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Purpose This paper reviews the synergy of Industry 4.0 and additive manufacturing (AM) and discusses the integration of data-driven manufacturing systems and product service systems as a key component of the Industry 4.0 revolution. This paper aims to highlight the potential effects of Industry 4.0 on AM via tools such as digitalisation, data transfer, tagging technology, information in Industry 4.0 and intelligent features. Design/methodology/approach In successive phases of industrialisation, there has been a rise in the use of, and dependence on, data in manufacturing. In this review of Industry 4.0 and AM, the five pillars of success that could see the Internet of Things (IoT), artificial intelligence, robotics and materials science enabling new levels of interactivity and interdependence between suppliers, producers and users are discussed. The unique effects of AM capabilities, in particular mass customisation and light-weighting, combined with the integration of data and IoT in Industry 4.0, are studied for their potential to support higher efficiencies, greater utility and more ecologically friendly production. This research also illustrates how the digitalisation of manufacturing for Industry 4.0, through the use of IoT and AM, enables new business models and production practices. Findings The discussion illustrates the potential of combining IoT and AM to provide an escape from the constraints and limitations of conventional mass production whilst achieving economic and ecological savings. It should also be noted that this extends to the agile design and fabrication of increasingly complex parts enabled by simulations of complex production processes and operating systems. This paper also discusses the relationship between Industry 4.0 and AM with respect to improving the quality and robustness of product outcomes, based on real-time data/feedback. Originality/value This research shows how a combined approach to research into IoT and AM can create a step change in practice that alters the production and supply paradigm, potentially reducing the ecological impact of industrial systems and product life cycle. This paper demonstrates how the integration of Industry 4.0 and AM could reshape the future of manufacturing and discusses the challenges involved.

The purpose of this work is to identify the principle of electron beam powder bed fusion (EB-PBF) and the performance of this AM method in the processing of copper components. This review details the experimentally reported properties, including microstructural, mechanical and physical properties of pure copper made by EB-PBF. The technical challenges and opportunities of EB-PBF are identified to provide insight into the influence of process parameters on observed mechanical properties as well as a roadmap for strategic research opportunities in this field. These insights allow optimisation of EB-PBF parameters, as well as comparison of the relative merits of EB-PBF over LB-PBF in the processing of copper components. This review details the microstructure and mechanical properties of EB-PBF of copper and identifies the technical opportunities and challenges. In addition, this report characterises the influence of process parameters, and subsequent energy density, on the associated mechanical properties. The discussions showed that the chance of pollution in copper processing by EB-PBF is less than laser-based powder bed fusion (LB-PBF) due to the high vacuum environment for electron beam. Oxygen content in the EB-PBF of copper powder is a vital factor and significantly affects the mechanical properties and quality of the specimen including physical density. The produced Cu2O due to the existence of oxygen content (in powder and bulk material) can improve the mechanical properties. However, if the Cu2O exceeds a certain percentage (0.0235%wt), cracks appear and negatively affect the mechanical properties. In copper printing by this method, the process parameters have to be tuned in such a way as to generate low build temperatures due to the high thermal conductivity of this alloy and the high sintering tendency of the powder.

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One problematic task in the laser-based powder bed fusion (LB-PBF) process is the estimation of meltpool depth, which is a function of the process parameters and thermophysical properties of the materials. In this research, the effective factors that drive the meltpool depth such as optical penetration depth, angle of incidence, the ratio of laser power to scan speed, surface properties and plasma formation are discussed. The model is useful to estimate the meltpool depth for various manufacturing conditions. A proposed methodology is based on the simulation of a set of process parameters to obtain the variation of meltpool depth and temperature, followed by validation with reference to experimental test data. Numerical simulation of the LB-PBF process was performed using the computational scientific tool “Flow3D Version 11.2” to obtain the meltpool features. The simulation data was then developed into a predictive analytical model for meltpool depth and temperature based on the thermophysical powder properties and associated parameters. The novelty and contribution of this research are characterising the fundamental governing factors on meltpool depth and developing an analytical model based on process parameters and powder properties. The predictor model helps to accurately estimate the meltpool depth which is important and has to be sufficient to effectively fuse the powder to the build plate or the previously solidified layers ensuring proper bonding quality. Results showed that the developed analytical model has a high accuracy to predict the meltpool depth. The model is useful to rapidly estimate the optimal process window before setting up the manufacturing tasks and can therefore save on lead-time and cost. This methodology is generally applied to Inconel 718 processing and is generalisable for any powder of interest. The discussions identified how the effective physical factors govern the induced heat versus meltpool depth which can affect the bonding and the quality of LB-PBF components.