The last few decades have seen rapid growth in additive manufacturing (AM) technologies. AM has implemented a novel method of production in design, manufacture, and delivery to end-users. Accordingly, AM technologies have given great flexibility in design for building complex components, highly customized products, effective waste minimization, high material variety, and sustainable products. This review paper addresses the evolution of engineering design to take advantage of the opportunities provided by AM and its applications. It discusses issues related to the design of cellular and support structures, build orientation, part consolidation and assembly, materials, part complexity, and product sustainability.

The integration of medical signal processing capabilities and advanced sensors into Internet of Things (IoT) devices plays a key role in providing comfort and convenience to human lives. As the number of patients is increasing gradually, providing healthcare facilities to each patient, particularly to the patients located in remote regions, not only has become challenging but also results in several issues, such as: (i) increase in workload on paramedics, (ii) wastage of time, and (iii) accommodation of patients. Therefore, the design of smart healthcare systems has become an important area of research to overcome these above-mentioned issues. Several healthcare applications have been designed using wireless sensor networks (WSNs), cloud computing, and fog computing. Most of the e-healthcare applications are designed using the cloud computing paradigm. Cloud-based architecture introduces high latency while processing huge amounts of data, thus restricting the large-scale implementation of latency-sensitive e-healthcare applications. Fog computing architecture offers processing and storage resources near to the edge of the network, thus, designing e-healthcare applications using the fog computing paradigm is of interest to meet the low latency requirement of such applications. Patients that are minors or are in intensive care units (ICUs) are unable to self-report their pain conditions. The remote healthcare monitoring applications deploy IoT devices with bio-sensors capable of sensing surface electromyogram (sEMG) and electrocardiogram (ECG) signals to monitor the pain condition of such patients. In this article, fog computing architecture is proposed for deploying a remote pain monitoring system. The key motivation for adopting the fog paradigm in our proposed approach is to reduce latency and network consumption. To validate the effectiveness of the proposed approach in minimizing delay and network utilization, simulations were carried out in iFogSim and the results were compared with the cloud-based systems. The results of the simulations carried out in this research indicate that a reduction in both latency and network consumption can be achieved by adopting the proposed approach for implementing a remote pain monitoring system.

Purpose: The Pulsed Laser Powder Bed Fusion (PBF) process is an additive manufacturing technology that uses a laser with pulsed beam to melt metal powder. In this case Stainless Steel SS316L alloy is used to produce complex components. To produce components with acceptable mechanical performance requires a comprehensive understanding of process parameters and their interactions. This study aims to understand the influence of process parameters on reducing porosity and increasing part density. Design/methodology/approach: The Response Surface Method (RSM) is used to investigate the impact of changing critical parameters on the density of parts manufactured. Parameters considered include: point distance, exposure time, hatching distance and layer thickness. Part density was used to identify the most statistically significant parameters, before each parameter was analysed individually. Findings: A clear correlation between the number and shape of pores and the process parameters was identified. Point distance, exposure time and layer thickness were found to significantly affect part density. The interaction between these parameters also critically affected the development of porosity. Finally, a regression model was developed and verified experimentally and used to accurately predict part density. Practical and Research limitations/implications: The study considered a range of selected parameters relevant to the SS316L alloy. These parameters need to be modified for other alloys according to their physical properties. Originality/value: This study is believed to be the first systematic attempt to use RSM for the design of experiments (DOE) to investigate the effect of process parameters of the pulsed-laser PBF process on the density of SS316L alloy components.

Triply periodic minimum surface (TPMS)-based lattice structures have gained interest for their outstanding capacity to absorb energy, their high load-bearing capacity, and their high surface-to-volume ratio. This study considered three TPMS cell topologies, including Diamond, Gyroid, and Primitive. The FDM process was used to print the lattice structures with two materials: pure polylactic acid (PLA) and carbon fiber-reinforced PLA (PLA + CF). The influence of carbon fiber (CF) incorporation, unit cell type (topologies) and size, and relative density (RD) on mechanical properties and failure patterns were explored comprehensively under uniaxial compression testing. The results demonstrate a change in the compressive modulus (0.09 to 0.47 GPa), compressive strength (2.98 to 13.89 MPa), and specific energy absorption (SEA) (0.14 MJ/m3/g to 0.58 MJ/m3/g) due to the influence of CF incorporation, cell type and size, and RD. Results indicate that the Diamond structure outperformed both Primitive and Gyroid structures in terms of compressive modulus and strength, and SEA. All the CF-based TPMS structures showed a higher compressive modulus. Compressive strength and energy absorption capacity were both slightly enhanced in most PLA + CF-based Diamond structures. On the contrary, Gyroid and Primitive structures showed better performance for pure PLA-based structures in terms of compression strength and specific absorption energy.

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Purpose Electron beam melting (EBM) is one of the potential additive manufacturing technologies to fabricate aero-engine components from gamma titanium aluminide (γ-TiAl) alloys. When a new material system has to be taken in to the fold of EBM, which is a highly complex process, it is essential to understand the effect of process parameters on the final quality of parts. This paper aims to understand the effect of melting parameters on top surface quality and density of EBM manufactured parts. This investigation would accelerate EBM process development for newer alloys. Design/methodology/approach Central composite design approach was used to design the experiments. In total, 50 specimens were built in EBM with different melt theme settings. The parameters varied were surface temperature, beam current, beam focus offset, line offset and beam speed. Density and surface roughness were selected as responses in the qualifying step of the parts. After identifying the parameters which were statistically significant, possible reasons were analyzed from the perspective of the EBM process. Findings The internal porosity and surface roughness were correlated to the process settings. Important ones among the parameters are beam focus offset, line offset and beam speed. By jointly deciding the total amount of energy input for each layer, these three parameters played a critical role in internal flaw generation and surface evolution. Research limitations/implications The range selected for each parameter is applicable, in particular, to γ-TiAl alloy. For any other alloy, the settings range has to be suitably adapted depending on physical properties such as melting point, thermal conductivity and thermal expansion co-efficient. Practical implications This paper demonstrates how melt theme parameters have to be understood in the EBM process. By adopting a similar strategy, an optimum window of settings that give best consolidation of powder and better surface characteristics can be identified whenever a new material is being investigated for EBM. This work gives researchers insights into EBM process and speeds up EBM adoption by aerospace industry to produce critical engine parts from γ-TiAl alloy. Originality/value This work is one of the first attempts to systematically carry out a number of experiments and to evaluate the effect of melt parameters for producing γ-TiAl parts by the EBM process. Its conclusions would be of value to additive manufacturing researchers working on γ-TiAl by EBM process.