Department of Production Engineering

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A REVIEW OF FRICTION WELDING RESEARCH ADDRESSING THE INFLUENCE, DEVELOPMENT, SIMILAR & DISSIMILAR WELDING
(Galati University Press, 2023-12-28) Murugan, S. Senthil.; Sathiya, P
This review paper discusses the recent research work carried out in the frictional joining of dissimilar and similar alloys through the friction welding (FW) process with various parameters and modifications. It includes further the latest developments and advances in the research on FW and the influences of FW’s process parameters on the quality of joints and their properties. The specimens’ faying surfaces can also influence the joint properties as the surface modifications stimulate or change the metal joints’ bonding according to the welding parameters selected during FW. Though the rise of friction pressure (FP) during FW improves the strength of the joints, the improper selection of parameters leads to metal damage. It feels better if the axial shortening is less than 30 mm for FW of soft metals. The axial shortening values are less than 25 mm for the hemispherical bowl-type faying surfaces under 18 bar FP and it is noted that the bevel-type tapered faying surfaces increase the shortening. FW provided very narrow weld interfaces with around 5-10 µm width. With a low FP, it was possible to obtain a maximum of 100 % efficiency by modifying their faying surfaces. The small-diameter soft material needs less FP and friction time. The microstructure modification is possible and the weld joint is shown as U and V shapes for the bowl and tapered faying surfaces. It further increases the contact area and thus increases strength.
Acoustic emission based deep learning technique to predict adhesive bond strength of laser processed CFRP composites
(Belgrade University, 2020-06-24) Sathiyamurthy, Ramkumar; Duraiselvam, Muthukannan; Sevvel, P
The high degree of inhomogeneity in material and intricacies created by machining of carbon fiber reinforced plastic (CFRP) composites hinder the accurate prediction of residual strength of the adhesive bond joint using analytical models. Recently, artificial intelligence techniques are effectively utilized as an alternative method for predicting the results of complex phenomena. In this paper, attempts were made to predict the bond strength of laser surface treated and adhesively bonded CFRP composite specimens using the artificial neural network (ANN) from the acoustic emission (AE) parameter recorded during the shear test. Twelve adhesively bonded specimens whose surfaces were pre-processed with 3W Nd:YAG laser at different processing parameters. ANN was trained using segregated AE data according to the failure mechanism and the percentage of failure load (5 to 100%). Predicted values were compared with experimental values and the results were analysed for the suitability of ANN with AE in the application. © Faculty of Mechanical Engineering, Belgrade.
An energy-efficient FPGA accelerator for transformer inference using layer-wise precision optimization
(Elsevier B.V., 2026-09-06) Eiswar S, Darun; N, Pugalbharani; Bharatula, Sitadevi; Reddy, B. Naresh Kumar.
Abstract FPGA transformer accelerators routinely fix their multiply-accumulate (MAC) accumulators at 32 bits, echoing a theoretical 25–27-bit worst case for INT8 BERT-base matrix multiplication that has never been checked against actual per-layer behavior. We provide a transformer-specific layer-level study, profiling 215 linear layers across BERT-base, TinyBERT-4L, DistilBERT-base, ALBERT-base-v2, and ELECTRA-small-discriminator over WikiText-2 samples via PyTorch forward-hook INT8 simulation that tracks the true partial-sum accumulation trajectory (not only the final dot-product value) with a 2-bit margin. Across these 215 profiled layers, the maximum observed accumulator requirement is 20 bits under the specified profiling conditions, and 500 SST-2 samples show zero prediction changes, with δ=2 bits the best-performing margin among those tested. Synthesized on the Zynq™ UltraScale+™ MPSoC ZCU104, a 16-bit MAC cuts flip-flops 39% and LUTs 17% versus a 32-bit baseline while exceeding 400 MHz; a per-layer-instance resource lower bound for a 73-layer BERT-base array projects 34.5% fewer flip-flops and 15.4% fewer LUTs.
An experimental study of thermal fatigue on ASTM A 213 grade T-23 steel tube
(Hindawi Limited, 2009-08-31) Jinu, G.R.; Sathiya, P; Ravichandran, G; Rathinam, A
Super heater tubes are subjected to alternate heating and cooling in power plants causes crack and eventually fail. This phenomenon is termed as thermal fatigue. In this paper, a laboratory simulation for reproducing thermal fatigue phenomenon is developed to determine the number of cycles of failure occurs in super heater tubes. Thermal fatigue tests are conducted in Non-Destructive Tested T23 base and SMAW welded tubes separately. The tubes are subjected to thermal cycles from 800∘C (accelerated temperature) to room temperature (28∘C). In this work 800∘C is selected in order to achieve the crack much earlier. The selected temperature is just below the Ac1 temperature. The tubes are subjected to heat by Oxy-acetylene flame and subsequently quenched with water. The tests are carried out until open cracks are identified. Surface cracks are identified in the base and weld tubes after 120 and 80 cycles respectively. The tubes are then sectioned and subjected to optical microscopy. The causes of failures are thoroughly investigated using Scanning Electron Microscope (SEM). This study reveals that localised heating and cooling causes thermal fatigue which initiates cracks in the tubes.
Artificial neural network modeling studies to predict the friction welding process parameters of Incoloy 800H joints
(Elsevier B.V., 2015-02-26) Anand, K; Barik, Birendra Kumar; Tamilmannan, K; Sathiya, P
The present study focuses on friction welding process parameter optimization using a hybrid technique of ANN and different optimization algorithms. This optimization techniques are not only for the effective process modelling, but also to illustrate the correlation between the input and output responses of the friction welding of Incoloy 800H. In addition the focus is also to obtain optimal strength and hardness of joints with minimum burn off length. ANN based approaches could model this welding process of INCOLOY 800H in both forward and reverse directions efficiently, which are required for the automation of the same. Five different training algorithms were used to train ANN for both forward and reverse mapping and ANN tuned force approach was used for optimization. The paper makes a robust comparison of the performances of the five algorithms employing standard statistical indices. The results showed that GANN with 4-9-3 for forward and 4-7-3 for reverse mapping arrangement could outperform the other four approaches in most of the cases but not in all. Experiments on tensile strength (TS), microhardness (H) and burn off length (BOL) of the joints were performed with optimised parameter. It is concluded that this ANN model with genetic algorithm may provide good ability to predict the friction welding process parameters to weld Incoloy 800H. © 2015 Karabuk University
Characterization of chemical treated and untreated natural fibers from Pennisetum orientale grass- A potential reinforcement for lightweight polymeric applications
(KeAi Publishing Communications Ltd., 2020-07-15) Vijay, R; Vinod, A; Lenin ,Singaravelu. D.; Sanjay, M.R; Siengchin, Suchart
The current work deals with the study extraction and characterization of fibers from Pennisetum orientale grass. The fibers were extracted, treated chemically with hydrochloric acid and sodium hydroxide (alkali) solutions. The chemically modified and unmodified fibers were analyzed for its thermal, chemical, crystalline, physical, morphological and tensile characteristics. The test results showed that chemical treatment using alkali helped to increase the cellulose content by 65.1% with a reduction in amorphous contents and moisture. But the hydrochloric acid treatment reduced the cellulose contents due to its more acidic attack whose values were lower than the untreated one. The crystalline size of alkali treatment based fibers had 42.92 nm, which is lower than untreated one 62.02 nm. Thus the Pennisetum orientale grass can be suggested as a potential reinforcement for light-weight polymeric applications.
Characterization of microstructure, toughness, and chemical composition of friction-welded joints of UNS S32205 duplex stainless steel
(Tsinghua University Press, 2014-03-11) Ajith, Puthuparambil Madhavan; Sathiya, Paulraj; Aravindan, Sivanandam
Friction welding is a solid-state joining process which is applied extensively because of its advantages such as low heat input, efficient application, ease in manufacturing, and environmental friendliness. The present study investigates the mechanical and metallurgical properties of UNS S32205 duplex stainless steel friction-welded joints. The process parameters, namely friction pressure, upsetting pressure, and rotational speed are individually varied from low level to high level (within the range of the machine setup) and their effects on the joint properties are analyzed. The partial-deformation zone had higher hardness than the weld and base metal. The toughness of the joints was evaluated at room temperature and at subzero temperature conditions. The impact toughness of the friction-welded joints was found to be superior to fusion-joined duplex stainless steel in room and cryogenic conditions.
Deep learning for object recognition and defect analysis in additive manufacturing
(Discover, 2025-10-15) Thakur, Chandrbhan; Mishra, Santosh Kr.; Jose, S. Silva Sajin.; Singh, Purushottam Kumar; Upadhyay, Ram Krishna
Additive manufacturing (AM) offers design flexibility and shorter lead times in manufacturing newer products. The layer by layer manufacturing approach often introduces defects that can deteroriate part performance, which require reliable inspection to detect quality. Manual inspection often followed in industries are slow and error prone, which thrusts for the need to automate inspection. This work proposes a modular deep learning framework for objection detection and defect analysis components manufactured by fused deposition modelling. A real-world dataset of 950 images from additively manufactured elevator maintainance components, is taken to test the model and evaluate performance.YOLOv12 and Faster R-CNN are used for object detection, CNN for binary defect classification and MobileNet to classify both defect severity(Levels 0–3) and defect type. The model successfully predicted, whether an object was defective, determined its defect severity level, and correctly labeled the defect type with greater accuracy. YOLOv12 yielded slightly better results in comparison to Faster R-CNN for object detection with a precision of around 93.6% and recall of 95.6%. The model accurately identified whether an object was defective, determined its defect severity level, and correctly labeled the defect type with high precision.
Development and characterization of stainless steel fiber-based copper-free brake liner formulation: A positive solution for steel fiber replacement
(Tsinghua University Press, 2019-05-10) Vijay, R; Singaravelu, D. Lenin.; Jayaganthan, R
This study deals with the development of drum brake liner for a multi-utility vehicle possessing a hydraulic brake system by varying 7 weight % of steel fiber and stainless steel fiber each, in friction composite formulations. The developed friction composites were tested for physical, chemical, corrosion, mechanical, thermal properties, and tribological characteristics, under near-actual conditions using an inertia dynamometer as per industrial standards. Finite element analysis software (ANSYS) analysis was performed to show the thermal stress distribution of the developed friction composites at the maximum temperature rise due to heat generated during brake stops, and an extensive evaluation method was used to rank the composites. The study concludes that the brake factor of the stainless steel fiber-based friction composite produces stable performance in all conditions with a lower liner temperature rise of 340 °C and lower thermal stress at 4.255294 MPa. However, the steel fiber-based composites produced high performance at the beginning but deteriorated after a certain period due to higher levels of corrosion and a high temperature rise of 361 °C resulting in a negative fade (−0.84%) and more thermal stress (5.619102 MPa). The primary plateau, secondary plateau, back transfer of drum wear debris, and the distribution of constituents on the worn surface of the developed composites in a resin matrix were identified and studied using a scanning electron microscope (SEM) equipped with energy-dispersive spectroscopy. © 2019, The Author(s).
Edge Detection and Defects Checking of Binder Clip and Welding Joint using a Python-Based Algorithm: Applications in Quality Inspection
(Galati University Press, 2023-12-15) Murugan S. Senthil.; Sathiya. P; Hariharan, K; McJone, J; Nithiyanantham, K. K.
Machine vision is a computer vision system that enables a computer to work on image-based inspection and analysis for different applications. In this computer vision, a camera and sensor were used to view an image for its analysis with the help of some sort of algorithms, then processed to infer the image-based data. Machine vision systems along with Python programs can be used for many interdisciplinary applications like weld inspection, online monitoring in manufacturing auto components etc. In this study, the “Edge detection python algorithm” was developed and run through “Google Colab” notebook to inspect the edges and the boundaries of samples like faying surface-modified friction welded dissimilar joints and a binder clip (paper clamp) to check any defects or cracks and straightness etc. With the help of this Python algorithm, the edge detection was done by Sobel, Scharr, and Prewit operators. An input image of the weld joint and the binder clip were converted into Otsu’s binary threshold image. The matrix vision camera and the CMOS sensor were used in the machine vision set-up to take the images. This written algorithm is helpful to trace the edges of any kind of solids components. The edges of the binder clips and the weld joint/zone were detected. The binder clips were inspected under two different cases namely the clip in folding condition (Case I) and the binder clip in unfolding condition (Case II). The results showed a defect that was identified in the weld zone and no bending was in the binder clips. This kind of study is useful in manufacturing industries for quality inspection purposes with a new machine vision set up for online inspection of fabricated components like nuts and bolts etc.
Effect of Scanning Strategy on the Microstructure and Load-Bearing Characteristics of Additive Manufactured Parts
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-07-05) Sajin Jose, S. Silva; Mishra, Santosh Kr.; Upadhyay, Ram Krishna
Additive manufacturing has witnessed significant growth in recent years, revolutionizing the automotive and aerospace industries amongst others. Despite the use of additive manufacturing for creating complex geometries and reducing material consumption, there is a critical need to enhance the mechanical properties of manufactured parts to broaden their industrial applications. In this work, AISI 316L stainless steel is used to fabricate parts using three different strategies of the additively manufactured Laser Powder Bed Fusion (LPBF) technique, i.e., continuous, alternate, and island. This study aims to identify methods to optimize grain orientation and compaction support provided to the material under load, which influence the frictional and wear properties of the manufactured parts. The load-bearing capacity is evaluated by measuring the frictional and wear properties. The wear patch track is also examined to establish the physical mechanisms at the surface interface that lead to the smooth transition in response to the load. Grain orientation is compared across different strategies using Electron Backscatter Diffraction (EBSD) maps, and the influence of surface roughness on sliding behavior is also evaluated. The results demonstrate that the island scanning strategy yields the best performance for load-bearing applications, exhibiting superior grain orientation and hardness in the additively manufactured parts.
Effect of temperature and strain rate on compressive response of extruded magnesium nano-composite
(National Engg. Reaserch Center for Magnesium Alloys, 2015-10-01) Selvam, B; Marimuthu, P; Narayanasamy, R; Senthilkumar, V; Tun, K.S.; Gupta, M
The hot deformation behaviour of extruded magnesium-zinc oxide nano composite has been studied using hot compression test. The test was conducted in the temperature range of 250-400 °C and in the strain rate range of 0.01 to 1.5 s-1.The processing map was obtained using the power dissipation efficiency with the functions of temperature and strain rate. The workability and instability domains were observed in the processing map for a nano composite. The optical microscopy (OM), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images were used to confirm the formation of dynamic recrystallization (DRX), dynamic recovery (DRY) and instability regions. The workability region of the composite was identified at a working temperature of 400 °C and the strain rate of 0.01 s-1 from the processing map. The instability regions were observed at higher strain rates (>0.1 s-1) and temperatures (250-400 °C).
Efficient computation and design of high speed double precision Vedic multiplier architecture
(Nature Research, 2026-02-05) Kumar, Aruru Sai; Sahitya G.; Kusuma, Rambabu; Krishna, M. Sankush; Reddy, B. Naresh Kumar; Tripathi, Suman Lata
Efficient multiplication and addition of floating-point numbers play a crucial role in digital signal processing applications. To achieve high computational performance with minimal resource utilization, an optimized multiplication approach is essential. Vedic mathematics encompasses the utilization of 16 sutras or algorithms. This paper presents a double-precision floating-point multiplier of 53-bit mantissa based on Vedic mathematics. The proposed architecture performs multiplication in three stages: sign generation, exponent generation, and mantissa multiplication. The Urdhva Tiryakbhyam sutra is employed for mantissa computation owing to its high efficiency and reduced hardware complexity compared to conventional techniques. The proposed multiplier design is implemented using Verilog HDL on Vivado 2022.2. Experimental results demonstrate a significant reduction in critical path delay and logic utilization compared to existing floating-point and Vedic-based multipliers, while maintaining a favorable power consumption trend. The CNN implementation employing the proposed Vedic double-precision floating-point multiplier achieves the lowest inference latency and power consumption while maintaining identical classification accuracy compared to conventional IEEE-754 and existing Vedic-based multiplier designs. Hardware realization on a Zynq FPGA device further confirms the superiority of the proposed architecture in terms of power, delay and on-board component utilization.
Experimental and numerical analyses of magnesium alloy hot workability
(National Engg. Reaserch Center for Magnesium Alloys, 2016-10-25) Abbassi, F; Srinivasan, M; Loganathan, C; Gupta, M
Due to their hexagonal crystal structure, magnesium alloys have relatively low workability at room temperature. In this study, the hot workability behavior of cast-extruded AZ31B magnesium alloy is studied through hot compression testing, numerical modeling and microstructural analyses. Hot deformation tests are performed at temperatures of 250 °C to 400 °C under strain rates of 0.01 to 1.0 s−1. Transmission electron microscopy is used to reveal the presence of dynamic recrystallization (DRX), dynamic recovery (DRY), cracks and shear bands. To predict plastic instabilities during hot compression tests of AZ31B magnesium alloy, the authors use Johnson–Cook damage model in a 3D finite element simulation. The optimal hot workability of magnesium alloy is found at a temperature (T) of 400 °C and strain rate (ε˙) of 0.01 s−1. Stability is found at a lower strain rate, and instability is found at a higher strain rate.
Extraction and characterization of vetiver grass (Chrysopogon zizanioides) and kenaf fiber (Hibiscus cannabinus) as reinforcement materials for epoxy based composite structures
(Elsevier Editora Ltda, 2019-12-09) Khan, Anish; Vijay, R; Lenin, Sinaravelu D.; Arpitha, G. R.; Sanjay, M. R.; Siengchin, Mohammad; Alamry, Khalid; Asiri, Abdullah M.
The study deals with the mechanical characterization of vetiver grass fiber and kenaf fiber reinforced epoxy-based hybrid composites. Five types of composite laminates were developed through the hand lay-up process by varying the percentage of vetiver grass and kenaf fibers. The tensile, flexural, compression and impact tests were conducted as per ASTM. The fractured surfaces of the tested specimens were studied using a scanning electron microscope. From the results, it was shown that properties of epoxy composites were improved by hybridization with vetiver grass and kenaf fibers. The improved mechanical properties of fiber-reinforced composites were noticed in increment of percentage composition of kenaf fibers
Finite element modelling and characterization of friction welding on UNS S31803 duplex stainless steel joints
(Elsevier B.V., 2015-05-06) Asif. M, Mohammed; Shrikrishana, Kulkarni Anup; Sathiya, P.
Solid state joining techniques are increasingly employed in joining duplex stainless steel materials due to their high integrity. Continuous drive friction welding is a solid state welding technique which is used to join similar and dissimilar materials. This joining technique is characterized by short cycle time, low heat input and narrow heat affected zones. The simulation becomes an important tool in friction welding because of short welding cycle. In the present work, a three dimensional non-linear finite element model was developed. The thermal history and axial shortening profiles were predicted using ANSYS, a software tool. This numerical model was validated using experimental results. The results show that the frictional heating stage of the process has more influence on temperature and upsetting stage has more impact on axial shortening. The knowledge of these parameters would lead to optimization of input parameters and improvement of design and machine tools.
Fuzzy PD-Based Control for Excavator Boom Stabilization Using Work Port Pressure Feedback
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-07-04) Jose, Joseph. T.; Wrat, Gyan; Mishra, Santosh Kr.; Ranjan, Prabhat; Das, Jayanta
Hydraulic excavators operate in harsh environments where direct measurement of actuator chamber pressures and boom displacement is often unreliable or infeasible. This study presents a novel control strategy that estimates actuator chamber pressures from work port pressures using differential equations, eliminating the need for direct pressure or position sensors. A fuzzy logic-based proportional–derivative (PD) controller is developed to mitigate boom oscillations, particularly under high-inertia load conditions and variable operator inputs. The controller dynamically adjusts gains through fuzzy logic-based gain scheduling, enhancing adaptability across a wide range of operating conditions. The proposed method addresses the limitations of classical PID controllers, which struggle with the nonlinearities, parameter uncertainties, and instability introduced by counterbalance valves and pressure-compensated proportional valves. Experimental data is used to design fuzzy rules and membership functions, ensuring robust performance. Simulation and full-scale experimental validation demonstrate that the fuzzy PD controller significantly reduces pressure overshoot (by 23% during extension and 32% during retraction) and decreases settling time (by 31.23% and 28%, respectively) compared to conventional systems. Frequency-domain stability analysis confirms exponential stability and improved damping characteristics. The proposed control scheme enhances system reliability and safety, making it ideal for excavators operating in remote or rugged terrains where conventional sensor-based systems may fail. This approach is generalizable and does not require modifications to the existing hydraulic circuit, offering a practical and scalable solution for modern hydraulic machinery.
Gain enhancement of cross shaped patch antenna for IEEE 802.11ax Wi-Fi applications
(Electromagnetics Academy, 2018-12-07) Rajalakshmi, Pitchai; Gunavathi,. N
In this paper, a dual band high gain miniaturized cross shaped patch antenna is proposed for IEEE 802.11ax applications. The radiating patch size is 0.330λ0x0.417λ0 on a low cost Flame Retardant 4 substrate. A cross shaped radiating element is designed to cover the upper band of IEEE 802.11ax, and a four ring circular Complementary Split Ring Resonator (CSRR) is etched on the cross shaped radiating element to cover the lower band of IEEE802.11ax. Thus the dual bands of 802.11ax are achieved. In order to enhance the gain, 2x2 array hexagonal metamaterial unit cell is positioned behind the substrate. To extract the constitutive parameters of the circular CSRR, NRW (Nicolson-Ross-Wier) retrieval method is used. The measured maximum gain is approximately 6 dBi, 10 dBi for 2.4 GHz, 5 GHz, respectively. Parametric study on the geometrical dimensions is investigated using HFSS 15.0.
Hot deformation response of AL 6061-MWCNTs alloy composites
(Blue Eyes Intelligence Engineering and Sciences Publication, 2019-10-10) Jeyasimman, D; Senthilkumar V; Narayanasamy, R
In this investigation, the effect of multi walled carbon nanotubes (MWCNTs) on compressive response with Al 6061 alloy nanocomposites prepared by mechanical alloying has been investigated. Hot deformation tests required to develop processing map were conducted at three temperatures such as 250, 350 and 450°C and in the three strain rates of 0.01, 0.1 and 1.0 s-1. The development of geometric dynamic recrystallization (DRX), dynamic recovery (DRV), instability regions and shear bands were confirmed by characterization study of prepared nanocomposites after hot Compression tests. The average activation energies for hot compression response was calculated as 153.00 KJ/mole for 2 wt.% MWCNTs reinforced Al 6061 alloy (AA 6061) nanocomposites. The most favorable key processing parameters for hot deformation was identified as temperature between 370-450°C and the range of strain rate was 0.1-0.01s-1. The region which are prone to shear localization, cracks and other instability were identified using the processing map and the same was verified with microstructural images obtained using optical and SEM images. © BEIESP.
Influence of temperature and thermal cycles on the corrosion mechanism of wrought AZ91D magnesium alloy in simulated sea water solution
(Sciendo, 2023-12-26) Hariesh, S.P.; Dhanyanth, P. V.; Kughan, S. A.; Babu, Dhanush K.; Vaira Viganesh, R.; Sathiya, P.
This study successfully conducted a comprehensive analysis of the AZ91D magnesium alloy, encompassing microstructural, mechanical, and corrosion assessments. The microstructure consisted of primary α-Mg crystals and an aluminum-rich α-Mg/β-Mg17Al12 eutectic phase, with intermetallic phases predominantly precipitating at grain boundaries. The microhardness was quantified at 49.96 ± 1.76 HV. Thermostatic tests unveiled a noTab. increase in corrosion rates with rising temperatures, signaling reduced corrosion resistance at elevated environments. Conversely, thermos-cyclic tests showed relatively lower corrosion rates attributed to the accumulation of protective debris on the specimen surface, which could mitigate corrosion during temperature fluctuations. Electrochemical corrosion behavior revealed susceptibility to pitting corrosion at –1.204 V, limiting its application as a sacrificial anode in marine settings. © 2023 Sciendo. All rights reserved.

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