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This study aims to comparatively analyze the cut parts obtained as a result of cutting the Ni-based Inconel 625 alloy, which is widely used in the aerospace industry, with the wire electro-discharge machining (WEDM) and abrasive water jet machining (AWJM) methods in terms of macro- and microanalyses.

In this study, calipers, Mitutoyo SJ-210, Nikon SMZ 745 T, scanning electron microscope and energy dispersive X-ray were used to determine kerf, surface roughness and macro- and microanalyses.

Considering the applications in the turbine industry, it has been determined that the WEDM method is suitable to meet the standards for the machinability of Inconel 625 alloy. In contrast, the AWJM method does not meet the standards. Namely, while the kerf angle was formed because the hole entrance diameters of the holes obtained with AWJM were larger than the hole exit diameters, the equalization of the hole entry and exit dimensions, thanks to the perpendicularity and tension sensitivity of the wire electrode used in the holes drilled with WEDM ensured that the kerf angle was not formed.

It is known that the surface roughness of the parts used in the turbine industry is accepted at Ra = 0.8 µm. In this study, the average roughness value obtained from the successful drilling of Inconel 625 alloy with the WEDM method was 0.799 µm, and the kerf angle was obtained as zero. In the cuts made with the AWJM method, thermal effects such as debris, microcracks and melted materials were not observed; an average surface roughness of 2.293 µm and a kerf of 0.976° were obtained.

The current relationship between humans and nature is complex and tense. Overexploitation of natural resources, pollution, climate change and biodiversity loss present the main challenges for modern society. In particular, the issue of climate change is being intensely debated, and the interest in protecting natural resources by adopting sustainable practices is growing. Therefore, this chapter examines a brief history and concept of climate change, reviewing relevant theories and authors from Svante Arrhenius and Guy Stewart Callendar to Charles David Keeling and Mikhail Budyko. This chapter explores the first measurements and warnings regarding climate crisis and reviews international treaties and policy development at local, national and global levels. Furthermore, adverse consequences of the climate crisis are described, and ecologism, eco-imperialism and climate change denialism are explained.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.

First, the effect of magnetic field intensity and nano-ferrofluid concentrations on surface roughness was evaluated in magnetic minimum quantity lubrication (MMQL). Then, the effect of lubricant flow rate and nozzle position on surface roughness was investigated in MQL, MMQL, electrostatic MQL (EMQL) and electromagnetic MQL (EMMQL).

This study examined the performance of MQL under magnetic and electric fields in turning AISI 304 stainless steel in terms of surface roughness and compared the results with those obtained from wet cutting and MQL turning operations. To prepare the nano-ferrofluid used in different states of MQL, Fe₃O₄ nanoparticles were added to the base fluid.

The results showed that the surface roughness under the EMMQL technique decreased by 36% and 49.4% on average compared with wet and MQL techniques, respectively. The lubrication technique affected the surface roughness by 90.2%, whereas it was 8.3% for the lubricant flow rate. EMQL and EMMQL techniques had no significant difference in their effects on surface roughness. In the innovative MMQL technique, the nano-ferrofluid concentration of 6% and magnetic field intensity of 93 G resulted in lower surface roughness of the workpiece relative to other counterparts.

Examining previously published studies showed that using nano-ferrofluids under a magnetic field for cooling purposes in machining processes have less considered by researchers. This study applies an innovative method of lubrication under the concurrent effect of magnetic and electric fields, called EMMQL, to improve the efficiency of MQL in machining hard-to-cut materials. For comprehensively inspecting the newly presented method, the effects of several parameters, including the nano-ferrofluid concentration, magnetic field intensity, lubricant flow rate and position of lubricant spray nozzle, on the surface roughness of workpiece in turning of AISI 304 stainless steel are investigated.

The purpose of the research was to evaluate the relationship between income and the recycled materials used in order to rate the business related to circular repair services under the burden of economic development in the countries of the European Union.

The analytical processes explore data from 2010 to 2020. The countries were divided into clusters according to economic maturity (Human Development Index (HDI), real Gross domestic product (GDP) per capita). Subsequently, the relationships were evaluated through the income indicators (for the 13 population groups), and the circular materials use rate indicator. The three indicators decomposed into five specific metrics were employed. The commonly applied characteristics of the descriptive analysis, Pearson's correlation coefficient and the panel regression analysis were engaged in the investigation.

The results demonstrated the vast disparities between income and circular materials use. In the more economically developed countries, their levels were twice higher as the less-developed countries. However, there is a meaningful positive relationship between them. The greatest attention was paid to the panel regression analysis applied to the relationship between income and circular economy (CE) use. The results showed that in a majority of the cases (different income categories), there is a significant positive relationship. When comparing the outcomes of the regression models between the groups of the countries according to their economic development, a closer relationship was clearly demonstrated in the countries with a lower level of development (Bulgaria, Romania, Croatia, Hungary).

Besides the specific strengths, the study also shows some limitations identified mainly on the data side. The latest data on the consumption of circular materials come from 2020, so they do not cover the period related to the pandemic crisis. It is believed that there may have been some changes in income during the pandemic, and they may have harmed CE. Furthermore, there is to note that some limitations occur in the analytical process. The incompleteness of the data can also be included here as certain data is not available; hence, it was estimated directly by the Eurostat statistical authority.

At the same time, the following are currently considered among the primary barriers: financial restrictions, insufficient infrastructure, weak government support and obstacles on the global market. Consumers, industry leaders and the government are the most influential stakeholder groups in overcoming barriers. Higher demand for repair services will also initiate further development of business activities in this area at various regional levels. Progress in the repair services economy will continue to require extensive efforts in the future. Systematic coordination of activities at multiple levels of government together with manufacturers, designers, educational institutions, community institutions and individuals will be essential.

Socioeconomic characteristics such as sex, age and education represent crucial predictors of consumer behavior. Therefore, the authors would like to focus future research on analyzing these characteristics and examine all the conceptual frameworks of consumer behavior and its positioning in detail within CE and the strategies related to the repair service. Discussing this issue through follow-up research will allow for solving complex transformational and political tasks related to the repair service strategies within CE. It will also inspire the discussion frameworks and multidisciplinary solutions to this issue affecting the fields of human geography, sociological, ethnographic and political sciences.

In less-developed countries, wage change can have a more substantial impact on the development of the CE. Also, a closer relationship between business in the field of repair services with income and the use of circular materials was manifested in the same way.

This study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.

The research method used analytical statistical methods to propose a classification model. The project science research concepts were integrated with the statistical process monitoring (SPM) concepts using the modeling methods applied in the data science (DS) area. For the integration development, SPM Phases I and II were associated, generating models with a structured data analysis process, creating a continuous validation approach.

Validation was performed by simulation and analytical techniques applied to the Cohen’s Kappa index, supported by voluntary comparisons in the Matthews correlation coefficient (MCC) and the Youden index, generating prescriptive criteria for the classification. Kappa-based control charts performed well for m = 5 sample amounts and n = 500 sizes when Pe is less than 0.8. The simulations also showed that Kappa control requires fewer samples than the other indices studied.

The main contributions of this study to both theory and practitioners is summarized as follows: (1) it proposes DS and SPM integration; (2) it develops a tool for continuous predictive classification models validation; (3) it compares different indices for model quality, indicating their advantages and disadvantages; (4) it defines sampling criteria and procedure for SPM application considering the technique’s Phases I and II and (5) the validated approach serves as a basis for various analyses, enabling an objective comparison among all alternative designs.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

The objectives of this study are twofold: identify the main challenges in performing training on Industry 4.0 concepts to managers operating in the manufacturing sector who are not familiar with them but aspire for an Industry 4.0 broad view and validate training practices that can be adopted to reduce managerial knowledge differences.

A Delphi method was carried out in two rounds to identify the Industry 4.0 training challenges and a Fuzzy Delphi method was applied in one round to validate the training practices. Both methods used the same set of participants composed of experts in training for Industry 4.0. Results were discussed considering literature statements.

In total, 11 challenges in Industry 4.0 training were identified and grouped into: challenges associated with the necessary knowledge, challenges of breaking paradigm, challenges associated with training characteristics and challenges associated with expected results. In total, 11 training practices were directly validated, including actions to be adopted before, during, and after the training process.

The findings are relevant for professionals, academics, or consultants as the findings enable better training planning and execution. No similar papers were found in scientific databases, reinforcing this present study's originality and contribution.