
Zhang, ShizhenMeng, DejianGao, Yunkai
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, PriyabrataGarg, IshanRawat, SudhanshuNarula, RahulGupta, AnkitBindra, RiteshRao, Akkinapalli VNGarg, Vipin
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, JonathanPreston, JoshuaJuncker, John
Surface roughness is a key factor in different machining processes and plays an important role in ergonomics, assembly process, wear and fatigue life of components. Other factors like functionality, performance and durability of parts are also affected by surface roughness. Although maintaining an optimum surface roughness is a major challenge in many manufacturing industries. Surface roughness during machining depends upon machining parameters such as tool geometry, feed rate, depth of cut, rotational speed, lubrication, tool wear, etc. Tool vibrations during machining also have significant influence in surface roughness. In this work an attempt is made to predict the surface roughness of machined components made by the turning process by using machine learning of tool vibration signals. By varying different machining parameters and keeping other tooling and material properties same, a range of surface roughness values can be obtained. For each condition, corresponding tool vibration
S S, SafeerSadique, AnwarD, Navaneeth
Today’s agriculture demands increased productivity due to the higher cropping intensities. Agricultural field readiness for cultivation requires various operation in field resulting in delay in cultivation which lower down productivity. Therefore, field operation needs to be more efficient in terms of both input cost and time consumption. One way to achieve this is by performing multiple operations in a single tractor pass, utilizing the increased power available in modern Tractors. In some agricultural operations, implements need to be mounted on the front of the tractor. Therefore, designing a front three-point hitching system for the tractor is essential to meet various farming needs, allowing customers to perform multiple operations simultaneously. The use of a front three-point linkage better utilizes the potential of four-wheel drive, higher horsepower tractors. This paper focuses on the comprehensive design process for developing and validating a front hitch system for both
Kumar, YuvarajV, Ashok KumarPerumal, SolairajGaba, RahulRamdebhai, KaravadaraSubbaiyan, Prasanna BalajiM, Kalaiselvan
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly nature, affordability, and ease of processing. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) for PLA material using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The researchers performed experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including dimensional accuracy, surface finish, and mechanical properties. The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. The TOPSIS approach, a technique for making decisions
Natarajan, ManikandanPasupuleti, ThejasreeD, PalanisamyKatta, Lakshmi NarasimhamuSilambarasan, R
In recent years, Additive Manufacturing (AM), more especially Fused Deposition Modeling (FDM), has emerged as a very promising technique for the production of complicated forms while using a variety of materials. Polyethylene Terephthalate Glycol, sometimes known as PETG, is a thermoplastic material that is widely used and is renowned for its remarkable strength, resilience to chemicals, and ease of processing. Through the use of Taguchi Grey Relational Analysis (GRA), the purpose of this investigation is to improve the process parameters of the FDM technology for PETG material. In order to investigate the influence that several FDM process parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, have on significant outcome variables, such as dimensional accuracy, surface quality, and mechanical qualities, an empirical research was conducted. For the purpose of constructing the regression prediction model, the obtained dataset is used to make
Natarajan, ManikandanPasupuleti, ThejasreeShanmugam, LoganayaganKatta, Lakshmi NarasimhamuSilambarasan, RKiruthika, Jothi
Electrochemical machining (ECM) is a highly efficient method for creating intricate structures in materials that conduct electricity, irrespective of their level of hardness. Due to the growing need for superior products and the requirement for quick design adjustments, decision-making in production has become more complex. This study focuses on Titanium Grade 7 and suggests creating predictive models utilizing a Taguchi-grey technique to achieve multi-objective optimization in ECM. The trials are structured based on Taguchi's principles, utilizing Taguchi-grey relational analysis (GRA) to simultaneously maximize several performance indicators. This entails optimizing the pace at which material is removed, decreasing the roughness of the surface, and attaining precise geometric tolerances. ANOVA is used to assess the relevance of process variables that affect these measures. The suggested predictive technique for Titanium Grade 7 outperforms current models in terms of flexibility
Pasupuleti, ThejasreeNatarajan, ManikandanKumar, VSagaya Raj, GnanaKrishnamachary, PCSilambarasan, R
On one hand population is increasing while on the other area under cultivation has been decreasing resulting in increased stress on the productivity to meet the needs. India in particular has been witnessing lot many challenges in terms of mechanization, availability of skilled manpower, urban shift and increased revenue to Agri households from non-Agri streams, lesser participation of women in mechanization. Likeability of younger generations to choose agriculture has declined due to need of strenuous manual works. This paper discusses about the system developed for automating monotonous agricultural tractor operations that offers increased operator comfort and productivity while minimizing operator fatigue. The system uses Electronic Depth & Draft Control (EDDC) system combined with Wheel angle sensors to offer key functions such as auto side braking, implement lift, lower and PTO disengagement during headland turns and automatic reengagement of the above controls. Field tests have
M, Rojer DennyNatarajan, SaravananBaskar, Augustin
Electrochemical machining (ECM) is a highly efficient method for creating intricate structures in electrically conductive materials, irrespective of their hardness. Due to the growing need for superior products and quick design adjustments, decision-making in production has become increasingly complex. This study focuses on Titanium Grade 19 and proposes creating predictive models using a Taguchi-grey technique to achieve multi-objective optimization in ECM. The experiments are structured based on Taguchi's principles, utilizing Taguchi-grey relational analysis (GRA) to simultaneously optimize several performance indicators, including the material removal rate, surface roughness, and geometric tolerances. ANOVA is employed to assess the significance of process variables affecting these measures. The proposed predictive technique for Titanium Grade 19 outperforms current models in terms of flexibility, efficiency, and accuracy, providing enhanced capabilities for monitoring and control
Pasupuleti, ThejasreeNatarajan, ManikandanKrishnamachary, PCKatta, Lakshmi NarasimhamuSilambarasan, R
In response to rising emissions and pollutants, an alternative and environmentally friendly synthesis is gaining prominence on the energy sources. The leather industries generate substantial amount of waste and fleshing oil extracted from fleshing which is rich in lipids and presents a viable feedstock for biodiesel production. In this research work, Response Surface Methodology (RSM) is used to optimize the conversion of leather fleshing oil into biodiesel using three parameters such as operating temperature, reaction time, and molar ratio. Experiments were carried out to determine the most optimal conditions and the response on yield (%) and viscosity (mm2/s) based on a 17-run Box–Behnken Design matrix. Stochastic model parameters such as R2 (0.9715 and 0.9793), adjusted R2 (0.9349 and 0.9527), predicted R2 (0.8327 and 0.7656), and high F-values (26.52 and 36.78) of both responses (yield and viscosity) were found to be statistically significant and warranted model adequacy. ANOVA and
P, KanthasamySelvan, Arul MozhiP, Shanmugam
In order to give full play to the economic and environmental advantages of liquid organic hydrogen carrier(LOHC) technology in hydrogen storage and transportation as well as its technological advantages as a hydrogen source for hydrogen refueling station(HRS) supply, it promotes the change of hydrogen supply method in HRSs and facilitates its technological landing in the terminal of HRSs. In this paper, combining the current commercialization status of organic liquid technology and the current construction status of HRS in China, we establish a traditional long-tube trailer HRS model through Matlab Simulink, carry out modification on the existing process, maximize the use of the original equipment, and introduce the hydrogen production end of the station with organic liquid as an auxiliary hydrogen source. Research and design of the two hydrogen sources of gas extraction strategy and the station control strategy and the formation of Stateflow language model, to realize the verification
Huo, TianqingFeng, TianyuYang, FushengHuang, YeZheng, HuaanWang, BinFang, TaoWu, ZhenZhang, ZaoXiao
Metal bipolar plates are important components of fuel cells, playing a role in conducting electricity, gas, and heat during the operation of fuel cells. The sealing and joint quality of the bipolar plates have a significant impact on the performance and service life of fuel cell stacks. In actual production, laser technology is often used for welding bipolar plates, and the welding quality is ensured by laser process parameters when using the same equipment. Therefore, in order to further optimize the laser welding process of metal bipolar plates, this paper selects three laser parameters for single-factor analysis to evaluate the impact of each parameter on laser welding quality. The Box-Behnken design-response surface method is used for multi-factor analysis, with process parameters as inputs and weld quality parameters as outputs, to assess the sensitivity of each laser process parameter to laser welding quality, and to fit a nonlinear function. Based on the results, the optimal
Li, WeiChang, GuofengXu, HuashengHuang, Ziheng
The predictive torque control strategy is a very commonly used model predictive control strategy. At present, the research prospects of PTC in motor control are broad, but there are still certain limitations in the industrial application of PTC. In traditional prediction torque control, due to the inconsistent units of electromagnetic torque and stator magnetic flux, weight factors need to be introduced to balance the control effects of the two. However, due to the cumbersome and time-consuming process of determining weight factors, it is not conducive to industrial promotion. In order to solve the problem of weight factors, this paper studies a new torque prediction control strategy based on stator flux vector angle that can avoid weight factors on the basis of traditional torque prediction control. The overall process of the new strategy is to first derive the relationship between the angle between the stator voltage vector and the stator magnetic flux vector and the electromagnetic
Zhang, DongdongHuang, YasongDu, AnnanLin, Xiaogang
The development of hydrogen economy is an effective way to achieve peak carbon emission and carbon neutralization. Therein, the green production of hydrogen is a prerequisite to reach the goal of decarbonization. As an ideal route, water electrolysis has triggered intense responses under the strong support from policies, which further presenting a phenomenon of water electrolysis equipment manufactures competing to enter the market. However, the extensive growth mode is not conducive to a long term healthy development of the water electrolysis hydrogen production market where products can be sold without requiring compulsory inspection or quality inspection process due to the absence of laws and test & evaluation standards. Considering the market status and technology maturity, the main working principles and characteristics of alkaline water electrolysis (AWE) and proton exchange membrane (PEM) hydrogen production systems are summarized, and the test frameworks of the AWE and PEM
Jiao, DaokuanWang, XiaobingHao, Dong
In recent years, the amount of industrial sewage sludge awaiting treatment has continued to rise steadily, posing serious risks to human health and the ecological environment if mishandled. This study proposes a photothermal-driven supercritical water co-gasification of sludge-coal thermochemical synergistic conversion system for efficient hydrogen production. The main feature is that the medium-low temperature exothermic heating method uses concentrated solar energy to provide reaction heat for the co-gasification process. This approach synergistically converts solar energy into syngas chemical energy while meeting the heat demand of the co-gasification hydrogen production process. The results show that this co-gasification system for hydrogen production can achieve an energy efficiency of 56.82%. The sensitivity analysis shows that the molar flow rate of hydrogen increased from 44.02 kmol/h to 217.51 kmol/h as the gasification temperature increased from 500°C to 700°C. The concluded
Li, GuangyangXue, XiaodongWang, Yulin
This specification covers requirements for the superfinishing of High Velocity Oxygen/Fuel (HVOF) applied tungsten carbide thermal spray coatings.
AMS B Finishes Processes and Fluids Committee
Competitive companies constantly seek continuous increases in productivity, quality and services level. Lean Thinking (LT) is an efficient management model recognized in organizations and academia, with an effective management approach, well consolidated theoretically and empirically proven Within Industry 4.0 (I4.0) development concept, manufacturers are confident in the advantages of new technologies and system integration. The combination of Lean and I4.0 practices emerges from the existence of a positive interaction for the evolutionary step to achieve a higher operational performance level (exploitation of finances, workload, materials, machines/devices). In this scenario where Lean Thinking is an excellent starting point to implement such changes with a method and focus on results; that I4.0 offers powerful technologies to increase productivity and flexibility in production processes; but people need to be more considered in processes, in a context aligned with the Industry 5.0
Braggio, LuisMarinho, OsmarSoares, LuisLino, AlanRabelo, FábioMuniz, Jorge
The fuel economy performance of road vehicles is one of the most important factors for a successful project in the current automotive industry due to greenhouse effect gases reduction goals. Aerodynamics and vehicle dynamics play key roles on leading the automaker fulfill those factors. The drag coefficient and frontal area of the vehicle are affected by several conditions, where the ground height and pitch angle are very relevant, especially for pickup trucks. In this work, we present a combined study of suspension trim heights and aerodynamics performance of a production pickup truck, where three different loading conditions are considered. The three weight configurations are evaluated both in terms of ground height and pitch angle change considering the suspension and tires deflection and these changes are evaluated in terms of drag coefficient performance, using a Lattice-Boltzmann transient solver. Results are compared with the baseline vehicle at road speed condition, where both
Buscariolo, Filipe FabianTerra, Rafael Tedim
The automotive industry is facing unprecedented pressure to reduce costs without compromising on quality and performance, particularly in the design and manufacturing. This paper provides a technical review of the multifaceted challenges involved in achieving cost efficiency while maintaining financial viability, functional integrity, and market competitiveness. Financial viability stands as a primary obstacle in cost reduction projects. The demand for innovative products needs to be balanced with the need for affordable materials while maintaining structural integrity. Suppliers’ cost structures, raw material fluctuations, and production volumes must be considered on the way to obtain optimal costs. Functional aspects lead to another layer of complexity, once changes in design or materials should not compromise safety, durability, or performance. Rigorous testing and simulation tools are indispensable to validate changes in the manufacturing process. Marketing considerations are also
Oliveira Neto, Raimundo ArraisSouza, Camila Gomes PeçanhaBrito, Luis Roberto BonfimGuimarães, Georges Louis Nogueira
The goal of this research is to better understand the methodologies for manufacturing biodiesel worldwide and the main raw materials used in its production. We aim to compare the solutions established by relevant countries with those used in Brazil, identifying their advantages and disadvantages. Our primary areas of interest include the United States, Indonesia, and Europe, where we will analyze the solutions and, whenever possible, understand the commercial and political interests involved. We will highlight aspects related to sustainability in the production, transportation, and use of biodiesel. The methodology is based on research from recent publications and news, organized into graphs to facilitate analysis and comparison. Next, we will also examine the consequences of the solutions adopted in Brazil, envisioning future scenarios and recommended paths. In the short term, biodiesel is expected to be replaced by renewable diesel (also known as green diesel in some regions
Labigalini, Marcio RobertoBarreto, Gilmar
The goal of this work is to increase the accuracy and efficiency of hose cutting operations in small scale industries is by designing and building an automatic hose-cutting equipment. The device uses a computer-controlled system to autonomously cut pipes of various sizes and lengths. By means of a stepper motor-driven, rapidly spinning blade, the cutting process is accomplished. Additionally, the machine has sensors that measure the hose's length and modify the cutting position as necessary. Premium components and materials are used in the machine's construction; these are chosen for their performance and longevity. The device is able to boost cut precision and raise industry production all around from 100% to 190% efficient system thereby decreasing labor and time needed for hose cutting operations.
Feroz Ali, L.Manikandan, R.Madhankumar, S.Sri Hari, P.Suriya Prakash, T.Vishnu Doss, G.
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, RajeshKumar, AshwiniKumar, Rajender
Wire Electrical Discharge Machining (WEDM) is a widely used manufacturing method that is employed to shape complex geometries in conductive materials such as cupronickel, which is highly regarded for its resistance to corrosion and ability to conduct heat. The aspiration of this investigation is to improve the effectiveness and accuracy of Wire Electrical Discharge Machining (WEDM) for cupronickel material by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) optimization method. The study analyzes the impact of WEDM parameters, specifically pulse-on time, pulse-off time, and discharge current, on important machining outcomes such as surface roughness, material removal rate. Experimental trials are performed to collect data on these parameters and their corresponding machining characteristics. The TOPSIS optimization method is utilized to determine the most favourable parameter settings by evaluating each parameter combination against the ideal and
Pasupuleti, ThejasreeNatarajan, ManikandanKiruthika, JothiC, NavyaSilambarasan, R
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly nature, affordability, and ease of processing. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) for PLA material using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The researchers performed experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including dimensional accuracy, surface finish, and mechanical properties. The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. The TOPSIS approach, a technique for making decisions
Natarajan, ManikandanPasupuleti, ThejasreeKiruthika, JothiKatta, Lakshmi NarasimhamuSilambarasan, R.
This specification establishes process controls for the repeatable implementation of the CSAM process for the manufacturing of metallic and metal-nonmetal blend components.
AMS AM Additive Manufacturing Metals
Additive Manufacturing (AM), specifically Fusion Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of complex structures using a wide range of materials. The objective of this study is to enhance the FDM process for Thermoplastic Polyurethane (TPU) material by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) optimization method. The study examines the influence of FDM parameters, such as layer height, nozzle temperature, and infill density, on important characteristics of the printing process, such as tensile strength, flexibility, and surface finish. The collection of experimental data is achieved by conducting systematic FDM printing trials that cover a variety of parameter combinations. The TOPSIS optimization method is utilized to determine the optimal parameter settings by evaluating each parameter combination against the ideal and anti-ideal solutions. This method determines the optimal parameter
Pasupuleti, ThejasreeNatarajan, ManikandanKiruthika, JothiRamesh Naik, MudeSilambarasan, R
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, ManikandanPasupuleti, ThejasreeKiruthika, JothiKrishnamachary, PCSilambarasan, R
Crawler Dozers play a critical role in global construction, mining and industrial sectors, performing essential tasks like pushing the material, grading, leveling and scraping. In the highly competitive dozer market, meeting the growing demand for increased productivity requires strategies to enhance blade capacity and width. Dozer operations involve pushing the material and dozing, where blade capacity significantly influences performance. Factors such as mold board profile, blade height, and width impact the blade capacity which are crucial for productivity in light weight applications such as snow removal and dirt pushing. Blade width is also pivotal for grading and leveling tasks. Traditional blade designs, like straight or fixed U-type blades, constrain operator flexibility, limiting overall productivity. The integration of hydraulic-operated foldable wings on both sides of the blade offers the adaptability to adjust blade capacity which also helps to reduce material spillage
Sahoo, Jyoti PrakashSarma, Neelam Kumar
Hemming is an incremental joining technique used in the automotive industry, it involves bending the flange of an outer panel over an inner panel to join two sheet metal panels. Different hemming methods are available such as Press die hemming, Table-top hemming and Robot roller hemming. Robot roller hemming is superior to press hemming and tabletop hemming because of its ability to hem complex-shaped parts and is typically used in low-volume automotive production lines. For higher production volumes, such as 120 Jobs per Hour (JPH), press hem or tabletop hem is generally preferred. However, to achieve high-volume production from roller hemming method multi station setup is used. This static multi station setup can be configured into a Turntable setup. This new method eliminates the robot load and unload time at each station in the existing setup, resulting in a 40% increase in hemming robot utilization. Therefore, this process reduces the number of robots and the required floor space
Raju, GokulRoy, AmlanSahu, ShishirPalavelathan, Gowtham RajJagadeesh, NagireddiChava, Seshadri
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 NarayanDolas, AniketMishra, Jagdish
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, ManikandanPasupuleti, ThejasreeKiruthika, JothiD, PalanisamySilambarasan, R
In recent years, engineers at ETH Zurich have developed the technology to produce liquid fuels from sunlight and air. In 2019, they demonstrated the entire thermochemical process chain under real conditions for the first time, in the middle of Zurich, on the roof of ETH Machine Laboratory. These synthetic solar fuels are carbon neutral because they release only as much CO2 during their combustion as was drawn from the air for their production. Two ETH spin-offs, Climeworks and Synhelion, are further developing and commercializing the technologies.
Design and material choices can have a long-term impact on an original equipment manufacturer’s (OEM) production costs and product quality. When an OEM works together with an experienced contract design manufacturer (CDM) from the start of a project, many negative impacts to cost and quality can be avoided.
Robotic automation technology is reshaping food manufacturing, packaging, and handling by driving significant improvements in efficiency, quality, and flexibility. By integrating advanced artificial intelligence, computer vision, and proprietary force-sensing technology, Flexiv has introduced cutting-edge automation to the food processing sector.
When a physician injects a patient with medication from a glass vial, they want to know that the drug inside that vial is sterile and stable. That’s where Genesis Packaging Technologies comes in. Genesis Packaging Technologies, formally a division of the West Company, was founded in 1946. Today, Genesis is a one of the leaders in the science and technology of parenteral vial sealing and residual seal force testing.
Anduril Industries Orange County, CA Contact@anduril.com
There is great recognition regarding the importance of hydrogen as an energy route for the decarbonization of road vehicles. Several countries are making large investments to create products, services, and infrastructures that allow hydrogen to be used as a clean source for propulsion, but there are still many open questions. This complete hydrogen chain involves production, transformation, transport, storage, and use. Although many initiatives are seeking global production, the use of low-carbon hydrogen is not yet economically competitive. Therefore, for this industry to establish itself, and acknowledging the characteristics of each region, there needs to be more intense coordination of efforts between the different industrial and political segments. Low-carbon Hydrogen Use Across Economic Sectors and Global Regions establishes premises for the hydrogen economy and its main environmental aspects. It also includes proposals and scenarios to establish a strategy that relates to
Adas, Camilo Abduch
Related to traditional engineering materials, magnesium alloy-based composites have the potential for automobile applications and exhibit superior specific mechanical behavior. This study aims to synthesize the magnesium alloy (AZ61) composite configured with 0 wt%, 4 wt%, 8 wt%, and 12 wt% of silicon nitride micron particles, developed through a two-step stir-casting process under an argon environment. The synthesized cast AZ61 alloy matrix and its alloy embedded with 4 wt%, 8 wt%, and 12 wt% of Si3N4 are subjected to an abrasive water jet drilling/machining (AJWM) process under varied input sources such as the diameter of the drill (D), transverse speed rate (v), and composition of AZ61 composite sample. Influences of AJWM input sources on metal removal rate (MRR) and surface roughness (Ra) are calculated for identifying the optimum input source factors to attain the best output responses like maximum MRR and minimum Ra via analysis of variant (ANOVA) Taguchi route with L16 design
Venkatesh, R.
Additive Manufacturing (AM) techniques, particularly Fusion Deposition Modeling (FDM), have received considerable interest due to their capacity to create complex structures using a diverse array of materials. The objective of this study is to improve the process control and efficiency of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material by creating a predictive model using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The study investigates the impact of FDM process parameters, including layer height, nozzle temperature, and printing speed, on key printing attributes such as tensile strength, flexibility, and surface quality. Several experimental trials are performed to gather data on these parameters and their corresponding printing attributes. The ANFIS predictive model is built using the collected dataset to forecast printing characteristics by analyzing input process parameters. The ANFIS model utilizes the learning capabilities of neural networks
Pasupuleti, ThejasreeNatarajan, ManikandanD, PalanisamyA, GnanarathinamUmapathi, DKiruthika, Jothi
The EN24 and EN42 materials were machined by the electric discharge machine (EDM). The study aimed to optimize the input variables for the multiple outputs, such as metal removal rate (MRR), tool wear rate (TWR), and surface roughness. The machining of the metal is essential to analyze the surface quality and the production rate. The MRR is a prediction of the production rate and surface roughness resembling the quality of the surface. The input variables were current (A), pulse on time (ton), and pulse duty factor (T). The three levels of current were 3A, 6A, and 9A. The ton time was selected as 30 μs, 50 μs, and 70 μs. The pulse duty factors were selected as 4, 5, and 6. The Taguchi optimization techniques are used to optimize process parameters. The L9 orthogonal array was selected for the process. ANOVA analysis was employed to check the rank of the input parameters relative to the output. The maximum MRR were at 9A, 70 μs, and 4 duty factor for the EN24. The best MRR were at 9A
Sahu, Kapil DevSingh, RajnishChauhan, Akhilesh Kumar
Accurately predicting system output performance is essential for manufacturing system design. However, traditional approaches that rely solely on the reliability of individual workstations may lead to inaccuracies, especially for a serial production line that includes several workstations with low reliability. This study investigates how prediction inaccuracies arise from intricate interactions among workstations, as revealed through discrete event simulation (DES). To resolve this issue, a novel methodology is proposed, leveraging DES and dual regression analyses to develop an adjustment factor. This paper details the application of this methodology across a range of reliability levels (85–99%) and workstation counts (5–10), conducting sensitivity analyses and validating the results. This approach offers a practical tool for improving the efficiency and precision of a system output prediction in design contexts. Additionally, the paper discusses the methodology’s limitations and
Tang, Herman
The impact of the upcoming U.S. federal election, global trade turmoil, a mediocre U.S. economy and the slumping ICE-to-EV (internal combustion engine to electric vehicle) transition must be considered. In my last column, we explored the growing use of scenarios to provide guardrails for future strategy. Suppliers can no longer rely upon a single forecast to drive future planning. The main culprits clouding the planning environment are program delays, rescopes and EV strategy shifts accompanied by the extension of ICE/hybrid models. The trajectory of EV launches and new offerings is decidedly ahead of the skis of consumer acceptance. This supply-and-demand mismatch is an ongoing challenge. It is important to understand the severity of program changes amid this slowing EV growth environment.
Contrary to what you may have heard, Americans are buying more EVs than ever. But they tend to like 'em big. After production delays due to software development issues - a problem that continues to plague automakers from Volkswagen to General Motors - Volvo's EX90 will look to lure families who live for three-row luxury SUVs. Based on a recent media drive in Newport Beach, California, Volvo may still have some work to do. The twin-motor EX90 did impress us with its 510 hp (380 kW), confident handling, leading-edge safety and sparkling high-resolution displays. But a software glitch dinged our test car when a section of its 14.5-inch (37 cm) center screen blanked out. Other journalists reported issues with a phone-based digital key that briefly left one driver stranded when it wouldn't connect with the Volvo. This is another reason I never rely on an automaker's digital key and always ask for a hard backup.
Ulrich, Lawrence
Items per page:
1 – 50 of 7981