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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.

Additive manufacturing also known as 3D printing is an evolving advanced manufacturing technology critical for the new era of complex machinery and operating systems. Manufacturing systems are increasingly faced with risk of attacks not only by traditional malicious actors such as hackers and cyber-criminals but also by some competitors and organizations engaged in corporate espionage. This paper aims to elaborate a plausible risk practice of designing and demonstrate a case study for the compromised-based malicious for polymer 3D printing system.

This study assumes conditions when a machine was compromised and evaluates the effect of post compromised attack by studying its effects on tensile dog bone specimens as the printed object. The designed algorithm removed predetermined specific number of layers from the tensile samples. The samples were visually identical in terms of external physical dimensions even after removal of the layers. Samples were examined nondestructively for density. Additionally, destructive uniaxial tensile tests were carried out on the modified samples and compared to the unmodified sample as a control for various mechanical properties. It is worth noting that the current approach was adapted for illustrating the impact of cyber altercations on properties of additively produced parts in a quantitative manner. It concurrently pointed towards the vulnerabilities of advanced manufacturing systems and a need for designing robust mitigation/defense mechanism against the cyber altercations.

Density, Young’s modulus and maximum strength steadily decreased with an increase in the number of missing layers, whereas a no clear trend was observed in the case of % elongation. Post tensile test observations of the sample cross-sections confirmed the successful removal of the layers from the samples by the designed method. As a result, the current work presented a cyber-attack model and its quantitative implications on the mechanical properties of 3D printed objects.

To the best of the authors’ knowledge, this is the original work from the team. It is currently not under consideration for publication in any other avenue. The paper provides quantitative approach of realizing impact of cyber intrusions on deteriorated performance of additively manufactured products. It also enlists important intrusion mechanisms relevant to additive manufacturing.

Three-dimentional (3D) food printers are innovative technologies that contribute to healthy, personalized and stainable nutrition. However, many consumers are still vigilant about 3D printed food in the age of technology. The purpose of this study is to develop a scale and propose a model for consumption preferences associated with 3D-printed food (3DPF).

The developed questionnaire was handed to 192 Z and Y generation participants (Data1) for the exploratory factor analysis stage initially. Then, the questionnaire was handed to another group of 165 participants (Data 2) for verification by confirmatory factor analysis. Finally, the dimensions “healthy and personalized nutrition,” “sustainable nutrition” and “socio-cultural nutrition” were analyzed by structural equation modeling.

The results indicated that there was a high relationship between “healthy and personalized nutrition” and “sustainable nutrition” as well as between “sustainable nutrition” and “socio-cultural nutrition” when 3DPF was considered.

The study would contribute to the new survey area related to 3DPF by presenting a scale and proposing a model. Also, the study reveals which nutritional factors affect the Z and Y generation’s consumption of 3DPF. In this context, the study aims to make marketing contributions to the food production, restaurant and hotel sectors.

3D食品打印机是创新技术, 有助于健康、个性化和可持续的营养。然而, 在科技时代, 许多消费者仍然对3D打印食品保持警惕。本研究的目的是开发一个刻画与3D打印食品相关的消费偏好的量表并提出一个模型。

本研究首先将开发的问卷交给192名Z和Y世代参与者（数据1）进行探索性因素分析阶段。然后, 将问卷交给另一组165名参与者（数据2）通过验证性因素分析进行验证。最后, 通过结构方程模型分析了“健康和个性化营养”、“可持续营养”和“社会文化营养”这三个维度。

结果表明, 在考虑3D打印食品时, “健康和个性化营养”与“可持续营养”之间以及“可持续营养”与“社会文化营养”之间存在很高的关系。

本研究通过提出一个量表并提出一个模型, 为与3D打印食品相关的新调查领域做出了贡献。此外, 研究揭示了影响Z和Y世代对3D打印食品消费的营养因素。在这一背景下, 本研究旨在为食品生产、餐厅和酒店等领域做出营销贡献。

Increasingly 3D printing is used for parts of garments or for making whole garments due to their flexibility and comfort and for functionalizing or enhancing the aesthetics of the final garment and hence adding value. Many of these applications rely on complex programming of the 3D printer and are usually provided by the vendor company. This paper introduces a simpler, easier platform for designing 3D-printed textiles, garments and other artifacts, by predicting the optimal orientation of the target objects to minimize the use of plastic filaments.

The main idea is based on the shadow-casting analogy, which assumes that the volume of the support structure is similar to that of the shadow from virtual sunlight. The triangular elements of the target object are converted into 3D pixels with integer-based normal vectors and real-numbered coordinates via vertically sparse voxelization. The pixels are classified into several groups and their noise is suppressed using a specially designed noise-filtering algorithm called slot pairing. The final support structure volume information was rendered as a two-dimensional (2D) figure, similar to a medical X-ray image. Thus, the authors named their method modified support structure tomography.

The study algorithm showed an error range of no more than 1.6% with exact volumes and 6.8% with slicing software. Moreover, the calculation time is only several minutes for tens of thousands of mesh triangles. The algorithm was verified for several meshes, including the cone, sphere, Stanford bunny and human manikin.

Simple hardware, such as a CPU, embedded system, Arduino or Raspberry Pi, can be used. This requires much less computational resources compared with the conventional g-code generation. Also, the global and local support structure is represented both quantitatively and graphically via tomographs.

This study aims to apply an open-source approach to protect the 3D printing industry from innovation stagnation due to broad patenting of obvious materials.

To do this, first an open-source implementation of the first five conditions of an open-source algorithm developed to identify all obvious 3-D printing materials was implemented in Python, and the compound combinations of two and three constituents were tested on ten natural and synthetic compounds. The time complexity for combinations composed of two constituents and three constituents is determined to be O(n²) and O(n³), respectively.

Generating all combinations of materials available on the Chemical Abstracts Services (CAS) registry on the fastest processor on the market will require at least 73.9 h for the latter, but as the number of constituents increases the time needed becomes prohibitive (e.g. 3 constituents is 1.65 million years). To demonstrate how machine learning (ML) could help prioritize both theoretical as well as experimental efforts a three-part biomaterial consisting of water, agar and glycerin was used as a case study. A decision tree model is trained with the experimental data and is used to fill in missing physical properties, including Young's modulus and yield strength, with 84.9 and 85.1% accuracy, respectively.

The results are promising for an open-source system that can theoretically generate all possible combinations of materials for 3-D printing that can then be used to identify suitable printing material for specific business cases based on desired material properties.

This research investigates how the value creation interests and activities of different stakeholder groups within one open source software (OSS) project influence the project's development over time.

The authors conducted a case study of OpenSimulator using textual and thematic analyses of the initial four years of OpenSimulator developer mailing list to identify each stakeholder group and guide our analysis of their interests and value creation activities over time.

The analysis revealed that while each stakeholder group was active within the OSS project's development, the different groups possessed complementary interests that enabled the project to evolve. In the formative period, entrepreneurs were interested in the software's strategic direction in the market, academics and SMEs in software functionality and large firms and hobbyists in software testing. Each group retained its primary interest in the maturing period with academics and SMEs separating into server- and client-side usability. The analysis shed light on how the different stakeholder groups overcame tensions amongst themselves and took specific actions to sustain the project.

The authors extend stakeholder theory by reconceptualizing the focal organization and its stakeholders for OSS projects. To date, OSS research has primarily focused on examining one project relative to its marketplace. Using stakeholder theory, we identified stakeholder groups within a single OSS project to demonstrate their distinct interests and how these interests influence their value creation activities over time. Collectively, these interests enable the project's long-term development.

The study aims to develop an integrated model for three-dimensional (3D) printing adoption in the Gulf Cooperation Council (GCC) context to form a baseline for more theoretical and empirical debate from emerging markets.

A qualitative approach with a convenience sample is adopted since there is no formal body that has accurate data about the number of companies, governmental bodies, nongovernmental organizations, universities, labs, etc. that already have adopted 3D printing.

The results indicate that the technological usefulness of 3D printing and its ease-of-use factor were found to be lacking among community members and governmental officials. Yet, these factors were the most influential factor affecting the spread of 3D printing technology adoption in the GCC countries. Nevertheless, the adaptation of 3D printing is not yet at the level of its global markets, nor is it used within leading companies’ assembly lines. In addition, the 3D printing awareness and use increased during the COVID-19 pandemic. Yet, the adaptation rate is still below expectations due to several challenges that face the growth of the 3D printing market in the GCC countries. The most vital challenge facing 3D printing growth is manifested in governmental policies and regulations.

Companies’ managers can benefit from the current study results by focusing on the factors that facilitate 3D adoption and avoiding bottle-neck factors that hinder the speed of the 3D adoption. 3D providers can also benefit by understanding the factors that affect 3D adoption and designing their machine and marketing strategy in a way that helps the intended companies to easily adopt 3D printing.

To the best of the authors’ knowledge, this is the first study that explored 3D printing adoption on the GCC countries’ level. It also adds a new flavor to the literature by exploring 3D adoption during the COVID-19 crisis.