Browsing by Author "Herbert, M.A."

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A comparative study of tensile properties of eutectic Al-Si / ZrO2 composites fabricated by spray forming and stir casting methods
(Taylor and Francis Ltd., 2022) Goudar, D.M.; Patil, I.S.; Magalad, V.T.; Rao, S.S.; Herbert, M.A.
The study aims to investigate the microstructural and mechanical properties of Al-12.5%Si matrix composites reinforced with ZrO2 were fabricated by spray forming method and stir casting (SC) technique by varying reinforcement of 2%, 6% and 10 wt.% ZrO2 powder (size 25 ?m).The spray-formed (SD) composites were subjected to hot (400°C) isostatic pressing to reduce the porosity. The microstructure of spray-formed and SC composites were examined using optical and SEM/ EDS. The microstructure of the spray-formed composites showed uniform distribution of fine Si, eutectic phase and ZrO2 particles in the equiaxed Al-matrix. In contrast, SC composites consist of a coarse Si, needle like eutectic phase and clustering of reinforcement particles at grain junctions as a continuous network along the grain boundaries. The hardness, ultimate tensile strength of both spray-formed and SC composites improved as the ZrO2 content increased, while yield strength decreased. Spray-formed composites showed better mechanical properties. This was attributed to uniform distribution fine of Si particles, reinforced particles, equiaxed matrix induced during spray deposition process. Tensile fracture surface of spray-formed composites possess ductile and cleavage fractures. SC composites showed intragranular cracks in coarse Si particles and increase in micro-cracks with increasing reinforcement. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
A comprehensive review of friction stir techniques in structural materials and alloys: challenges and trends
(Elsevier Editora Ltda, 2022) Prabhakar, D.A.P.; Shettigar, A.; Herbert, M.A.; Gowdru Chandrashekarappa, M.; Pimenov, D.Y.; Giasin, K.; Prakash, C.
Friction-stir techniques are the potential alternative to fusion-based systems for processing and welding metallic alloys and other materials. This review explores the advantages, applications, limitations, and future directions of seven friction-based techniques namely, Additive Friction Stir Deposition (AFSD), Friction Stir Additive Manufacturing (FSAM), Friction Stir Welding (FSW), Friction Stir Processing (FSP), Friction Surfacing (FS), Friction Stir Spot Welding (FSSW), and Friction Stir Lap Welding (FSLW). The basic underlying principle of these processes uses friction as a thermal energy source to weld/process/deposit materials. The common control parameters of all friction stir processing techniques are axial force, rotational speed, and weld or traverse speed. In addition, tool profiles and tool dimensions are known to influence the weld quality. The tool's rotational speed and axial force generate friction between the workpiece and tool material interface, which could plasticize the material. The additive powder bed friction stir process (APBFSP) is another new solid-state manufacturing technique that focus on fabricating the polymer matrix nanocomposites (PNC). In this, a hollow tool like AFSD and the fundamental principle of FSP are combined. The said parameters affect the quantity of material getting deposited/welded. However, weld speed/traverse speed alters the weld quality, and higher traverse speed results in porosity and voids in the welded/deposited/processed region. The only difference between AFSD and other friction stir techniques (FSTs) is that in the AFSD technique, the hollow rotating tool comprises two protrusions with different tool profiles (cylindrical, threaded cylindrical, and tapered cylindrical, square) used. Threaded cylindrical profile and tool steel as the tool material is the most commonly employed in FSTs. Apart from that, tungsten carbide is preferred for hard materials. The working principles and process parameters of FSTs that affect the part quality are discussed in detail. The above review gives the reader an understanding of the domain of FSTs that can be researched further. A summary of some of the potential research works with objectives, process parameters, and outcomes is highlighted. This will provide the readers with an overview of the work carried out by researchers across the globe. Finally, the potential research gaps for future directions to be explored soon across the globe are outlined. © 2022 The Author(s).
A Review of Optimization and Measurement Techniques of the Friction Stir Welding (FSW) Process
(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Prabhakar, D.A.P.; Korgal, A.; Shettigar, A.K.; Herbert, M.A.; Gowdru Chandrashekarappa, M.P.G.; Pimenov, D.Y.; Giasin, K.
This review reports on the influencing parameters on the joining parts quality of tools and techniques applied for conducting process analysis and optimizing the friction stir welding process (FSW). The important FSW parameters affecting the joint quality are the rotational speed, tilt angle, traverse speed, axial force, and tool profile geometry. Data were collected corresponding to different processing materials and their process outcomes were analyzed using different experimental techniques. The optimization techniques were analyzed, highlighting their potential advantages and limitations. Process measurement techniques enable feedback collection during the process using sensors (force, torque, power, and temperature data) integrated with FSW machines. The use of signal processing coupled with artificial intelligence and machine learning algorithms produced better weld quality was discussed. © 2023 by the authors.
A study of microstructure and mechanical properties of friction stir welded joint of Al-Ce-Si-Mg aluminium alloy plates and optimization cum prediction techniques using Taguchi and ANN
(Elsevier Ltd, 2023) Dâ€™Souza, A.D.; Rao, S.S.; Herbert, M.A.
In the current research work, the effect of friction stir welding (FSW) on joint strength and evolution of microstructure at the weld zone of the friction stir welded of Al-Ce-Si-Mg aluminium alloy (Al10Mg8Ce3.5Si and Al5Mg8Ce3.5Si) is studied. The experimentations demonstrated that the speed of tool revolution, contour of tool pin and tool movement rate have influence on the quality of the FSW joint of the alloy. It was noticed that the size of grains at nugget zone (NZ) depends upon the speed of tool spin, speed, of tool feed, tool pin contour and composition of the aluminium alloy. The grain size at the bottom of the NZ was discovered to be reducing when compared to that at the top of the NZ. It was also noted that highest hardness was reached at NZ. Lowest hardness was found at heat affected zone (HAZ) and most of the tensile specimens fractured at HAZ. The Taguchi orthogonal array-based design has demonstrated that the tool pin contour had the greatest influence in enhancing the joint strength, followed by speed of tool feed, material composition and speed of tool spin. A speed of revolution of tool of 1000 rpm, tool movement rate of 20 mm/min, triangular contour pin (TCP) tool and Al10Mg8Ce3.5Si aluminium alloy were concluded as the optimum variables of the process. The percentage contribution of each one of these input process parameters on optimum output quality characteristics was also found out and noticed to be lying well within the confidence interval of 95% suggested by the Taguchi design. The current study has shown that the prediction results with artificial neural network (ANN) are better compared to those predicted using statistical methods like Taguchi Techniques. Â© Â© 2023 Elsevier Ltd. All rights reserved.
Active Upper Arm Exoskeleton - Design and Kinematic Analysis
(2019) Santra, P.; Mukhopadhyay, A.; Debnath, B.; Herbert, M.A.; Bhaumik, S.
The authors present a design of an exoskeleton with 6 active degrees of freedom (DOF) and 5 passive DOFs for rehabilitation of stroke survivors. Emphasis has been laid on making the model light weight and more ergonomic. Thus, concentration is mainly on 3D modeling of that device so that the mechatronic approach is compatible with human hand. The main choice of material for fabrication has been Nylon 6/10, owing to its lightweight and durable properties. The model was developed completely by the use of Computer Aided Design (CAD) and Computer Aided Engineering (CAE). Our model focuses on proposing a new actuation principle for better development of ergonomic shoulder design by incorporation of compliant passive springs and one passive revolute joint. Joints of the exoskeleton have been taken as simple revolute, possessing desired motion limits. Also forward kinematics has been established and the general workspace of the model has been developed. � 2019 IEEE.
Active Upper Arm Exoskeleton - Design and Kinematic Analysis
(Institute of Electrical and Electronics Engineers Inc., 2019) Santra, P.; Mukhopadhyay, A.; Debnath, B.; Herbert, M.A.; Bhaumik, S.
The authors present a design of an exoskeleton with 6 active degrees of freedom (DOF) and 5 passive DOFs for rehabilitation of stroke survivors. Emphasis has been laid on making the model light weight and more ergonomic. Thus, concentration is mainly on 3D modeling of that device so that the mechatronic approach is compatible with human hand. The main choice of material for fabrication has been Nylon 6/10, owing to its lightweight and durable properties. The model was developed completely by the use of Computer Aided Design (CAD) and Computer Aided Engineering (CAE). Our model focuses on proposing a new actuation principle for better development of ergonomic shoulder design by incorporation of compliant passive springs and one passive revolute joint. Joints of the exoskeleton have been taken as simple revolute, possessing desired motion limits. Also forward kinematics has been established and the general workspace of the model has been developed. Â© 2019 IEEE.
Advantages of cryogenic machining technique over without-coolant and with-coolant machining on SS316
(IOP Publishing Ltd, 2021) Karthik, M.; Malghan, R.L.; Shettigar, A.K.; Herbert, M.A.; Rao, S.S.
The analysis concentrated towards the influence of speed of the spindle along with a cryogenic (LN2) cooling technique in treating SS316 usingCNC(Computerized numerical control) milling machine. An comparative study path was set and anlyised among three states i.e. Dry (Without coolant), wet (With coolant) and cryogenic (With liquid LN2) machining using coated carbide inserts. The coolant used in case of wet machining was water-soluble, referred to as cutting fluid. The experimental range falls in 3 different levels of spindle speed (SS), such as low level (1000 rpm), medium level (2000 rpm), and high level (3000 rpm), respectively. Meanwhile, feed rate (FR) and depth of cut (DOC) were reserved steadily with 450 mm min-1, 1 mm separately. This vital focus is towards cryogenic (LN2) machining effects and its perception of machinability on SS316, such as tool wear -TW(?m), cutting force-CF (N), cutting temperature-CT (oC) and surface roughness-Ra (?m). The experiments were conducted and documented with cryogenic (LN2) techniques to establish the fairness and practicability of the method to compare with without-coolant (dry) and with-coolant (wet) machining. The attained statistical results in comparison of LN2 method over without-coolant and with-coolant machining concerned to test cases for CF- Fx (N), CT(oC), Ra (?m) andFW(?m) are 53.21%-34.20%, 65.88%-44.51%, 75.43%-44.27%,&59.76%-23.10%, respectively. © 2021 IOP Publishing Ltd.
An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques
(Springer, 2019) Karthik, M.C.; Malghan, R.L.; Shettigar, S.; Rao, S.S.; Herbert, M.A.
The present work is an endeavor to carry out a machining using LN2 in face milling operations and to produce the milling samples with excellent wear resistance property. The output response (wear rate) depends on appropriate choice of speed, feed, and depth of cut. The experimental data are conducted (collected) for SS316 as per central composite design. The present work exemplifies an employment of conventional and nonconventional strategies for optimizing the milling factors of cryogenically treated samples in face milling to achieve the desired wear (response). The results of nonlinear regression (desirability strategy) and nonconventional [particle swarm optimization, (PSO)] optimization techniques are compared, and PSO is found to outperform the desirability function approach. The present work even highlights the effect and results of LN2 on wear in contrast to wet condition. © 2018, The Indian Institute of Metals - IIM.
An Experimental and Numerical Approach to Study the Performance of Modified Perforated Cutting Tools on Machining of Ti–6Al–4V Alloy
(Springer, 2020) Rao, C.M.; Rao, S.S.; Herbert, M.A.
In this research, the main aim is to reduce the unfavorable effects that occurred during machining of the Ti–6Al–4V alloy by perforating the rake face and the flank face of the cutting insert. The main novelty in this research is that machining of Ti–6Al–4V alloy with the micro-hole textured insert helps in the improvement of tribological properties and also reduces cutting temperature at chip–tool interface with proper lubricating effect. To validate the micro-hole textured tools, it is compared with conventionally available insert. The deformation of Ti–6Al–4V alloy with modified cutting inserts was simulated, considering tool as rigid body and workpiece as elasto-plastic material. DEFORM 3D software was used for the simulation of the machining process with the updated Lagrangian formulation. To predict the cutting temperature and chip morphology, the thermo-mechanical analysis was applied using Johnson–Cook material model for the machining process. The turning of the Ti–6Al–4V alloy was carried out with the modified polycrystalline diamond (PCD) cutting inserts (Design 1 and Design 2) and commercially available PCD insert (normal insert). Coconut oil was used as a micro-pool lubricant during the machining process under minimum quantity lubrication environment. In the present work, the turning performance characteristics such as cutting temperature, cutting vibration, tool wear, chip morphology and surface integrity were measured during machining of the Ti–6Al–4V alloy. The experimental results of cutting temperature and chip morphology were validated with the simulation results with better accuracy. The machining results of Design 2 cutting insert showed maximum reduction of 30%, 38%, 45% and 35% in cutting temperature, cutting vibration, tool wear and surface roughness, respectively, when compared with machining under normal insert and Design 1 cutting insert. It is also evident from the results that machining with Design 2 cutting insert significantly improved the process performance of the product quality at higher feed rates. © 2019, King Fahd University of Petroleum & Minerals.
An Industry 4.0 Approach: Data Acquisition and Machine Monitoring for Welding Machines
(Springer Nature, 2024) Narendra Reddy, T.N.; Ponnappa, N.P.; Prasad, P.; Vinod, P.; Herbert, M.A.; Rao, S.S.
The research introduces an innovative application of Industry 4.0 principles in welding by employing IIoTbased performance monitoring equipment. One the important aspect of Industry 4.0 adaption is understanding the requirement from the customer and develop/ provide the acceptable solution to them is crucial. An attempt has been made to develop a solution which can be used for any kind of welding machines including legacy welding machines. The developed solution delivers real-time updates on shop floor welding processes with the help of Operational Technology (OT) and Information technology (IT) with the help of hall effect sensors and voltage transducers by connecting them to the Programmable logic controller (PLC). Additionally, it facilitates real-time feedback, alerts, and report generation. The study comprehensively assesses the effectiveness and production capacity of an industrial welding system, presenting a detailed design overview and practical demonstration. Potential enhancements, such as integrating machine learning, emphasizing remote monitoring, evaluating energy efficiency, addressing cybersecurity, and assessing scalability, are explored. The research includes a cost–benefit analysis for the shopfloor and provides insights into the real-world effectiveness of IIoT-based welding performance monitoring in industrial contexts. The developed solution has been tested, validated, and deployed in one of the welding industries, and it has helped in real-time monitoring, scheduling the work and data analytics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Application of back propagation algorithms in neural network based identification responses of AISI 316 face milling cryogenic machining technique
(Taylor and Francis Ltd., 2022) Karthik, K.R.; Malghan, R.L.; Shettigar, A.; Rao, S.S.; Herbert, M.A.
The paper explores the potential study of artificial neural network (ANN) for prediction of response surface roughness (Ra) in face milling operation with respect to cryogenic approach. The model of Ra was expressed as the main factor in face milling of spindle speed, feed rate, depth of cut and coolant type. The ANN is trained using four various back propagation algorithms (BPA). The emphasis of the paper is to investigate the performance and the accuracy of the attained results depicts the effectiveness of the trained ANN in identifying the predicted Ra. The incorporated various BPA in predicting the Ra. The performance comparative study is made among statistical (Response Surface Methodology (RSM)) and ANN (BPA–training algorithm) methods. The various incorporated BPA algorithms are Gradient Descent (GD), Scaled Conjugate Gradient Descent (SCGD), Levenberg Marquardt (LM) and Bayesian Neural Network (BNN). Afterwards the best suitable BPA is identified in predicting Ra for AISI 316 in face milling operation using liquid nitrogen (LN2) as cutting fluid. The outperformed BPA is identified based on the attained deviation percentage and time required for the training the network. © 2020 Engineers Australia.
Applications of reinforcement particles in the fabrication of Aluminium Metal Matrix Composites by Friction Stir Processing - A Review
(EDP Sciences, 2022) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.
Composite materials possess advantages like high strength and stiffness with low density and prove their essentiality in the aviation sector. Aluminium metal matrix composites (AMMC) find applications in automotive, aircraft, and marine industries due to their high specific strength, superior wear resistance, and lower thermal expansion. The fabrication of composites using the liquid phase at high temperature leads to the formation of intermetallics and unwanted phases. Friction Stir Processing (FSP) is a novel technique of composite fabrication, with temperature below the melting point of the matrix, achieving good grain refinement. Many researchers reported enhancement of mechanical, microstructure, and tribological properties of AMMC produced by the FSP route. The FSP parameters such as tool rotational speed, tool traverse speeds are found to be having greater impact on uniform dispersion of particles. It is observed that the properties such as tensile strength, hardness, wear and corrosion resistance, are altered by the FSP processes, and the scale of the alterations is influenced significantly by the processing and tool parameters. The strengthening mechanisms responsible for such alterations are discussed in this paper. Advanced engineering materials like shape memory alloys, high entropy alloys, MAX phase materials and intermetallics as reinforcement material are also discussed. Challenges and opportunities in FSP to manufacture AMMC are summarized, providing great benefit to researchers working on FSP technique. ©
Assessment of influence of process parameters on properties of friction stir welded Al-Ce-Si-Mg aluminium alloy
(Institute of Physics Publishing helen.craven@iop.org, 2019) D’Souza, A.D.; Rao, S.S.; Herbert, M.A.
The research on friction stir welding is mainly focused on welding of aluminium alloys. The material of interest in this research is an aluminium alloy known as Al-Ce-Si-Mg aluminium alloy. The FSW of this alloy finds applications in aerospace industry like joining of aircraft structure parts such as fuselage, cladding and engine components and in automotive industry for welding of parts of body structure and engine. The quality of the weld produced by FSW such as macrostructure defects, average grain size, ultimate tensile stress and weld zone hardness etc are dependent on input parameters like tool revolution, tool feed rate and tool pin profile. The weld defects like tunnel hole, worm hole and pin holes were not predominant in the tool revolution range of 800 to 1200 rpm and tool feed rate range of 10 to 20 mm min-1. The maximum ultimate stress was found to be lesser in the low and high tool revolution and tool feed rates compared to the medium speeds. The maximum value of UTS noted was 102.55 MPa for the weld at a tool revolution of 800 rpm and tool feed rate of 20 mm min-1 with a triangular pin profile tool, giving a joint efficiency of 67%. The Vickers hardness values were less at lower and higher speed ranges of tool revolution and tool feed rates for all the tool pin profiles used. The maximum value of Vickers hardness was noted for a tool revolution of 1000 rpm and tool feed rate of 20 mm min-1 with a triangular pin profile tool. The lowest grain size was observed for the tool revolution of 1000 rpm and tool feed rate of 20 mm min-1 with a triangular pin profile tool, indicating the inverse relation between hardness and grain size. In all the experiments it was observed that the triangular pin profile tool gives the best results at medium tool revolution and tool feed rate ranges. © 2019 IOP Publishing Ltd.
Comparison of Response Surface Methodology (RSM) and Machine Learning Algorithms in Predicting Tensile Strength and Surface Roughness of AA8090/B4C Surface Composites Fabricated by Friction Stir Processing
(Springer Science and Business Media Deutschland GmbH, 2024) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.K.; Shrivathsa, T.V.; Tapariya, R.
Friction stir processing is an innovative solid-state process, widely utilized for surface composite fabrication, material property enhancement, and microstructural modification. Rotational speed, traverse speed, groove width, and axial force are key FSP parameters that improve the characteristics of surface composites (SCs). This work makes use of FSP to fabricate AA8090/B4C SCs by altering parameters within ranges. Response variables include ultimate tensile strength (UTS) and surface roughness (SR). Central composite design (CCD) of response surface methodology (RSM) leads trials, establishing a mathematical relationship between input parameters and UTS/SR. The modelsâ€™ adequacy is validated using ANOVA, which investigates the impact of input parameters on UTS and SR. This study also looks into machine learning regression methodologies for UTS and SR forecasting in AA8090/B4C SCs. The ML algorithms are evaluated by utilizing performance metrics like coefficient of determination (R2) and root mean squared error (RMSE). Predicted UTS and SR values from RSM are compared with machine learning outcomes. Â© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Comparison of Wear Behaviour of Alâ€“12.5Si Alloy Reinforced with ZrO2 Using Spray Deposition and Stir Casting Technique
(Springer Science and Business Media Deutschland GmbH, 2023) Patil, I.S.; Rao, S.S.; Herbert, M.A.
Aluminium silicon alloy materials are commonly used in aerospace and automotive engineering applications due to their enhanced stiffness, excellent wear resistance and lightweight. The measurement of wear properties for these combinations is very tangled. This can differ under different operating conditions. Dry sliding wear properties of Alâ€“12.5Si with reinforced zirconium oxide matrix composite have been investigated using stir casting and spray deposition methods. The weight fraction of ZrO2 is 15%. The influence of applied nominal load (10 to 60 N) was investigated using the design of experiments. Wear properties of the hybrid composites were studied using pin-on-disc machine. The study found that the wear behaviour was improved by increasing the composition the zirconium oxide in alloy silicon matrix in both stir casting and spray forming techniques. The spray forming method showed lesser wear rate compared with stir casting method. Microstructure of the developed hybrid composites was analysed using scanning electron microscope (SEM). The developed hybrid composite samples have twice the improvement in wear resistance using spray deposition. The influence of reinforced zirconium oxide in aluminium silicon metal matrix on the wear properties using spray forming method is highlighted. This study shows that the wear resistance of the metal matrix composites can be improved by increasing the ZrO2 composition in aluminium silicon matrix. Â© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Control factor optimization for friction stir processing of AA8090/SiC surface composites
(Elsevier B.V., 2024) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.K.
Friction Stir Processing is a state-of-the-art technology for microstructure refinement, material property enhancement, and surface composites fabrication. This investigation concentrates on AA8090/SiC surface composites produced via friction stir processing. Experiments were conducted by varying the following friction stir processing parameters: Tool rotational speed (800–1400 rpm), Tool traverse speed (25–75 mm/min), and Groove width (1.0–1.8 mm). Response measures encompassed Ultimate Tensile Strength and surface roughness. Central Composite Design of Response Surface Methodology designed the experiments and mathematical relationships established between input parameters and ultimate tensile strength and surface roughness. Analysis of variance was used to test the model's adequacy. The models examined individual and interaction effects of input factors on ultimate tensile strength and surface roughness of surface composites. A combinations of input parameters was identified that yields the maximum ultimate tensile strength and minimum surface roughness. The current work employs the friction stir processing approach to synthesis near-net-shaped surface composites without additional machining by systematically optimizing process parameters. Results indicate that increasing tool rotational speed produces well-finished AA8090/SiC surface composites with decreased strength. In contrast, increased tool traverse speed and groove width generate surface composites with rougher surfaces and higher strength. Surface and contour plots further explored the influence of parameter interactions on responses. © 2024 The Authors
Correlation of Tribological Properties with Microstructure and Mechanical Properties of Graphite Cast Irons Centrifugally Cast for Engine Liner
(Springer India sanjiv.goswami@springer.co.in, 2014) Desai Gowda, H.S.; Mukunda, P.G.; Herbert, M.A.
This is a study of the influence of centrifugal process on the graphite morphology, mechanical and wear properties on flake graphite iron (FGI), spheroidal graphite iron (SGI) and compacted graphite iron (CGI). Melts of hypereutectic and almost of identical composition with or without melt treatment were centrifugally cast. The microstructure, mechanical and wear properties of these specimens were studied. In the microstructure for FG iron it has been observed that the centrifugal process produces flake size range class 2–3 (range 160–320 ?m) and graphite of flake type A by about 67.9 % (field %) and combined flakes of type B, C, D and E will be of 32.1 % (field %). While SGI has been observed to have 96.1 % nodules and 330.0 nodules per square millimeter. Similarly CGI has been seen to produce 52.0 % nodules and 113 nodules per square millimeter. SGI possess the highest tensile strength, rupture strain and hardness of 604 N/mm2, 6.1 %, 233 BHN respectively. Whereas FGI possess the least tensile strength, rupture strain and hardness of 303 N/mm2, 0.65 %, 185 BHN respectively among the irons. CGI has a tensile strength, rupture strain and hardness of 369 N/mm2, 1.2 % and 200 BHN respectively which lies in between those of FGI and SGI. During the wear test similar materials for both disk and pin combination show higher co-efficient of friction and wear rate than those for dissimilar material combinations. SGI disk and FGI pin combination show least wear. This combination would be ideally suited for engine liner and piston rings. © 2014, Indian Institute of Metals.
Correlational Study of Ultimate Tensile Stress and Hardness of Friction Stir-Welded Al–Ce–Si–Mg Aluminum Alloys
(Springer Nature, 2024) D’Souza, A.D.; Herbert, M.A.; Rao, S.S.
In this research article, an analysis of correlation between mechanical properties of aluminum alloy such as ultimate tensile stress and Vickers hardness is carried out. Research analysis shows that hardness and UTS have a direct relationship. Tool rotation speed also directly impacts hardness and UTS values by controlling the amount of heat generated and hence extent of plasticization and grain refinement in the region of the weld. According to the research results, the plane surfaces of the square profiled pin of the tool aid in introducing a pulsing effect, which contributes to improved strength of weld connection. When compared to other tool profiles, a higher dynamic-to-static ratio attained with the triangular profiled pin tool results in greater material sweeping. As a result, the highest UTS and hardness values were obtained for welding connections created with the triangular profile pin tool. The study shows that the various input process parameters pertaining to tool revolving velocity, welding velocity, and tool-pin profile have a similar relationship on both hardness and ultimate tensile strength of weldment connection obtained with friction stir weld process. Hence, a similar trend or correlation has been observed in the variation of hardness and UTS. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Development of Low-Cost IIoT Solution for Smart Factories in MSME Industries: Utilizing Current Measurements for Machine and Factory Monitoring
(Springer Science and Business Media Deutschland GmbH, 2025) Narendra Reddy, T.N.; Vinod, S.P.; Nachappa, P.P.; Herbert, M.A.; Rao, S.S.
In response to an evolving industrial landscape, monitoring industrial assets and systems involves aggregating data from diverse sources within a production system to assess the performance of machinery, and associated processes. This paper is dedicated to the development of an affordable IIoT solution for productivity monitoring in MSME industries and also being implemented in the development cell for manufacturing setup. The devised solution leverages cost-effective hardware for sensing, a controller for data acquisition and analysis, and an edge gateway for cloud storage. The collected data are processed and analyzed through web-based front-end and back-end software technologies designed for machine and factory monitoring. The solution offers insights into factory and machine statuses, facilitates productivity tracking, and enables part count measurements. Furthermore, the software also provides users with automated reporting through Email and SMS, allowing for the creation of customized reports on a daily and monthly basis. Subsequently, the resulting experimental setup was successfully introduced as a low-cost solution to an industry, further validating its practicality and relevance in real-world settings. Â© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Development of machine learning regression models for the prediction of tensile strength of friction stir processed AA8090/SiC surface composites
(Institute of Physics, 2024) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.K.; Vasudeva, T.V.
Friction Stir Processing is a state-of-the-art technology for microstructure refinement, material property enhancement, and fabrication of surface composites. Machine learning approaches have garnered significant interest as prospective models for modeling various production systems. The present work aims to develop four machine learning models, namely linear regression, support vector regression, artificial neural network and extreme gradient boosting to predict the influence of FSP parameters such as tool rotational speed, tool traverse speed and groove width on ultimate tensile strength of friction stir processed AA8090/SiC surface composites. These models were developed through Python programming and the original dataset was divided into 80% for the training phase and 20% for the testing phase. The performance of the models was evaluated by root mean squared error, mean absolute error and R2. Based on the results and graphical visualization, it was observed that the XGBoost model outperformed other models with high accuracy in predicting UTS of AA8090/SiC surface composites. © 2024 The Author(s). Published by IOP Publishing Ltd.