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The COVID-19 pandemic significantly increased demand for medical and protective equipment by frontline health workers, as well as the general community, causing the supply chain to stretch beyond capacity, an issue further heightened by geographical and political lockdowns. Various 3D printing technologies were quickly utilised by businesses, institutions and individuals to manufacture a range of products on-demand, close to where they were needed. This study gathered data about 91 3D printed projects initiated prior to April 1, 2020, as the virus spread globally. It found that 60% of products were for personal protective equipment, of which 62% were 3D printed face shields. Fused filament fabrication was the most common 3D print technology used, and websites were the most popular means of centralising project information. The project data provides objective, quantitative insight balanced with qualitative critical review of the broad trends, opportunities and challenges that could be used by governments, health and medical bodies, manufacturing organisations and the 3D printing community to streamline the current response, as well as plan for future crises using a distributed, flexible manufacturing approach.

In response to shortages in personal protective equipment (PPE) during the COVID-19 pandemic, makers, community groups and manufacturers around the world utilised 3D printing to fabricate items, including face shields and face masks for healthcare workers and the broader community. In reaction to both local and global needs, numerous designs emerged and were shared online. In this paper, 37 face shields and 31 face masks suitable for fused filament fabrication were analysed from a fabrication perspective, documenting factors such as filament use, time to print and geometric qualities. 3D print times for similar designs varied by several hours, meaning some designs could be produced in higher volumes. Overall, the results show that face shields were approximately twice as fast to 3D print compared to face masks and used approximately half as much filament. Additionally, a face shield typically required 1.5 parts to be 3D printed, whereas face masks required five 3D printed parts. However, by quantifying the print times, filament use, 3D printing costs, part dimensions, number of parts and total volume of each design, the wide variations within each product category could be tracked and evaluated. This data and objective analysis will help makers, manufacturers, regulatory bodies and researchers consolidate the 3D printing response to COVID-19 and optimise the ongoing strategy to combat supply chain shortages now and in future healthcare crises.

The purpose of this paper is to analyze the business models that 3D printer manufacturers apply to commercialize their technologies. The authors investigate these business models and analyze whether there are business model patterns. The paper describes the gestalt of the business model patterns and discusses differences and similarities.

The authors review the literatures on business models and 3D printing technology. The authors apply a componential business model approach and carry out an in-depth analysis of the business models of 48 3D printer manufacturers in Europe and North America. The authors develop a framework focusing on value proposition, value creation and value capture components. Cluster analysis is used to identify business model patterns.

The results indicate that there are two distinct business model patterns in the industry. The authors termed these patterns the “low-cost online business model” and the “technology expert business model.” The results demonstrate that there is a relationship between business model and technology. The identified patterns are independent of age, company size and country of origin.

The empirical results complement and extend existing literature on business models. The authors contribute to the discussion on business models in the context of novel technology. The technology seems to influence the gestalt of the business model. The sample is limited to European and North American companies and the analysis is based on secondary data.

This is the first empirical study on the business models of 3D printer manufacturers. The authors apply an original mixed-methods approach and develop a framework that can function as a starting point for future research. 3D printer manufacturers can use the identified business model patterns as blueprints to reduce the risk of failure or as a starting point for business model innovation.

Present for more than 20 years, 3D food printing (3DFP) technology has not experienced the same widespread adoption as its non-food counterparts. It is believed that relevant business models are crucial for its expansion. The purpose of this study is to identify the dominant prototypical business models and patterns in the 3DFP industry. The knowledge gained could be used to provide directions for business model innovation in this industry.

The authors established a business model framework and used it to analyse the identified 3DFP manufacturers. The authors qualitatively identified the market’s prototypical business models and used agglomerative hierarchical clustering to extract further patterns.

All identified 3DFP businesses use the prototypical business model of selling ownership of physical assets, with some variations. Low-cost 3D food printers for private usage and dedicated 3D food printers for small-scale food producers are the two primary patterns identified. Furthermore, several benefits of 3DFP technology are not being used, and the identified manufacturers are barely present in high-revenue markets, which prevents them from driving technological innovation forward.

The extracted patterns can be used by the companies within the 3DFP industry and even in other additive manufacturing segments to reflect upon, refine or renew their business model. Some directions for business model innovation in this industry are provided.

To the best of the authors’ knowledge, this is the first quantitative study to give an account of the current 3DFP business models and their possible evolution. This study also contributes to the business model patterns methodological development.

This paper aims to print 3D structures from polymers that resist bacterial attachment by reactive jetting of acrylate monomers.

The first step towards printing was ink development. Inks were characterised to carry out an estimation of their potential printability using the Z parameter to predict stable jetting conditions. Printability conditions were optimised for each ink using a Dimatix DMP-2800, which enabled 3D structures to be fabricated.

UV photo-initiated polymers, which resist bacterial attachment, were found to be printable using piezo-based inkjet printers. The waveform required for each ink depends on the value of the Z parameter. Once the waveform and the printability parameters were optimised, 3D objects were fabricated.

This methodology has been confirmed as an effective method to 3D print materials that have been demonstrated to be bacteria resistant. However, ink curing depends on modification of some parameters (such as photoinitiator concentration or UV exposure time) which would result in an improvement of the curing process post jetting.

The combination of inkjet based 3D printing with new materials resistant to bacterial attachment means the possibility of building customised medical devices with a high level of complexity and bespoke features can be fully realised. The scope and variability of the devices produced will exceed what can be achieved using standard fabrication methodologies and can be applied to reduce the incidence of device associated infections and to address increased morbidity, mortality and health care costs associated with nosocomial infections.

In this paper, the novel use of materials that resist bacterial attachment has been described to build 3D structures using material jetting. Its value lies on the potential impact this methodology could produce in the biomedical device and research fields.

This paper is devoted to prepare micro-cone structure with variable cross-section size by Stereo Lithography Appearance (SLA)-based 3D additive manufacturing technology. It is mainly focused on analyzing the forming mechanism of equipment and factors affecting the forming quality and accuracy, investigating the influence of forming process parameters on the printing quality and optimization of the printing quality. This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.

The µ-SLA process is optimized based on the variable cross-section micro-cone structure printing. Multi-index analysis method was used to analyze the influence of process parameters. The process parameter influencing order is determined and validated with flawless micro array structure.

After the optimization analysis of the top diameter size, the bottom diameter size and the overall height, the influence order of the printing process parameters on the quality of the micro-cone forming is: exposure time (B), print layer thickness (A) and number of vibrations (C). The optimal scheme is A1B3C1, that is, the layer thickness of 5 µm, the exposure time of 3000 ms and the vibration of 64x. At this time, the cone structure with the bottom diameter of 50 µm and the cone angle of 5° could obtain a better surface structure.

This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.

The purpose of this paper was to assess and determine the impact of the five core technologies of Industry 4.0 (3D Printing, Big Data Analytics, Cloud Computing, Internet of Things (IoT) and Robotics) on the organizational performance of the retail industry in the context of Pakistan.

Pakistan's retail industry was chosen as the target sector, and the target population was composed of senior-level employees, including managers from first-level positions to top-level positions, as well as subordinate employees working under the supervision of first-level managers, possessing the technological know-how of Industry 4.0. The data were collected through a matrix-based survey questionnaire that was based on a five-point Likert scale, ranging from “strongly agree” to “strongly disagree.” The process of data analysis was conducted using IBM SPSS Statistics.

The findings obtained by this research work showed a significant relationship among the five core pillars of Industry 4.0 and the organizational performance of Pakistan's retail industry. Besides, the obtained findings provided preliminary evidence that Industry 4.0's disruptive technologies, particularly, 3D printing, big data analytics, cloud computing, IoT and robotics, could help Pakistan's retail industry solve various problems and challenges, such as meager revenues, increased expenses and unorganized systems.

The present study extended the theoretical body of knowledge through studying and examining Industry 4.0's five crucial factors that significantly contribute to the service sector, particularly, the retail industry, of the big emerging markets (BEM) economies, including Pakistan.

The purpose of this study is to cover the influence of selected printing parameters at a macro and micro-geometrical level, focusing on the dimensions, geometry and surface of printed parts with short carbon fibers reinforced PLA. For this case study, a hollow cylindrical shape is considered, aiming to cover the gap detected in previous works analyzed.

Nowadays, additive manufacturing plays a very important role in the manufacturing industry, as can be seen through its numerous research and applications that can be found. Within the engineering industry, geometrical tolerances are essential for the functionality of the parts and their assembly, but the variability in three-dimensional (3D) printing makes dimensional control a difficult task. Constant development in 3D printing allows, more and more, printed parts with controlled and narrowed geometrical deviations and tolerances. So, it is essential to continue narrowing the studies to achieve the optimal printed parts, optimizing the manufacturing process as well.

Results present the relation between the selected printing parameters and the resulting printed part, showing the main deviations and the eligible values to achieve a better tolerance control. Also, from these results obtained, we present a parametric model that relates the geometrical deviations considered in this study with the printing parameters. It can provide an overview of the piece before printing it and so, adjusting the printing parameters and reducing time and number of printings to achieve a good part.

The main contribution is the study of the geometry selected under a 3D printing process, which is important because it considers parts that are created to fit together and need to comply with the required tolerances. Also, we consider that the parametric model can be a suitable approach to selecting the optimal printing parameters before printing.

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

This study aims to provide a comprehensive overview of the current state of the art in powder bed fusion (PBF) techniques for additive manufacturing of multiple materials. It reviews the emerging technologies in PBF multimaterial printing and summarizes the latest simulation approaches for modeling them. The topic of “multimaterial PBF techniques” is still very new, undeveloped, and of interest to academia and industry on many levels.

This is a review paper. The study approach was to carefully search for and investigate notable works and peer-reviewed publications concerning multimaterial three-dimensional printing using PBF techniques. The current methodologies, as well as their advantages and disadvantages, are cross-compared through a systematic review.

The results show that the development of multimaterial PBF techniques is still in its infancy as many fundamental “research” questions have yet to be addressed before production. Experimentation has many limitations and is costly; therefore, modeling and simulation can be very helpful and is, of course, possible; however, it is heavily dependent on the material data and computational power, so it needs further development in future studies.

This work investigates the multimaterial PBF techniques and discusses the novel printing methods with practical examples. Our literature survey revealed that the number of accounts on the predictive modeling of stresses and optimizing laser scan strategies in multimaterial PBF is low with a (very) limited range of applications. To facilitate future developments in this direction, the key information of the simulation efforts and the state-of-the-art computational models of multimaterial PBF are provided.