Browsing by Author "Sharma, Panchagnula Jayaprakash"

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Additive Manufacturing of Complex Shapes Through Weld-Deposition and Feature Based Slicing
(ASME, 2016-04) Sharma, Panchagnula Jayaprakash
Fabricating fully dense and functional metallic components is one of the important challenges in Additive Manufacturing (AM). Additive Manufacturing is a technology in which functional components can be fabricated rapidly and efficiently from their CAD models. It is also referred as Layered Manufacturing (LM) as the object is created by slicing the CAD model into layers and realizing each layer at a time. These layers are thin and stacked or glued together to get the physical shape of the CAD model. However, realizing overhanging features is a difficult task due to deficiency of support mechanism for metals. A separate support structure has to be deposited to build overhanging structures. Although, use of a distinct support material is quite common in non-metallic AM processes, such as Fused Deposition Modelling (FDM), and the same for metals is not yet available. The various techniques in AM process for fabricating metal parts can be mainly classified as laser based, electron beam based and arc based processes. While some Additive Manufacturing processes like Selective Laser Sintering (SLS) employ easily-breakable-scaffolds made of same material to realize the overhanging features, the same approach cannot be extended to deposition processes like laser or arc based direct energy deposition processes.
CoCoSo method-based optimization of cryogenic drilling on multi-walled carbon nanotubes reinforced composites
(Springer, 2022-05) Sharma, Panchagnula Jayaprakash
Continuous quest for lighter yet stronger materials has led to significant research in the field of composites. Modern-day nanocomposites have found widespread applications in diverse engineering sectors, which often require their machining. In this paper, multi-walled carbon nanotubes (MWCNTs) reinforced composites are subjected to drilling operation under cryogenic condition. To investigate the effects of different drilling parameters, like drill type, feed rate and spindle speed on delamination factors at drill entry and exit, circularity error and surface roughness, a three-level full factorial experimental study consisting of 27 experiments is carried out. To determine the optimal combination of drilling parameters, a recently developed multi-criteria decision making tool in the form of combined compromise solution (CoCoSo) method is employed. Five different objective criteria weight allocation techniques, i.e. mean weight method, standard deviation method, entropy method, criteria importance through intercriteria correlation method and method based on the removal effects of criteria are considered in this paper to avoid subjectivity in the decision making process. The optimal drilling parameters derived using the combined applications of CoCoSo and different criteria weight allocation techniques are also compared. Based on the experimental observations, it can be concluded that a TiCN coated drill with 10 mm/min feed rate and 1500 rpm spindle speed would provide the most desired response values during cryogenic drilling of MWCNTs reinforced composites.
A Complete Study on Various Area Filling Strategies Used in Weld Deposition-Based Additive Manufacturing
(Springer, 2021-06) Sharma, Panchagnula Jayaprakash
Achieving the optimal toolpath as well as obtaining the desired physical and geometrical properties for bulk metallic parts through weld deposition-based additive manufacturing (AM) is a challenging task. The current work aims in identifying the suitable toolpath for bulk weld deposition-based AM applications by comparing the various toolpath (eleven types) techniques. These toolpaths were evaluated based on the final layer thickness attained after face milling (skinning) operation, minimum amount material machined during the face milling, average hardness achieved, length of the heat-affected zone (HAZ) and the microstructural behaviour. Amongst the various toolpath patterns considered, hybrid toolpath (Single Contour Out with Hilbert In) is ideal for bulk deposition-based AM owing to its maximum final layer thickness and the minimum amount of material removed in skinning operation. On the other hand, it has been observed that Spiral Out to In toolpath pattern is inferior for bulk deposition-based AM. Additionally, the average grain size is presented for some of the toolpath patterns in the current article.
Design, Development, and Manufacturing of Cost-Effective Face Shields for COVID-19
(Springer, 2022-11) Sharma, Panchagnula Jayaprakash
COVID-19 is a highly contagious respiratory disease and is declared as a pandemic by the World Health Organization (WHO). COVID-19 has disrupted global supply chains including those of medical products and created severe shortage of personal protective equipment (PPE). To ease the situation, many universities, industries, maker communities, and hobbyists have come forward and shared their designs in the public domain, to enable manufacturing of PPE such as face shields with readily available materials in partnership with local industries. Face shield protects the facial region including the mucous membranes (eyes, nose, and mouth) from splashes of body fluids that could contain harmful pathogens, in this case the novel coronavirus. The design and manufacturing of two novel reusable, low-cost, lightweight, comfortable, and easy to wear face shields are presented in the current article. The headband in one face shield (referred as FS1) is realized via additive manufacturing (popularly known as 3D printing) and the other (denoted by FS2), using conventional milling operation. The novelty in FS1 is its headband, which is designed to cover the ears too while in FS2, the headband is made of 3-ply corrugated cardboard that is biodegradable and recyclable. A 175 microns thick, high transparency, scratch-resistant, and anti-fog sheet are used as the shield material. Mass-producing face shields at low costs (INR 20 or USD 0.27) with the selected manufacturing methods are proposed. Both products received very good feedback from frontline workers.
Effect of Cutting Environments on Drilling Induced Damage in GFRP Nanocomposites
(ASME, 2021-02) Sharma, Panchagnula Jayaprakash
Drilling is most commonly used secondary machining process for structural joining of Glass Fiber Reinforced Plastic (GFRP) composites. Performing drilling operations on GFRPs/Multi-Walled CarbonNanoTubes (MWCNTs) reinforced GFRPs is really a challenging task due to their non-homogeneity and anisotropic behavior, which directs to generation of material damages. The prime focus of current work is to identify the suitable process parameters for enhancing the performance of drilling of GFRP nanocomposites. In this study, the drilling experiments are conducted on 0.3wt.% MWCNT-GFRP nanocomposites with solid carbide, TiCN and TiAlN coated drills (6mm diameter) under dry and chilled air cutting environments. The dry drilling experiments are conducted without any assistance of cooling fluid in ambient condition. The chilled air at a temperature of 3°C was supplied from the vortex tube. Experimental data is used for ANOVA (balanced) analysis. The cutting parameters such as feed rate, cutting speed and tool type (coating) are considered as input and the measured thrust force, delamination factor and AE RMS signal are treated as output responses. From ANOVA results, it is observed that the influence of feed rate is more on thrust force as compared to cutting speed. The coefficients of determination (R2) shows good fit between thrust force and cutting parameters and the corresponding confidence levels are above 98% for all cutting environments. Similarly, R2 values of delamination factor and AE RMS signals are above 90% and 96% respectively. The minimum thrust force and torque values are noted as 12.61 N and 0.152 N-m respectively at lower feed rate (10 mm/min) and higher cutting speed (1500 RPM) using TiCN coated drill under chilled air cutting environment. The delamination factor is also low (1.025) under the same cutting conditions of minimum cutting forces. A good correlation exists between the thrust force vs. delamination factor (> 0.85) and the delamination factor vs. AE RMS signal (> 0.80) for the selected cutting environments. The recommended range of RMS voltage is 0.083 to 0.121 volts for producing the delamination free holes on GFRP nanocomposites.
Fabrication of hoop-wound glass fiber reinforced plastic cylindrical shells using filament winding machine
(Elsevier, 2020) Sharma, Panchagnula Jayaprakash
Glass Fiber Reinforced Plastic (GFRP) composites are playing an important role in the commercial industries like aerospace, marine and automotive, due to its notable material properties over metals. Development of these GFRPs for complex structures is really a challenging task owing to its heterogeneous and anisotropic nature. The present work is an attempt to develop an experimental setup to produce Hoop wound GFRP cylindrical shells using filament winding process. A constant mandrel speed of 45 revolutions per minute and glass fiber tension of 20 N is maintained during hoop winding process. The achieved samples had geometry of 140 mm length, 102 mm internal diameter and 2 mm thickness, which can fulfils the ASTM standards of transverse tensile and compressive tests.
Feature based Weld-Deposition for Additive Manufacturing of Complex Shapes
(Springer, 2016-08) Sharma, Panchagnula Jayaprakash
Fabricating functional metal parts using Additive Manufacturing (AM) is a leading trend. However, realizing overhanging features has been a challenge due to the lack of support mechanism for metals. Powder-bed fusion techniques like, Selective Laser Sintering (SLS) employ easily-breakable-scaffolds made of the same material to realize the overhangs. However, the same approach is not extendible to deposition processes like laser or arc based direct energy deposition processes. Although it is possible to realize small overhangs by exploiting the inherent overhanging capability of the process or by blinding some small features like holes, the same cannot be extended for more complex geometries. The current work presents a novel approach for realizing complex overhanging features without the need of support structures. This is possible by using higher order kinematics and suitably aligning the overhang with the deposition direction. Feature based non-uniform slicing and non-uniform area-filling are some vital concepts required in realizing the same and are briefly discussed here. This method can be used to fabricate and/or repair fully dense and functional components for various engineering applications. Although this approach has been implemented for weld-deposition based system, the same can be extended to any other direct energy deposition processes also.
Inclined slicing and weld-deposition for additive manufacturing of metallic objects with large overhangs using higher order kinematics
(Taylor & Francis, 2016-04) Sharma, Panchagnula Jayaprakash
This paper presents an automated tool path planning for deposition of overhanging features using GMAW-based weld-deposition. Overhanging features, although possible to a certain extent in power-bed process like SLS, remain a challenge in deposition-based processes. Deposition processes like weld-deposition-based AM realised smaller overhangs by exploiting the inherent overhang capability of the weld bead; but the same cannot be applicable for complex geometries with large overhangs. This paper explains an efficient way of depositing the overhanging features through weld-deposition, without use of supports, based on inclined slicing and deposition. This approach uses higher order kinematics, that is, adding extra degrees of mobility to workpiece. The methodology used for realising these inclined slices based on an in-house MATLAB code has also been presented. While this concept is implemented in the context of weld-deposition, it can be extended for any other metallic deposition processes as well.
Influence of Various Tool Path Patterns on Hardness Used in Weld Deposition-Based Additive Manufacturing
(Springer, 2019-10) Sharma, Panchagnula Jayaprakash
Identification of optimal tool path is critical for successful fabrication of bulk metallic parts using weld deposition-based additive manufacturing (AM). The various features of tool path, i.e., the number of starts and stops, convolutions, and continuity, have a significant effect on the geometric as well as physical properties of manufactured parts. Ideally, an optimised tool path is a continuous path with no self-intersecting pattern, with a minimum of starts and stops and minimum convoluted patterns. The tool paths available in the literature are unable to achieve all the listed requirements. Further, there are no one-to-one comparisons of these tool paths in detail in the literature. The present work aims in comparing various tool path techniques based on flatness achievable by minimum material skinned out during face milling (thickness of the deposited layer) and the hardness achieved. Experiments are performed using the in-house developed weld-based metallic AM workstation (weld deposition torch is retrofitted with a CNC).
Manufacture of complex thin-walled metallic objects using weld-deposition based additive manufacturing
(Elsevier, 2018-02) Sharma, Panchagnula Jayaprakash
Gas Metal Arc Welding (GMAW) based weld-deposition process is one of the deposition-based Additive Manufacturing (AM) processes with the ability to produce fully dense complex functional metallic objects. Due to its high deposition rates, high material and power efficiency, lower investment costs, simpler setup and work environment requirements it is slowly becoming a viable metallic AM method. Amongst various geometrical features that can be realized in weld-deposition based AM, the thin-walled features (i.e., features with one single deposition pass) are the toughest as the process has to overcome the bead-over-bead complexity. Based on geometric modelling and experimentation, this paper presents an efficient technique for producing the thin-walled metallic structures, including objects with undercut features. This is possible by adding extra degrees of freedom or by using higher order kinematics to the work piece and/or to the deposition head by suitably aligning the overhanging feature in-line to the deposition direction. An in-house MATLAB code was developed to slice the CAD model and generate the tool path for inclined deposition of a given layer of a thin-walled model. A geometrical model proposed to predict the layer thickness of a given layer during such bead-on-bead deposition showed good correlation with experimental data. Some illustrative complex thin-walled components successfully fabricated using this model have also been presented.
A new approach for attaining uniform properties in build direction in additive manufactured components through coupled thermal-hardness model
(Elsevier, 2019-04) Sharma, Panchagnula Jayaprakash
The theme of the investigation is to strategize uniform build direction properties in additive manufactured components. A computationally efficient model for prediction of layer-wise thermal cycle is developed using control volume approach. The thermal model is coupled with a hardness model to predict the hardness variation in the component. The predicted results are validated with hardness measurement and microstructure observation for a thin walled component of 60 layers produced by wire arc additive manufacturing. The experimental results strongly corroborate the computed cooling rates. The results show how the dynamic control of external conditions (e.g. substrate temperature) can be a very effective measure to attain uniform hardness in the build direction. An optimal strategy is presented for a candidate component. The investigation discloses new strategic steps to achieve uniform mechanical properties vis-à-vis in contrast to the conventional practice of cooling the substrate; the investigation suggests that heating the substrate to a pre-determined temperature and then cooling at a controlled rate during the deposition of layers helps to manage the properties in build direction.
A novel methodology to manufacture complex metallic sudden overhangs in weld-deposition based additive manufacturing
(Emerald, 2023-01) Sharma, Panchagnula Jayaprakash
Amongst various additive manufacturing (AM) techniques for realizing the complex metallic objects, weld-deposition (arc)-based directed energy AM technique is attaining more focus over commercially available powder bed fusion techniques. This is because of the capability of high deposition rates, high power and material utilization, simpler setup and less initial investment of arc-based AM. Nevertheless, realization of sudden overhanging features through arc-based weld-deposition techniques is still a challenging task because of the necessity of support structures. This paper aims to describe a novel methodology for producing complex metallic objects with sudden overhangs without using supports.
Prediction of drilling induced delamination and circularity deviation in GFRP nanocomposites using deep neural network
(Elsevier, 2022) Sharma, Panchagnula Jayaprakash; Jasti, Naga Vamsi Krishna
Drilling of Glass Fiber Reinforced Polymer (GFRP) nanocomposites is most prevailing topic to understand the composite behaviour under different cutting conditions. The present study is mainly focused on prediction of drilling output responses such as delamination factor and circularity error randomly with the help of deep neural network (DNN) model. L9 orthogonal array is used for experimentation. Drilling operation is performed on 0.3 wt% multi-walled carbon nano tubes reinforced GFRPs with solid carbide, TiCN and TiAlN coated (6 mm- diameter) twist drills. Based on experimental results, two different deep neural network models are prepared with single and double hidden layers by varying node numbers such as 8, 16, 32, 64, and 128. Thrust force, Acoustic Emission RMS voltage, and drill type (coating) are considered as input to the neural network and delamination factor at exit, circularity error are treated as predicted output responses for the given network model. The revealed predicted results recommended that two hidden layers with 32 nodes network model give the lowest absolute error of 0.08% and 3.13% in delamination factor and circularity errors respectively. Similarly, the highest absolute error is identified as 4.19% in delamination factor and 13.14% in circularity error by single hidden layer with 128 nodes. Therefore, it is urged that DNN is the most suitable modelling technique for prediction of drilling responses on GFRP nano composites.
Regression model-based parametric analysis of drilling of multi-walled carbon nanotubes-added glass fiber composite laminates
(IOP, 2024) Sharma, Panchagnula Jayaprakash; Jasti, Naga Vamsi Krishna
Multi-walled carbon nanotubes (MCNTs)-enhanced glass fiber composite (GFC) laminates are among the most promising materials for fulfilling various structural and non-structural requirements. They have also shown exceptional functional applications as excellent electrical and thermal conductors, as well as electromagnetic interference shielding materials. The present work primarily focuses on developing regression models for the drilling process of 0.3 wt% MCNTs-GFC laminates. For experimentation, three different coated drills—carbide, TiCN-coated, and TiAlN-coated—are used under both dry and chilled air cutting environments. The lowest thrust force, torque, and delamination factor were observed at a feed rate of 10 mm min−1 and a speed of 1500 RPM using a TiCN-coated drill in a chilled air environment. Regression analysis reveals that feed rate significantly influences thrust force, as justified by the R2 value, which is above 90% for the selected cutting conditions. The corresponding t and F statistics values indicate the statistical significance of the relevant explanatory factors. The efficiency of the developed models is further validated by considering the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values, which are 136.9 and 144.7, respectively. These values indicate a good regression fit and likelihood of the models for data prediction. Additionally, there is a strong correlation (coefficient > 0.85) between thrust force and delamination factor under the selected cutting environments. Concurrently, the developed regression models are simulated and evaluated for random experiments (Nos. 87, 125, 187, 243, 244, and 399), and the predicted responses closely match the experimental values.