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Fused Filament Fabrication (FFF) is an extrusion-based manufacturing process using fused thermoplastics. Despite its low cost, the FFF is not extensively used in high-value industrial sectors mainly due to parts' anisotropy (related to the deposition strategy) and residual stresses (caused by successive heating cycles). Thus, this study aims to investigate the process improvement and the optimization of the printed parts.

In this work, a meshless technique – the Radial Point Interpolation Method (RPIM) – is used to numerically simulate the viscoplastic extrusion process – the initial phase of the FFF. Unlike the FEM, in meshless methods, there is no pre-established relationship between the nodes so the nodal mesh will not face mesh distortions and the discretization can easily be modified by adding or removing nodes from the initial nodal mesh. The accuracy of the obtained results highlights the importance of using meshless techniques in this field.

Meshless methods show particular relevance in this topic since the nodes can be distributed to match the layer-by-layer growing condition of the printing process.

Using the flow formulation combined with the heat transfer formulation presented here for the first time within an in-house RPIM code, an algorithm is proposed, implemented and validated for benchmark examples.

The purpose of this paper is to apply the concept of equivalent initial flaw size (EIFS) to the anisotropic nickel-based single crystal (SX) material, and to predict the fatigue life on this basis. The crack propagation law of SX material at different temperatures and the weak correlation of EIFS values verification under different loading conditions are also investigated.

A three-parameter time to crack initial (TTCI) method with multiple reference crack lengths under different loading conditions is established, which include the TTCI backstepping method and EIFS fitting method. Subsequently, the optimized EIFS distribution is obtained based on the random crack propagation rate and maximum likelihood estimation of median fatigue life. Then, an effective driving force based on anisotropic and mixed crack propagation mode is proposed to describe the crack propagation rate in the small crack stage. Finally, the fatigue life of three different temperature ESE(T) standard specimens is predicted based on the EIFS values under different survival rates.

The optimized EIFS distribution based on EIFS fitting - maximum likelihood estimation (MLE) method has the highest accuracy in predicting the total fatigue life, with the range of EIFS values being about [0.0028, 0.0875] (mm), and the mean value of EIFS being 0.0506 mm. The error between the predicted fatigue life based on the crack propagation rate and EIFS distribution for survival rates ranges from 5% to 95% and the experimental life is within two times dispersion band.

This paper systematically proposes a new anisotropic material EIFS prediction method, establishing a framework for predicting the fatigue life of SX material at different temperatures using fracture mechanics to avoid inaccurate anisotropic constitutive models and fatigue damage accumulation theory.

The goal of this work is to create a computational finite element model to perform thermoelastic stress analysis (TSA) with the usage of a non-ideal load frequency, containing the effects of the material thermal properties.

Throughout this document, the methodology of the model is presented first, followed by the procedure and results. The last part is reserved to results, discussion and conclusions.

This work had the main goal to create a model to perform TSA with the usage of non-ideal loading frequencies, considering the materials’ thermal properties. Loading frequencies out of the ideal range were applied and the model showed capable of good results. The created model reproduced acceptably the TSA, with the desired conditions.

This work creates a model to perform TSA with the usage of non-ideal loading frequencies, considering the materials’ thermal properties.

The majority of machine component failures are caused by load conditions that change with time. Under those circumstances, the component can function effectively for a long time but then breaks down unexpectedly and without warning. Therefore, the study of fatigue considerations in design becomes important. Also, to determine the component's long-term tenability, fatigue behavior must be investigated. This paper aims to investigate the fatigue life of aluminum 6061-T6 alloy under uniaxial loading using experiments and finite element simulation.

Both base metal (BM) and friction stir welding (FSW) configurations have been used to analyze fatigue behavior. The experimental tests were carried out using Instron-8801 hydraulic fatigue testing machine at frequency of 20 Hz and load ratio of 0.1. The yield strength, ultimate tensile strength, amplitude stress and fatigue life were used as input in simulation analysis software. Based on the findings of the tensile test, the maximum stress applied during the fatigue testing was estimated. Simulated and experimental results were also used to plot and validate the S-N curves. The fracture behavior of specimens was also examined using fractographic analysis.

The fractured surfaces indicate both brittle and ductile failure in the specimens. However, dimples dominated during the final fracture. The comparison between experimental and simulation results illustrates that the difference in fatigue cycles increases with an increase in the yield strength of both BM and FSWed specimens. This disparity is attributed to many factors such as scratches, rough surfaces and microstructural behavior. Aluminum 6061-T6 alloy is considered a noteworthy material where high strength with reduced weight contributes to the crash-worthy design of automobile structures.

The current study is significant in the prediction of the fatigue life of aluminum 6061-T6 alloy using experiments and simulation analysis. A good correlation was found when the experimental and simulation analysis were compared. The proposed simulation analysis approach can be used to anticipate a component's fatigue life.

This study aims to synthesize pigment and resin from agro-wastes and use them in the formulation of eco-friendly surface coatings.

The pigments and resin were synthesized through a chemical modification of agro-wastes. The pigments were characterized by infrared spectroscopy (FTIR) and were screened for their antimicrobial activities. The physicochemical characteristics of the cashew nutshell liquid (CNSL)-modified resin were evaluated. These precursors and other natural additives were used to formulate surface coatings, and their drying and adhesive properties were evaluated using international testing methods.

It was observed that the curing of the CNSL-modified resin depended on time and temperature. The pigments exhibited antimicrobial activity against E. coli and S. aureus and had high melting points, affirming their stability. The chemically modified precursors successfully yielded surface coatings with acceptable drying times and adhesion to the base substrate.

The use of agro-wastes as the main components of the surface coatings implies waste valorization, a reduction in production costs and the creation of job opportunities for sustainable development. To increase the chemical, physical, corrosion resistance and antimicrobial qualities of paint compositions, chemically modified peanut skin extracts and CNSL can be used as pigments and resins, respectively. This could be a green approach to achieving the targets of Sustainable development goals 11 and 12.

The paper outlines a prospective approach to use unwanted waste (peanut skin, cashew nutshells) and other natural additives as industrial raw materials. These novel surface coating precursors are cost-effective, readily available, eco-friendly and could replace conventional precursors.

This paper aims to provide SIF calculation method for engineering application.

In this paper, the stress intensity factors (SIFs) calculation method is applied to the anisotropic Ni-based single crystal film cooling holes (FCHs) structure.

Based on contour integral, the anisotropic SIFs analysis finite element method (FEM) in Ni-based single crystal is proposed. The applicability and mesh independence of the method is assessed by comparing the calculated SIFs using mode of plate with an edge crack. Anisotropic SIFs can be calculated with excellent accuracy using the finite element contour integral approach. Then, the effect of crystal orientation and FCHs interference on the anisotropic SIFs is clarified. The SIFs of FCH edge crack in the [011] orientated Ni-based single crystal increases faster than the other two orientations. And the SIF of horizontal interference FCHs edge crack is also larger than that of the inclined interference one.

The SIFs of the FCH edge crack in the turbine air-cooled blade are innovatively computed using the sub-model method. Both the Mode I and II SIFs of FCHs edge crack in blade increase with crack growing.

This study aims to bring awareness to the developing of fault detection systems using the data collected from sensor devices/physical devices of various systems for predictive maintenance. Opportunities and challenges in developing anomaly detection algorithms for predictive maintenance and unexplored areas in this context are also discussed.

For conducting a systematic review on the state-of-the-art algorithms in fault detection for predictive maintenance, review papers from the years 2017–2021 available in the Scopus database were selected. A total of 93 papers were chosen. They are classified under electrical and electronics, civil and constructions, automobile, production and mechanical. In addition to this, the paper provides a detailed discussion of various fault-detection algorithms that can be categorised under supervised, semi-supervised, unsupervised learning and traditional statistical method along with an analysis of various forms of anomalies prevalent across different sectors of industry.

Based on the literature reviewed, seven propositions with a focus on the following areas are presented: need for a uniform framework while scaling the number of sensors; the need for identification of erroneous parameters; why there is a need for new algorithms based on unsupervised and semi-supervised learning; the importance of ensemble learning and data fusion algorithms; the necessity of automatic fault diagnostic systems; concerns about multiple fault detection; and cost-effective fault detection. These propositions shed light on the unsolved issues of predictive maintenance using fault detection algorithms. A novel architecture based on the methodologies and propositions gives more clarity for the reader to further explore in this area.

Papers for this study were selected from the Scopus database for predictive maintenance in the field of fault detection. Review papers published in this area deal only with methods used to detect anomalies, whereas this paper attempts to establish a link between different industrial domains and the methods used in each industry that uses fault detection for predictive maintenance.

This paper aims to investigate the performance of OECD countries' long-term productivity during the period of 1975–2018.

This study employed different approaches to evaluate how efficiency scores vary with changes in inputs and outputs: Data Envelopment Analysis (CRS, VRS and FDH), TOPSIS and TOPSIS of these scores.

The findings suggest that, during the period of this study, countries with higher freedom of religion and with Presidential democracy regimes are positively associated with higher productivity.

To the best of the authors’ knowledge, this is the first study that uses efficiency models to assess the productivity levels of OECD countries based on several contextual variables that can potentially affect it.

The decision to become international is a highlighted organisational decision that affects all dimensions at all firm levels. Human resources are also among the parts of the organisation affected by this decision. Paying attention to employees can speed up and facilitate this process. Organisational integrity is one of the most significant issues that must be considered. In this regard, identifying, investigating and planning to deal with the destructive effects that may influence the employees of small and medium-sized enterprise (SMEs) in internationalisation, are among the subjects that have so far received less attention and should be studied more. The present study explores the destructive influences of internationalisation on the employees of SMEs by a hybrid multi-layer decision-making model-psychological solution. First, by reviewing the literature, the destructive impacts of internationalisation on employees are extracted. In the next stage, these factors are screened according to the condition of the SMEs in an emerging economy by interval-valued intuitionistic hesitant fuzzy Delphi (IVIHF-Delphi). The impact of these factors on each other is then evaluated applying interval-valued intuitionistic hesitant fuzzy DEMATEL-based ANP (IVIHF-DANP). Consequently, the highlighted destructive impacts are determined and the psychological solutions to face them are provided.