Ramesh Chand, Vishal S. Sharma, Rajeev Trehan and Munish Kumar Gupta
A nut bolt joint is a primary device that connects mechanical components. The vibrations cause bolted joints to self-loosen. Created by motors and engines, leading to machine…
Abstract
Purpose
A nut bolt joint is a primary device that connects mechanical components. The vibrations cause bolted joints to self-loosen. Created by motors and engines, leading to machine failure, and there may be severe safety issues. All the safety issues and self-loosen are directly and indirectly the functions of the accuracy and precision of the fabricated nut and bolt. Recent advancements in three-dimensional (3D) printing technologies now allow for the production of intricate components. These may be used technologies such as 3D printed bolts to create fasteners. This paper aims to investigate dimensional precision, surface properties, mechanical properties and scanning electron microscope (SEM) of the component fabricated using a multi-jet 3D printer.
Design/methodology/approach
Multi-jet-based 3D printed nut-bolt is evaluated in this paper. More specifically, liquid polymer-based nut-bolt is fabricated in sections 1, 2 and 3 of the base plate. Five nuts and bolts are fabricated in these three sections.
Findings
Dimensional inquiry (bolt dimension, general dimensions’ density and surface roughness) and mechanical testing (shear strength of nut and bolt) were carried out throughout the study. According to the ISO 2768 requirements for the General Tolerances Grade, the nut and bolt’s dimensional examination (variation in bolt dimension, general dimensions) is within the tolerance grades. As a result, the multi-jet 3D printing (MJP)-based 3D printer described above may be used for commercial production. In terms of mechanical qualities, when the component placement moves from Sections 1 to 3, the density of the manufactured part decreases by 0.292% (percent) and the shear strength of the nut and bolt decreases by 30%. According to the SEM examination, the density of the River markings, sharp edges, holes and sharp edges increased from Sections 1 to 3, which supports the findings mentioned above.
Originality/value
Hence, this work enlightens the aspects causing time lag during the 3D printing in MJP. It causes variation in the dimensional deviation, surface properties and mechanical properties of the fabricated part, which needs to be explored.
Details
Keywords
Shekhar Srivastava, Rajiv Kumar Garg, Vishal S. Sharma, Noe Gaudencio Alba-Baena, Anish Sachdeva, Ramesh Chand and Sehijpal Singh
This paper aims to present a systematic approach in the literature survey related to metal additive manufacturing (AM) processes and its multi-physics continuum modelling approach…
Abstract
Purpose
This paper aims to present a systematic approach in the literature survey related to metal additive manufacturing (AM) processes and its multi-physics continuum modelling approach for its better understanding.
Design/methodology/approach
A systematic review of the literature available in the area of continuum modelling practices adopted for the powder bed fusion (PBF) AM processes for the deposition of powder layer over the substrate along with quantification of residual stress and distortion. Discrete element method (DEM) and finite element method (FEM) approaches have been reviewed for the deposition of powder layer and thermo-mechanical modelling, respectively. Further, thermo-mechanical modelling adopted for the PBF AM process have been discussed in detail with its constituents. Finally, on the basis of prediction through thermo-mechanical models and experimental validation, distortion mitigation/minimisation techniques applied in PBF AM processes have been reviewed to provide a future direction in the field.
Findings
The findings of this paper are the future directions for the implementation and modification of the continuum modelling approaches applied to PBF AM processes. On the basis of the extensive review in the domain, gaps are recommended for future work for the betterment of modelling approach.
Research limitations/implications
This paper is limited to review only the modelling approach adopted by the PBF AM processes, i.e. modelling techniques (DEM approach) used for the deposition of powder layer and macro-models at process scale for the prediction of residual stress and distortion in the component. Modelling of microstructure and grain growth has not been included in this paper.
Originality/value
This paper presents an extensive review of the FEM approach adopted for the prediction of residual stress and distortion in the PBF AM processes which sets the platform for the development of distortion mitigation techniques. An extensive review of distortion mitigation techniques has been presented in the last section of the paper, which has not been reviewed yet.
Details
Keywords
Shekhar Srivastava, Rajiv Kumar Garg, Anish Sachdeva, Vishal S. Sharma, Sehijpal Singh and Munish Kumar Gupta
Gas metal arc-based directed energy deposition (GMA-DED) process experiences residual stress (RS) developed due to heat accumulation during successive layer deposition as a…
Abstract
Purpose
Gas metal arc-based directed energy deposition (GMA-DED) process experiences residual stress (RS) developed due to heat accumulation during successive layer deposition as a significant challenge. To address that, monitoring of transient temperature distribution concerning time is a critical input. Finite element analysis (FEA) is considered a decisive engineering tool in quantifying temperature and RS in all manufacturing processes. However, computational time and prediction accuracy has always been a matter of concern for FEA-based prediction of responses in the GMA-DED process. Therefore, this study aims to investigate the effect of finite element mesh variations on the developed RS in the GMA-DED process.
Design/methodology/approach
The variation in the element shape functions, i.e. linear- and quadratic-interpolation elements, has been used to model a single-track 10-layered thin-walled component in Ansys parametric design language. Two cases have been proposed in this study: Case 1 has been meshed with the linear-interpolation elements and Case 2 has been meshed with the combination of linear- and quadratic-interpolation elements. Furthermore, the modelled responses are authenticated with the experimental results measured through the data acquisition system for temperature and RS.
Findings
A good agreement of temperature and RS profile has been observed between predicted and experimental values. Considering similar parameters, Case 1 produced an average error of 4.13%, whereas Case 2 produced an average error of 23.45% in temperature prediction. Besides, comparing the longitudinal stress in the transverse direction for Cases 1 and 2 produced an error of 8.282% and 12.796%, respectively.
Originality/value
To avoid the costly and time-taking experimental approach, the experts have suggested the utilization of numerical methods in the design optimization of engineering problems. The FEA approach, however, is a subtle tool, still, it faces high computational cost and low accuracy based on the choice of selected element technology. This research can serve as a basis for the choice of element technology which can predict better responses in the thermo-mechanical modelling of the GMA-DED process.
Details
Keywords
Ramesh Chand, Vishal S. Sharma, Rajeev Trehan and Munish Kumar Gupta
The purpose of this study is to find the best geometries among the cylindrical, enamel and honeycomb geometries based upon the mechanical properties (tensile test, compression…
Abstract
Purpose
The purpose of this study is to find the best geometries among the cylindrical, enamel and honeycomb geometries based upon the mechanical properties (tensile test, compression test and shear test). Further this obtained geometry could be used to fabricate products like exoskeleton and its supporting members.
Design/methodology/approach
The present research focuses on the mechanical testing of cylindrical, enamel and honeycomb-shaped parts fabricated through multi-jet printing (MJP) process with a wall thickness of 0.26, 0.33, 0.4 and 0.66 mm. The polymer specimens (for tensile, compression and shear tests) were fabricated using a multi-jet fusion process. The experimental results were compared with the numerical modelling. Finally, the optimal geometry was obtained, and the influence of wall thicknesses on various mechanical properties (tensile, compression and shear) was studied.
Findings
In comparison to cylindrical, enamel structures the honeycomb structures required less time to fabricate and had lower tensile, compressive and shear strengths. The most efficient geometry for fully functional parts where tensile, compressive and shear forces are present during application – cylindrical geometry is preferred followed by enamel, and then honeycomb. It was found that as the wall thickness of various geometries was increased, their ability to withstand tensile, compressive and shear loads also enhanced. The enamel shape structure exhibits greater strain energy storage capacity than other shape structures for compressive loads, and the strength to resist the compressive load will be lower. In the case of cylindrical geometries for tensile loading, the resisting area toward the loading will be higher in comparison to honeycomb- and enamel-based structures. At the same time, the ability to store the stain energy is less. The results of the tensile, compression and shear load finite element analysis using ANSYS are in agreement with those of the experiments.
Originality/value
From the insight of literature review, it is found that a wide range of work is done on fused deposition modeling (FDM) process. But in comparison to FDM, the MJP provide the better dimensional accuracy and surface properties (Lee et al., 2020). Therefore, it is observed that past research works not incorporated the effect of wall thickness of the embedded geometries on mechanical properties of the part fabricated on MJP (Gibson, n.d.). Hence, in this work, effect of wall thickness on tensile, compression and shear strength is considered as the main factor for the honeycomb, enamel and cylindrical geometries.
Details
Keywords
Shrutika Sharma, Vishal Gupta, Deepa Mudgal and Vishal Srivastava
Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to…
Abstract
Purpose
Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates.
Design/methodology/approach
The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R2) and mean absolute error (MAE).
Findings
Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments.
Research limitations/implications
The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study.
Originality/value
This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.
Details
Keywords
Vishal Singh and Arvind K. Rajput
The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal…
Abstract
Purpose
The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal bearing (MHJB) system.
Design/methodology/approach
To simulate the behaviour of PVP lubricant in clearance space of the MHJB system, the modified form of Reynolds equation is numerically solved by using finite element method. Galerkin’s method is used to obtain the weak form of the governing equation. The system equation is solved by Gauss–Seidal iterative method to compute the unknown values of nodal oil film pressure. Subsequently, performance characteristics of bearing system are computed.
Findings
The simulated results reveal that the location of pressurised lubricant inlets significantly affects the oil film pressure distribution and may cause a significant effect on the characteristics of bearing system. Further, the use of PVP lubricant may significantly enhances the performance of the bearing system, namely.
Originality/value
The present work examines the influence of pocket orientation with respect to loading direction on the characteristics of PVP fluid lubricated MHJB system and provides vital information regarding the design of journal bearing system.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0241/
Details
Keywords
Stephen Linacre, Jessica Green and Vishal Sharma
Carers of people with eating disorders (EDs) experience high levels of burden which can lead to clinical levels of depression and anxiety, high levels of expressed emotion and can…
Abstract
Purpose
Carers of people with eating disorders (EDs) experience high levels of burden which can lead to clinical levels of depression and anxiety, high levels of expressed emotion and can lead to a non-conducive environment to support recovery. The Maudsley Method skills-based workshops can empower carers to support people with ED to move towards recovery, reduce carer burden and high levels of distress. The paper aims to discuss these issues.
Design/methodology/approach
Adaptations have been made to the Maudsley Method skills based workshops to include evidence based approaches from cognitive remediation therapy; mindfulness and acceptance commitment therapy. The adapted workshops were assessed via a pilot study with ten carers of people with ED using a mixed method design. The Experience of Caregiving Inventory and SF-36 were used to assess aspects of caregiving and carer wellbeing, respectively pre and post intervention. Thematic analysis was used to evaluate carers’ views on the intervention.
Findings
Results indicated that carers reduced their level of burden particularly in their experience of stigma, dependency and loss. Furthermore, positive aspects of the relationship with the person with the ED improved. Thematic analysis was used to obtain feedback from carers of the workshops. Qualitative data identified that carers improved their self-awareness, understanding of ED and the techniques they could use, and increased their social support.
Research limitations/implications
Further research is required to compare the original workshops with this adapted intervention.
Originality/value
Although this is a pilot study, the results suggest that further evidence based interventions could be added to the Maudsley Method approach to support carers.
Details
Keywords
Shrutika Sharma, Vishal Gupta and Deepa Mudgal
The implications of metallic biomaterials involve stress shielding, bone osteoporosis, release of toxic ions, poor wear and corrosion resistance and patient discomfort due to the…
Abstract
Purpose
The implications of metallic biomaterials involve stress shielding, bone osteoporosis, release of toxic ions, poor wear and corrosion resistance and patient discomfort due to the need of second operation. This study aims to use additive manufacturing (AM) process for fabrication of biodegradable orthopedic small locking bone plates to overcome complications related to metallic biomaterials.
Design/methodology/approach
Fused deposition modeling technique has been used for fabrication of bone plates. The effect of varying printing parameters such as infill density, layer height, wall thickness and print speed has been studied on tensile and flexural properties of bone plates using response surface methodology-based design of experiments.
Findings
The maximum tensile and flexural strengths are mainly dependent on printing parameters used during the fabrication of bone plates. Tensile and flexural strengths increase with increase in infill density and wall thickness and decrease with increase in layer height and wall thickness.
Research limitations/implications
The present work is focused on bone plates. In addition, different AM techniques can be used for fabrication of other biomedical implants.
Originality/value
Studies on application of AM techniques on distal ulna small locking bone plates have been hardly reported. This work involves optimization of printing parameters for development of distal ulna-based bone plate with high mechanical strength. Characterization of microscopic fractures has also been performed for understanding the fracture behavior of bone plates.
Details
Keywords
Rakesh Chandmal Sharma, Vishal Dabra, Gurpreet Singh, Rajender Kumar, Ravi Pratap Singh and Sameer Sharma
Stainless steel is widely used in different manufacturing sectors. The purpose of this study is to optimize the process parameters of machining while processing SS316L alloy. The…
Abstract
Purpose
Stainless steel is widely used in different manufacturing sectors. The purpose of this study is to optimize the process parameters of machining while processing SS316L alloy. The optimization of machining characteristics in the case of SS316L alloy greatly improves the quality and productivity economically.
Design/methodology/approach
The machining variables in current research are depth of cut, spindle speed and feed rate. The optimization of response characteristics was carried out using the intelligent approach of grey, regression and teaching learning-based optimization (TLBO) and Taguchi-Grey approach. Planning of experiments was made using Taguchi’s based L27 orthogonal array. With the implementation of grey, the response characteristics were normalized and converted into a single response. The regression analysis was used for empirical modeling of the single response induced from the grey application. TLBO is further used to investigate the combinations of machining variables and compared with grey theory.
Findings
The grey-TLBO based multi-criteria decision-making approach suggests that the optimized setting for material removal rate, mean roughness depth (Rz) and cutting force (Fz) is spindle speed (N): 720 rpm; feed rate (F): 0.3 mm/rev; depth of cut (DoC): 1.7 mm. The grey theory suggests an optimized setting as N: 720 rpm; F: 0.2 mm/rev and DoC: 1.7 mm.
Originality/value
The parametric optimization during the turning of SS316L using grey-TLBO based intelligent approach is not performed till now. Thus, this intelligent approach will give a path to the researchers working in this direction. However, the grey theory performs better as compared to the grey-TLBO approach.