Search results

This paper aims to propose a new framework on prioritizing and deployment of design for additive manufacturing (DfAM) strategies to an industrial component using Fuzzy TOPSIS multiple criteria decision-making (MCDM) techniques. The proposed framework is then applied to an automotive component, and the results are discussed and compared with existing design.

Eight DfAM design alternatives associated with eight design criteria have been identified for framing new DfAM strategies. The prioritization order of the design alternatives is identified by Fuzzy TOPSIS MCDM technique through its closeness coefficient. Based on Fuzzy TOPSIS MCDM output, each of the design alternatives is applied sequentially to an automobile component as a case study. Redesign is carried out at each stage of DfAM implementation without affecting the functionality.

On successful implementation of proposed framework to an automotive component, the mass is reduced by 43.84%, from 0.429 kg to 0.241 kg. The redesign is validated by finite element analysis, where von Mises stress is less than the yield stress of the material.

The proposed DfAM framework and strategies will be useful to designers, R&D engineers, industrial practitioners, experts and consultants for implementing DfAM strategies on any industrial component without impacting its functionality.

To the best of the authors’ knowledge, the idea of prioritization and implementation of DfAM strategies to an automotive component is the original contribution.

Additive Manufacturing (AM) conventionally necessitates an intermediary slicing procedure using the standard tessellation language (STL) data, which can be computationally burdensome, especially for intricate microcellular architectures. This study aims to propose a direct slicing method tailored for digital light processing-type AM processes for the efficient generation of slicing data for microcellular structures.

The authors proposed a direct slicing method designed for microcellular structures, encompassing micro-lattice and triply periodic minimal surface (TPMS) structures. The sliced data of these structures were represented mathematically and then convert into 2D monochromatic images, bypassing the time-consuming slicing procedures required by 3D STL data. The efficiency of the proposed method was validated through data preparations for lattice-based nasopharyngeal swabs and TPMS-based ellipsoid components. Furthermore, its adaptability was highlighted by incorporating 2D images of additional features, eliminating the requirement for complex 3D Boolean operations.

The direct slicing method offered significant benefits upon implementation for microcellular structures. For lattice-based nasopharyngeal swabs, it reduced data size by a factor of 1/300 and data preparation time by a factor of 1/8. Similarly, for TPMS-based ellipsoid components, it reduced data size by a factor of 1/60 and preparation time by a factor of 1/16.

The direct slicing method allows for bypasses the computational burdens associated with traditional indirect slicing from 3D STL data, by directly translating complex cellular structures into 2D sliced images. This method not only reduces data volume and processing time significantly but also demonstrates the versatility of sliced data preparation by integrating supplementary features using 2D operations.

The purpose of this paper is to compare the influence of relative density (RD) and strain rates on failure mechanism and specific energy absorption (SEA) of polyamide lattices ranging from bending to stretch-dominated structures using selective laser sintering (SLS).

Three bending and two stretch-dominated unit cells were selected based on the Maxwell stability criterion. Lattices were designed with three RD and fabricated by SLS technique using PA12 material. Quasi-static compression tests with three strain rates were carried out using Taguchi's L9 experiments. The lattice compressive behaviour was verified with the Gibson–Ashby analytical model.

It has been observed that RD and strain rates played a vital role in lattice compressive properties by controlling failure mechanisms, resulting in distinct post-yielding responses as fluctuating and stable hardening in the plateau region. Analysis of variance (ANOVA) displayed the significant impact of RD and emphasised dissimilar influences of strain rate that vary to cell topology. Bending-dominated lattices showed better compressive properties than stretch-dominated lattices. The interesting observation is that stretch-dominated lattices with over-stiff topology exhibited less compressive properties contrary to the Maxwell stability criterion, whereas strain rate has less influence on the SEA of face-centered and body-centered cubic unit cells with vertical and horizontal struts (FBCCXYZ).

This comparative study is expected to provide new prospects for designing end-user parts that undergo various impact conditions like automotive bumpers and evolving techniques like hybrid and functionally graded lattices.

To the best of the authors' knowledge, this is the first work that relates the strain rate with compressive properties and also highlights the lattice behaviour transformation from ductile to brittle while the increase of RD and strain rate analytically using the Gibson–Ashby analytical model.

This paper aims to discuss the development of a defect classification system that can be used to detect and classify powder bed surface defects from captured layer images without the need for specialised computational hardware. The idea is to develop this system by making use of more traditional machine learning (ML) models instead of using computationally intensive deep learning (DL) models.

The approach that is used by this study is to use traditional image processing and classification techniques that can be applied to captured layer images to detect and classify defects without the need for DL algorithms.

The study proved that a defect classification algorithm could be developed by making use of traditional ML models with a high degree of accuracy and the images could be processed at higher speeds than typically reported in literature when making use of DL models.

This paper addresses a need that has been identified for a high-speed defect classification algorithm that can detect and classify defects without the need for specialised hardware that is typically used when making use of DL technologies. This is because when developing closed-loop feedback systems for these additive manufacturing machines, it is important to detect and classify defects without inducing additional delays to the control system.

This paper aims to determine the impact of perceived virtuality on team dynamics and outcomes by adopting the Input-Mediators-Outcome (IMO) framework. Further, it also investigates the mediating role of team processes and emergent states.

The authors collected survey data from 315 individuals working in virtual teams (VTs) in the information technology sector in India using both offline and online questionnaires. They performed the analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The authors investigated two sets of hypotheses – both direct and indirect (or mediation interactions). Results show that psychological empowerment and conflict management are significant in managing VTs. Also, perceived virtuality impacts team outcomes, i.e. perceived team performance, team satisfaction and subjective well-being.

The interplay between the behavioural team process (conflict management) and the emergent state (psychological empowerment) was examined. The study also helps broaden our understanding of the various psychological variables associated with teamwork in the context of VTs.

Findings from this study will aid in assessing the consequences of virtual teamwork at both individual and organisational levels, such as guiding the design and sustainability of VT arrangements, achieving higher productivity in VTs, and designing effective and interactive solutions in the virtual space.

The study examined the interplay between behavioural team processes (such as conflict management) and emergent states (such as psychological empowerment). The study also theorises and empirically tests the relationships between perceived virtuality and team outcomes (i.e. both affective and effectiveness). It may serve as a guide to understanding team dynamics in VTs better.

This exploratory study attempts to enhance the current understanding of the research and practice of VTs within a developing economy.

One of the critical reasons for the nonacceptance of additive manufacturing (AM) processes is the lack of understanding and structured knowledge of design for additive manufacturing (DfAM). This paper aims to assist designers to select the appropriate AM technology for product development or redesign. Using the suggestion provided by the design assist tool, the user’s design alterations depend on their ability to interpret the suggestion into the design without affecting the design’s primary objective.

This research reports the development of a tool that evaluates the efficacy values for all seven major standard AM processes by considering design parameters, benchmark standards within the processes and their material efficacies. In this research, the tool provides analytical and visual approaches to suggestion and assistance. Seventeen design parameters and seven benchmarking standards are used to evaluate the proposed product and design quality value. The full factorial design approach has been used to evaluate the DfAM aspects, design quality and design complexity.

The outcome is evaluated by the product and design quality value, material suit and material-product-design (MPD) value proposed in this work for a comparative assessment of the AM processes for a design. The higher the MPD value, the better the process. The visual aspect of the evaluation uses spider diagrams, which are evaluated analytically to confirm the results’ appropriateness with the proposed methodology.

The data used in the database is assumed to make the study comprehensive. The output aims to help opt for the best process out of the seven AM techniques for better and optimized manufacturing. This, as per the authors’ knowledge, is not available yet.

School counselors are committed to serving students' social-emotional, postsecondary, and academic needs while they navigate primary and secondary school (American School Counselor Association, 2019). Much has been said about the ways in which school counselors can impact postsecondary outcomes and social emotional health. It is important that we also address the ways school counselors can impact positive academic outcomes as it is intertwined in postsecondary options and success. For Black males, academic success has traditionally been met with systemic barriers (i.e., school-to-prison pipeline, lower graduation rates, lower incomes, higher unemployment rates, and lower college going rates (National Center for Edcuation Statisitics, 2019a, 2019b, 2020a, 2020b) and low expectations. School counselors are charged to be leaders and change agents for social justice and equity in our schools by the American School Counselor Association (ASCA, 2019) and can impact systemic change. This chapter will explore ways in which school counselors can impact positive academic outcomes for Black males. School counselors as change agents and advocates are positioned to make a real impact for Black male academic success. The authors will also provide some recommendations and best practices for elementary, middle, and high school counselors as they work with students, teachers, and families from an anti-deficit model as outlined by Harper (2012).

Three-dimensional (3D) printing has great potential in the food industry. While 3D printing technology offers customised food products to consumers, it also allows producers to develop new products using a wide variety of alternative food ingredients, modernise the production process and carry out environmentally friendly production. This research aims to determine the attitudes of students towards 3D foods who are studying in the Department of Gastronomy and Culinary Arts, as they are both consumers and examine different food processing systems and use them in the field of application. As a result of the study, it was identified that the participants believed that 3D printing is a great modern technology that allows the development of new foods, that it will bring benefit to us in the future, reduce the cost of food and food waste, increase the sustainability of food and that they see it as environmentally friendly. In addition, it was determined that the participants did not think that 3D-printed foods were disgusting; they found these foods reliable, could try them in the future and were excited to experience them.

This study aims to comprehensively investigate the mixed-mode fracture behavior and mechanical properties of selective laser sintering (SLS) polyamide 12 (PA12) components, considering different build orientations and layer thicknesses. The primary objectives include the following. Conducting mixed-mode fracture and mechanical analyses on SLS PA12 parts. Investigating the influence of build orientation and layer thickness on the mechanical properties of SLS-printed components. Examining the fracture mechanisms of SLS-produced Arcan fracture and tensile specimens through experimental methods and finite element analyses.

The research used a combination of experimental techniques and numerical analyses. Tensile and Arcan fracture specimens were fabricated using the SLS process with varying build orientations (X, X–Y, Z) and layer thicknesses (0.1 mm, 0.2 mm). Mechanical properties, including tensile strength, modulus of elasticity and critical stress intensity factor, were quantified through experimental testing. Mixed-mode fracture tests were conducted using a specialized fixture, and finite element analyses using the J-integral method were performed to calculate fracture toughness. Scanning electron microscopy (SEM) was used for detailed morphological analysis of fractured surfaces.

The investigation revealed that the highest tensile properties were achieved in samples fabricated horizontally in the X orientation with a layer thickness of 0.1 mm. Additionally, parts manufactured with a layer thickness of 0.2 mm exhibited favorable mixed-mode fracture behavior. The results emphasize the significance of build orientation and layer thickness in influencing mechanical properties and fracture behavior. SEM analysis provided valuable insights into the failure mechanisms of SLS-produced PA12 components.

This study contributes to the field of additive manufacturing by providing a comprehensive analysis of the mixed-mode fracture behavior and mechanical properties of SLS-produced PA12 components. The investigation offers novel insights into the influence of build orientation and layer thickness on the performance of such components. The combination of experimental testing, numerical analyses and SEM morphological observations enhances the understanding of fracture behavior in additive manufacturing processes. The findings contribute to optimizing the design and manufacturing of high-quality PA12 components using SLS technology.

Fused Filament Fabrication (FFF) is an extrusion-based manufacturing process using fused thermoplastics. Despite its low cost, the FFF is not extensively used in high-value industrial sectors mainly due to parts' anisotropy (related to the deposition strategy) and residual stresses (caused by successive heating cycles). Thus, this study aims to investigate the process improvement and the optimization of the printed parts.

In this work, a meshless technique – the Radial Point Interpolation Method (RPIM) – is used to numerically simulate the viscoplastic extrusion process – the initial phase of the FFF. Unlike the FEM, in meshless methods, there is no pre-established relationship between the nodes so the nodal mesh will not face mesh distortions and the discretization can easily be modified by adding or removing nodes from the initial nodal mesh. The accuracy of the obtained results highlights the importance of using meshless techniques in this field.

Meshless methods show particular relevance in this topic since the nodes can be distributed to match the layer-by-layer growing condition of the printing process.

Using the flow formulation combined with the heat transfer formulation presented here for the first time within an in-house RPIM code, an algorithm is proposed, implemented and validated for benchmark examples.