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The purpose of this study is to investigate the thermoforming process of 3D-printed parts made from polylactic acid (PLA) and explore its application in producing wrist-hand orthoses. These orthoses were 3D printed flat, heated and molded to fit the patient’s hand. The advantages of such an approach include reduced production time and cost.

The study used both experimental and numerical methods to analyze the thermoforming process of PLA parts. Thermal and mechanical characteristics were determined at different temperatures and infill densities. An equivalent material model that considers infill within a print is proposed. Its practical use was proven using a coupled finite-element analysis model. The simulation strategy enabled a comparative analysis of the thermoforming behavior of orthoses with two designs by considering the combined impact of natural convection cooling and imposed structural loads.

The experimental results indicated that at 27°C and 35°C, the tensile specimens exhibited brittle failure irrespective of the infill density, whereas ductile behavior was observed at 45°C, 50°C and 55°C. The thermal conductivity of the material was found to be linearly related to the temperature of the specimen. Orthoses with circular open pockets required more time to complete the thermoforming process than those with hexagonal pockets. Hexagonal cutouts have a lower peak stress owing to the reduced reaction forces, resulting in a smoother thermoforming process.

This study contributes to the existing literature by specifically focusing on the thermoforming process of 3D-printed parts made from PLA. Experimental tests were conducted to gather thermal and mechanical data on specimens with two infill densities, and a finite-element model was developed to address the thermoforming process. These findings were applied to a comparative analysis of 3D-printed thermoformed wrist-hand orthoses that included open pockets with different designs, demonstrating the practical implications of this study’s outcomes.

This paper aims to fill a research gap by presenting design and 3D printing guidelines and considerations which apply to the development process of patient-specific osteotomy guides for orthopaedic surgery.

Analysis of specific constraints related to patient-specific surgical guides design and 3D printing, lessons learned during the development process of osteotomy guides for orthopaedic surgery, literature review of recent studies in the field and data gathered from questioning a group of surgeons for capturing their preferences in terms of surgical guides design corresponding to precise functionality (materializing cutting trajectories, ensuring unique positioning and stable fixation during surgery), were all used to extract design recommendations.

General design rules for patient-specific osteotomy guides were inferred from examining each step of the design process applied in several case studies in relation to how these guides should be designed to fulfill medical and manufacturing (fused deposition modelling process) constraints. Literature was also investigated for finding other information than the simple reference that the surgical guide is modelled as negative of the bone. It was noticed that literature is focussed more on presenting and discussing medical issues and on assessing surgical outcomes, but hardly at all on guides’ design and design for additive manufacturing aspects. Moreover, surgeons’ opinion was investigated to collect data on different design aspects, as well as interest and willingness to use such 3D-printed surgical guides in training and surgery.

The study contains useful rules and recommendations for engineers involved in designing and 3D printing patient-specific osteotomy guides.

A synergetic approach to identify general rules and recommendations for the patient-specific surgical guides design is presented. Specific constraints are identified and analysed using three case studies of wrist, femur and foot osteotomies. Recent literature is reviewed and surgeons’ opinion is investigated.

The paper aims to present the processing pipeline of an assembly immersive simulation application which can manage the interaction between the virtual scene and user using stereoscopic display and haptic devices. A new set of elements are integrated in a Collaborative Virtual Environment (CVE) and validated using an approach based on subjective and objective users’ performance criteria. The developed application is intended for Assembly/Disassembly (A/D) analysis, planning and training.

A mobility module based on contact information is used to handle the assembly components’ movements through real-time management of collision detection and kinematically constraint guidance. Information on CVE architecture, modules and application configuration process are presented. Impact of device type (3 degrees of freedom (DoFs) vs 6 DoFs) over user’s experience is evaluated. Parameters (number of assembled components and components assembly time) are measured for each user and each haptic device, and results are compared and discussed.

Test results proved the efficiency of using a mobility module based on predefined kinematic constraints for reducing the complexity of collision detection algorithms in real-time assembly haptic simulations. Also, experiments showed that, generally, users performed better with 3 DoFs haptic device compared to 6 DoFs haptic equipment.

The proposed immersive application automates the kinematical joints inference from 3D computer-aided design (CAD) assembly models and integrates it within a haptic-based virtual environment, for increasing the efficiency of A/D process simulations.

This paper aims to propose a new solution for producing customized three-dimensional (3D)-printed flat-shaped splints, which are then thermoformed to fit the patient’s hand. The splint design process is automated and is available to clinicians through an online application.

Patient anthropometric data measured by clinicians are associated with variables of parametric 3D splint models. Once these variables are input by clinicians in the online app, customized stereo lithography (STL) files for both splint and half mold, in the case of the bi-material splint, are automatically generated and become available for download. Bi-materials splints are produced by a hybrid manufacturing process involving 3D printing and overmolding.

This approach eliminates the need for 3D CAD-proficient clinicians, allows fast generation of customized splints, generates two-dimensional (2D) drawings of splints for verifying shape and dimensions before 3D printing and generates the STL files. Automation reduces splint design time and cost, while manufacturing time is diminished by 3D printing the splint in a flat position.

The app could be used in clinical practice. It meets the demands of mass customization using 3D printing in a field where individualization is mandatory. The solution is scalable – it can be extended to other splint designs or to other limbs. 3D-printed tailored splints can offer improved wearing comfort and aesthetic appearance, while maintaining hand immobilization, allowing visually controlled follow-up for edema and rapidly observing the need for revision if necessary.

An online application was developed for uploading patient measurements and downloading 2D drawings and STL files of customized splints. Different models of splints can be designed and included in the database as alternative variants. A method for producing bi-materials flat splints combining soft and rigid polymers represents another novelty of the research.

The mechanical performances of 3D-printed parts are influenced by the manufacturing variables. Many studies experimentally evaluate the impact of the process parameters on specimens’ static and dynamic behavior with the aim of tailoring the mechanical response of the prints. However, this experimental approach is hampered by the very large number of parameters, 3D printers and materials, the development of computer simulation models being thus required. In the context, this study aims to fill a gap by experimentally investigating the influence of infill related parameters over the vibrations of 3D-printed specimens, as well as to propose and validate a parametric finite element (FE) model for the prediction of eigenfrequencies.

A generally applicable FE model is not yet available for the 3D printing technology based on the material extrusion process due to the large number of parameters settings that determine a large variability of outcomes. Hence, the idea of developing numerical simulation models that address sets of parameters and assess their impact on a certain mechanical property. For the natural frequency, the influence of the infill density and infill line width is studied in this paper. An FE script that automates the generation of the model geometry by using the considered set of parameters is developed and run. The results of the modal analysis are compared to the experimental values for validating the script.

Based on the experimental results, a linear regression between the weight of the part and the first natural frequency is established. The response surfaces indicate that the infill density is the most significant parameter of influence. The weight-frequency function is then used for the prediction of the natural frequency of specimens manufactured with other infill parameters and values, including different infill patterns.

As the malfunctions or mechanical damages can be caused by the resonant vibration of parts during use, this research develops a FE-parameterized model that evaluates and predicts the eigenfrequencies of 2D printed parts to prevent these undesirable events. The targeted functional applications are those in which 3D-printed polymer parts are used, such as drone arms or drone propellers.

This research studies the influence of process parameters on the natural frequency of 3D-printed polylactic acid specimens, a topic scarcely addressed in literature. It also proposes a new approach for the development of parameterized FE models for sets of parameters, instead of a general model, to reduce the time and resources allocated to the experimental tests. Such a model is provided in this paper for evaluating the influence of infill parameters on 3D prints eigenfrequency. The numerical model is validated for other infill settings.

Porosity is a commonly analyzed defect in the laser-based additive manufacturing processes owing to the enormous thermal gradient caused by repeated melting and solidification. Currently, the porosity estimation is limited to powder bed fusion. The porosity estimation needs to be explored in the laser melting deposition (LMD) process, particularly analytical models that provide cost- and time-effective solutions compared to finite element analysis. For this purpose, this study aims to formulate two mathematical models for deposited layer dimensions and corresponding porosity in the LMD process.

In this study, analytical models have been proposed. Initially, deposited layer dimensions, including layer height, width and depth, were calculated based on the operating parameters. These outputs were introduced in the second model to estimate the part porosity. The models were validated with experimental data for Ti6Al4V depositions on Ti6Al4V substrate. A calibration curve (CC) was also developed for Ti6Al4V material and characterized using X-ray computed tomography. The models were also validated with the experimental results adopted from literature. The validated models were linked with the deep neural network (DNN) for its training and testing using a total of 6,703 computations with 1,500 iterations. Here, laser power, laser scanning speed and powder feeding rate were selected inputs, whereas porosity was set as an output.

The computations indicate that owing to the simultaneous inclusion of powder particulates, the powder elements use a substantial percentage of the laser beam energy for their melting, resulting in laser beam energy attenuation and reducing thermal value at the substrate. The primary operating parameters are directly correlated with the number of layers and total height in CC. Through X-ray computed tomography analyses, the number of layers showed a straightforward correlation with mean sphericity, while a converse relation was identified with the number, mean volume and mean diameter of pores. DNN and analytical models showed 2%–3% and 7%–9% mean absolute deviations, respectively, compared to the experimental results.

This research provides a unique solution for LMD porosity estimation by linking the developed analytical computational models with artificial neural networking. The presented framework predicts the porosity in the LMD-ed parts efficiently.

This study aims to present a model for detecting and predicting creative accounting in companies listed on the Tehran Stock Exchange (TSE).

The authors conduct this research in three stages. First, the authors review the literature to determine the dimensions, components, indicators and techniques of creative accounting. Second, the authors conduct semi-structured interviews with experts using the fuzzy Delphi technique to obtain screening and reach a consensus. Finally, the authors develop a model to predict creative accounting by classifying the financial statements of the sample companies into two groups based on the use or non-use of creative accounting techniques, measuring the indicators determined in the previous stage, running various machine learning algorithms and choosing the superior algorithm.

The results indicate the usefulness of accounting information for detecting and predicting creative accounting and the relevance of several financial attributes as important predictors. The results also indicate the superiority of extremely randomized trees over other algorithms in predicting creative accounting and suggest that the primary purpose of creative accounting in Iran is earnings management. Contrary to the political cost hypothesis, large Iranian companies use creative accounting to inflate profits.

The present research also has several limitations that must be considered, and caution must be exercised in interpreting and generalizing the findings as specified in the revised manuscript.

This study’s implications are significant for policymakers, standard-setters and practitioners. By recognizing the detrimental effects of creative accounting on financial transparency within companies, policymakers can address existing gaps in accounting standards to minimize the potential for earnings manipulation. Consequently, strengthening internal and external mechanisms related to a firm’s financial performance becomes achievable. The study provides evidence of the need for audit firms to recognize the importance of creative accounting and consider creative accounting in their audit plans to prevent insufficient or even misleading disclosure by companies that extensively use creative accounting practices in their financial reporting. Moreover, knowledge of creative accounting techniques can help auditors assess audit and detection risks and serve as a valuable guide for reducing audit costs and improving audit quality.

Given that creative accounting practices distort the true or real accounting results, curbing creative accounting practices reduces corporate failures and could lead to the reduction of job losses and other social consequences.

This study uses a unique database in Iran to determine a model for predicting creative accounting using a mixed-method methodology, qualitative and quantitative, to identify creative accounting techniques and run various machine learning algorithms.

From the 1990s to the present, decision-makers around the world have sought to identify the most appropriate legal framework to support the energy transition. This research aims to analyze the institutional dynamics of renewable energy promotion, focusing on regulatory aspects at the European and national level and emphasizing the case of Romania through several comparative approaches. In the context of the conflict in Ukraine, we focused on the issue of coal, which was reconsidered given the dependence of some European countries on this resource. The main research methods used in this study are comparative analysis and analysis of chronological information in a historical context, with correlations being made. The study was structured in three stages, the first from the 1990s until the European Energy Union formation, the second during the COVID-19 pandemic, and the third from the emergence of the conflict in Ukraine, which determined the recalibration of previously adopted measures. Starting from the hypotheses formulated and considering the regulatory scenario conducive to the transfer of public funds to achieve climate neutrality, the results of the study show the fact that, at this stage of the research, the states of the European continent are determined to fight for zero carbon by 2050. One result we found interesting is that almost a year after the outbreak of the conflict in Ukraine, less than a quarter of European states have moved past their assumed deadline for phasing out coal in the national mix.

The paper aims to investigate the standpoints and practices of university members from European developing countries regarding the harnessing of the intellectual capital (IC) within online academic social networks.

A questionnaire-based survey with 210 university members was conducted, with the indicators adopting prior measurement scales which were further adapted to a network framework.

The organizational policies and practices relate positively and highly significantly with the valuation of the network-based IC components. Moreover, 63 per cent of the professional and organizational competitiveness of higher education institutions is determined by the exploitation of the IC embedded in online academic networks.

All survey respondents were from the European developing countries, which may limit the general applicability of the findings. Also, the emphasis is laid solely on online academic networks.

This paper brings to the fore both the potential and the state-of-the-art in leveraging the IC of online specialized networks which are indicative of the academic field. When acknowledged as such, the network-based IC is liable to generate substantial competitive advantages at the professional and organizational levels at the same time.

This research adds to the extant literature in two main ways. First, it advances a new construct – network-based IC – in the context of the online academic social networks. Second, it proposes a research model for addressing the network-based IC from a competitive advantage perspective.