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Manufacturer specifications for the resolution of an additive manufacturing (AM) machine can be ten times smaller (more optimistic) than the actual size of manufacturable features. Existing methods used to establish a manufacturable design rule-set are conservative piecewise-constant approximations. This paper aims to evaluate the effectiveness of a first-order model for producing improved design rule-sets for feature manufacturability, accounting for process variation.

A framework is presented which uses an interpolation method and a statistical model to estimate the minimum size for a wide range of features from a set of iterative experiments.

For an SLS process, using this approach improves the accuracy and reliability of minimum feature size estimates for a wider variety of features than assessed by most existing test artifacts.

More research is needed to provide better interpolation models, broaden applicability and account for additional geometric and process parameters which significantly impact the results. This research focuses on manufacturability and does not address dimensional accuracy of the features produced.

An application to the design of thin channels in a prosthetic hand shows the utility of the results in a real-world scenario.

This study is among the first to investigate statistical variation of “pass/fail” features in AM process characterization, propose a means of estimating minimum feature sizes for shapes not directly tested and incorporate a more efficient iterative experimental protocol.

This purpose of this paper is to provide an overview of the steps and processes behind successfully adapting novel materials, namely virgin glass and recycled glass, to three‐dimensional printing (3DP).

The transition from 3DP ceramic systems to glass systems will be examined in detail, including the necessary modifications to binder systems and printing parameters. The authors present preliminary engineering data on shrinkage, porosity, and density as functions of peak firing temperature, and provide a brief introduction to the complexities faced in realizing an adequate and repeatable firing method for 3D printed glass.

Shrinkage behavior for the 3D printed recycled glass showed significant anisotropy, especially beyond peak firing temperatures of 730°C. The average shrinkage ratios for the slow‐ and fast‐axes to the Z‐axis were 1:1.37 and 1:2.74, respectively. These extreme differences can be attributed to the layer‐by‐layer production method and binder burn‐off. At 760°C, the apparent porosity reached a minimum of 0.36 percent, indicative of asymptotic behavior that approaches a fully dense 3DP glass specimen. At low firing temperatures, the bulk density was similar to water, but increased to a maximum of 2.41 g/cm³. This indicates that 3DP recycled glass can behave similarly to common glass with accepted published bulk densities ranging from 2.4‐2.8 g/cm³.

Heating schedule analysis and optimization may reduce geometric variations, therefore, the firing method should be investigated in greater depth.

This paper provides a guide to successfully adopting glass to commercially available 3DP hardware. This research has also enabled rapid prototyping of recycled glass, a monumental step towards a sustainable future for 3DP.

The purpose of this paper is to explore the improvements in speed and precision achievable using straightforward closed-loop control for the gantry motion in additive manufacturing machines. The authors designed and built an economically viable demonstration system to quantify the performance improvement.

The authors develop and evaluate a low-cost closed-loop controller for the X and Y axes of an entry-level three-dimensional (3D) printer. The system developed captures and compensates for the dynamics of the motor and the belt-driven stage and detects mechanical errors, such as skipped motor steps.

The system produces path-following precision improvements of 40 and 75 per cent for two different sample trajectories. Correcting for skipped steps increases reliability and allows for more aggressive tuning of motion parameters; time savings of up to 25 per cent are seen by doubling acceleration rate.

The system presented provides an appropriate platform for further investigation into more complex, application-specific controllers and inclusion of more details of the printer dynamics that could produce still greater improvements in speed and accuracy.

The performance, low cost (40 USD/axis) and applicability to the majority of sub-2000USD 3D printer designs make this work of practical significance.

The CNC machining industry has for many years used similar approaches, but application to 3D printers has not been explored in the literature. This paper demonstrates the value of even a simple controller applicable to almost any 3D printer, while maintaining cost-effectiveness of the solution in a competitive market.

This paper aims to explore and demonstrate the ability to integrate entry-level additive manufacturing (AM) techniques with responsive polymers capable of mechanical to chemical energy transduction. This integration signifies the merger of AM and smart materials.

Custom filaments were synthesized comprising covalently incorporated spiropyran moieties. The mechanical activation and chemical response of the spiropyran-containing filaments were demonstrated in materials that were produced via fused filament fabrication techniques.

Custom filaments were successfully produced and printed with complete preservation of the mechanochemical reactivity of the spiropyran units. These smart materials were demonstrated in two key constructs: a center-cracked test specimen and a mechanochromic force sensor. The mechanochromic nature of the filament enables (semi)quantitative assessment of peak loads based on color change, without requiring any external analytical techniques.

This paper describes the first examples of three-dimensional-printed mechanophores, which may be of significant interest to the AM community. The ability to control the chemical response to external mechanical forces, in combination with AM to process the bulk materials, potentiates customizability at the molecular and macroscopic length scales.

This paper aims to provide a holistic view of infiltration behaviour by organised crime groups (OCGs), with a specific focus on the methods used to access the legal market, including factors that drive an organised crime group to pursue infiltration. The act of infiltration is examined as a business decision; therefore, factors such as the surrounding community, the availability of criminal opportunities and broader implications, are considered.

Initially, the concept of an organised crime group is explored by, where possible, identifying trends in behaviour and structure. The act of infiltration is dissected, including the infiltration behaviour of OCGs and their related decision-making processes.

Infiltration actions are complex; therefore, any countervailing combatting and preventative actions will need to follow suit. OCGs pursue infiltration only when deemed feasible and to their benefit in furthering their illicit actions. Criminal opportunities are pursued across the entire economic sector. When these groups participate in a legal market, their criminality infects the healthy market and leaves it ill and contagious to the rest of the licit economy.

Infiltration is organic, as it indicates growth or adjustment to changing market conditions. Criminal opportunities are widespread, and their creation is often unintentional–the legal economy casts a shadow. Combatting organised crime, entrenched in the lawful community, requires that the focus should be on the susceptibility of potential infiltration targets through the possible infiltration methods. Furthermore, a broader perspective is needed when considering the underlying motivation for infiltration–it may not only be to generate profit.

This study seeks to address the challenge of repatriate turnover by focusing on how effective repatriation adjustment, job satisfaction, and organizational commitment are at predicting the Taiwanese repatriates' intentions to leave their organization. By building on the cross‐cultural adjustment and turnover theories and researches, this study expands these recent findings to Taiwanese repatriates.

Multiple regression was used to predict intent to leave and explain the impact of the three predictors on intent to leave. Correlation was used to compare the relationship of study variables.

The results of multiple regression indicated that repatriation adjustment was the strongest predictor of intent to leave followed by organizational commitment. The combination of the three variables can predict approximately 58 percent of the variance of intent to leave. Overall interrelations among the independent variables showed a positive strong relationship and negatively related to intent to leave the organization.

The results provide empirical evidence that repatriation adjustment, job satisfaction, and organizational commitment are negatively related to intent to leave the organization. Furthermore, the conceptual framework of this study can be a guide to future research in repatriates' turnover intention.

The results of this study may help multinational organizations in Taiwan to enhance the international assignment process of their employees and keep valuable human capital within the organization.