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Flame-retardant plastics are used in critical applications, such as aircraft interior parts, when the occurrence of fire can lead to serious injury to people. However, there is a lack of related publications. The purpose of this study is to present experimental data regarding geometrical analysis, such as dimensional accuracy and surface roughness, tensile strength and elongation of parts manufactured with flame-retardant materials by additive manufacturing.

Two additive manufacturing processes, selective laser sintering (SLS) and fused deposition modeling (FDM), were selected to manufacture the parts to be evaluated. Each process used its respective polymer, that is polyamide with flame-retardant additive (PA) for SLS and polyphenylsulfone (PPSF) for FDM. The samples consist of tensile specimens and representative parts of different products. Tensile tests were performed using standard tensile test machines, and geometrical analyses were performed using coordinate measuring machine as well as surface roughness tester.

As each material can be, in commercial machines, produced by only one process, the material selection for final products has to consider the manufacturing process as well. In general, although the FDM/PPSF process provided specimens with the highest ultimate strength, because of its strong influence by the building direction, FDM/PPSF also provided the lowest strength. SLS/PA was able to provide average strength with less dependency on the build-up direction. The geometrical analysis showed that SLS/PA presents a much smoother surface, but FDM/PPSF presented slightly better dimensional accuracy.

There is still lack of publications on polymers with flame resistance or flame-retardant polymers. Thus, this paper brings new technical information about processing such materials.

The use of rapid prototyping (RP) technologies is becoming increasingly popular due to the reduction of machinery prices. Consequently, more and more industries now have the opportunity to apply such processes to improve their product development cycles. The purpose of this paper is to present different decision‐making approaches to choose an adequate RP process.

Here, four decision approaches are applied to compare six processes regarding six criteria, using the input data from previous works. As a result, six decision methods are compared. Two different scenarios are constructed, where different important attributes are considered, simulating two different prototype applications.

It is demonstrated that not all methods result in the same RP ranking, however, most of them provide the same first option for a given scenario. The characteristics of the methods could be related to their influence on the evaluation, which serve as guidelines for the decision makers in order to reflect their exact opinion or requirements.

Owing to different ways of inputting information into the decision methods, some considerations are made in order to convert as close as possible the RP process attributes and scenario requirements into useful data for each method. In particular, the conversion of scenarios, i.e. the relative importance of the criteria, is somewhat challenging.

Although the fundamentals of the decision methods are presented here, one should be careful while comparing the RP process, because their attributes may vary enormously depending on the parameter process to build a part. Despite all the considerations and precautions to be observed, the selection of the RP process can be done in a simple way, dispensing with complex calculations.

This paper aims to argue about the involvement of additive technologies (ATs) in the prototyping issues of designing. More precisely, it reviews the literature contributions focused on the different perspectives of prototyping activities for design purposes, searching for both available knowledge and research needs concerning the correct exploitation of ATs.

A two-step literature review has been performed. In the first step, general information has been retrieved about prototyping issues related to design. In the second step, the literature searches were focused on retrieving more detailed information about ATs, concerning each of the main issues identified in the previous step. Extracted information has been analyzed and discussed for understanding the actual coverage of the arguments and for identifying possible research needs.

Four generally valid prototyping issues have been identified in the first step of the literature review. For each of them, available information and current lacks have been identified and discussed about the involvement of AT, allowing to extract six different research hints for future works.

This is the first literature review concerning AT-focused contributions that cover the complex and inter-disciplinary issues characterizing prototyping activities in design contexts.

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.

The main objective of this study is to determine the factors that have the greatest impact on travelers' opinions of airports.

11,656 customer reviews for 649 airports around the world were gathered following the COVID-19 outbreak from the website that rates airport quality. The dataset was examined using hierarchical regression, PLS-SEM, and the unsupervised Bayesian algorithm-based PSEM in order to verify the hypothesis.

The results showed that people’s intentions to recommend airports are significantly influenced by their opinions of how well the servicescape, staff, and services are.

By encouraging air travelers to have positive intentions toward recommending the airports, this research offers airport managers decision-support implications for how to improve airport service quality. This will increase the likelihood of retaining more passengers.

This study also suggests a quick-to-implement visual decision-making mechanism based on PSEM that is simple to understand.

This study aims to investigate the effects of consumers’ motivations on behavioral intention to use self-service technology (SST) in airline services exploring multimediating effects of flow experience and SST evaluation in Stimulus-Organism-Response model.

An online survey was conducted with quota sampling based on age group who had experiences of SSTs usage at the Incheon International Airport in South Korea. A total of 286 responses were used for the data analysis with structural equation modeling to examine the proposed model and the multimediating effects.

The results showed that consumers’ intrinsic and extrinsic motivations had positive impacts on their flow experience, SST evaluation and behavioral intention to use airline SSTs. Their flow experience had a positive influence on SST evaluation, and their SST evaluation influenced behavioral intention to use airline SSTs. Consumers’ flow experience and SST evaluation mediated the relationship between intrinsic and extrinsic motivations and behavioral intention to use airline SSTs.

It is important for customers to perceive extrinsic motivation such as speed, convenience and efficiency for the smooth process of airline SSTs at the airport. SST evaluation plays a key role to increase customers’ behavioral intention to use airline SSTs.

This study extends the understanding of consumers’ intrinsic and extrinsic motivations, flow experience, SST evaluation and behavioral intentions to use SST in airline services by building on a model. Especially, findings of the (multi)mediating effects of customers’ perceived flow and SST evaluation on the relationship between motivations and behavioral intention to use airline SSTs might provide better guidelines for managers to incorporate SSTs, to increase operational efficiency and to boost customer experiences.