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The Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In just a short period, it has garnered some considerable strengths. Based on the 1987–2021 data collected from the Web of Science (WoS), the current study reports the advancement of the GST.

Research papers utilizing the GST in the fields of economics and education were retrieved from the Web of Science (WoS) platform using a set of predetermined keywords. In the final stage of the process, the papers that underwent analysis were manually chosen, with selection criteria based on the information presented in the titles and abstracts.

The study identifies prominent authors, institutions, publications and journals closely associated with the subject. In terms of authors, two major clusters are identified around Liu SF and Wang ZX, while the institution with the highest number of publications is Nanjing University of Aeronautics and Astronautics. Moreover, significant keywords, trends and research directions have been extracted and analyzed. Additionally, the study highlights the regions where the theory holds substantial influence.

The study is subject to certain limitations stemming from factors such as the language employed in the chosen literature, the papers included within the Web of Science (WoS) database, the designation of works categorized as “articles” in the database, the specific selection of keywords and keyword combinations, and the meticulous manual process employed for paper selection. While the manual selection process itself is not inherently limiting, it demands a greater investment of time and meticulous attention, contributing to the overall limitations of the study.

The significance of the study extends not only to scholars and practitioners but also to readers who observe the development of emerging scientific disciplines.

The analysis of trends revealed a growing emphasis on the application of GST in diverse domains, including supply chain management, manufacturing and economic development. Notably, the emergence of COVID-19 as a new research focal point among GST scholars is evident. The heightened interest in COVID-19 can be attributed to its global impact across various academic disciplines. However, it is improbable that this interest will persist in the long term, as the pandemic is gradually brought under control.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

Military and unmanned aerial vehicles (UAV) applications like rocket motor casings, missile covers and ship hulls use components that are made of maraging steel. Maraging steel has properties that are superior to other metals, making it more suitable for the fabrication of such components. A grey relational analysis (GRA) that is based on the Taguchi method has been utilised in the current study to optimise a laser beam welding (LBW) process. Further aspects such as GRA's optimum ranges and percentage contributions were also estimated.

A Taguchi L16 orthogonal array is utilised to design and conduct the experiments. Laser power (LP), welding speed (WS) and focal position (FP) are the three parameters are chosen for the process of welding. The output responses are the upper width of the heat-affected zone (HAZup), the upper width of the fusion zone (FZup) and the depth of penetration (DOP). The effect of the above key parameters on the responses was examined using an analysis of variance (ANOVA).

The results of ANOVA reveal that the parameter that has the most influence on the overall grey relational grade (GRG) is the FP. Finally, metallographic characterisation and a microstructural analysis are conducted on the weld bead geometry to demarcate the zone of HAZ and fusion zone (FZ).

As the most important criteria for LBW of maraging steels is the provision of higher DOP, higher FZ width and lower heat-affected zone, the study intended to prove the applicability of GRA technique in solving multi-objective optimisation problems in applications like defence and unmanned systems.

This study aims to investigate the micro mechanism of macro rheological characteristics for composite modified asphalt.Grey relational analysis (GRA) was used to analyze the correlation between macro rheological indexes and micro infrared spectroscopy indexes.

First, a dynamic shear rheometer and a bending beam rheometer were used to obtain the evaluation indexes of high- and low-temperature rheological characteristics for asphalt (virgin, SBS/styrene butadiene rubber [SBR], SBS/rubber and SBR/rubber) respectively, and its variation rules were analyzed. Subsequently, the infrared spectroscopy test was used to obtain the micro rheological characteristics of asphalt, which were qualitatively and quantitatively analyzed, and its variation rules were analyzed. Finally, with the help of GRA, the macro-micro evaluation indexes were correlated, and the improvement efficiency of composite modifiers on asphalt was explored from rheological characteristics.

It was found that the deformation resistance and aging resistance of SBS/rubber composite modified asphalt are relatively good, and the modification effect of composite modifier and virgin asphalt is realized through physical combination, and the rheological characteristics change with the accumulation of functional groups. The correlation between macro rutting factor and micro functional group index is high, and the relationship between macro Burgers model parameters and micro functional group index is also close.

Results reveal the basic principle of inherent-improved synergistic effect for composite modifiers on asphalt and provide a theoretical basis for improving the composite modified asphalt.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

Currently, China’s manufacturing industry chain still faces the danger of chain breakage due to the persistent “lack of technology” issue. The definition and detection of key nodes in the industry chain are significant to the enhancement of the stability of the industry chain. Therefore, detecting the key nodes in the manufacturing industry chain is necessary.

A complex network based on the links amongst listed manufacturing enterprises is built, and the authors analyse the network’s basic characteristics and vulnerability, taking into account the impact of scientific and technological innovation on the stability of the industry chain.

It is found that the high structural characteristic of midstream nodes in the naval architecture and marine engineering equipment industry chain determines their importance to stability, and the key status of upstream nodes is reflected in the weakness of technological innovation. The upstream nodes should focus on improving their independent innovation and R&D capability, whilst the midstream nodes should maintain a close supply–demand cooperation relationship.

The key node detection model for industry chain stability is constructed by considering various factors from the perspective of network and technological innovation. Empirical study is conducted to verify effectiveness of proposed method.

Over the last two decades, green supply chain management (GSCM) has enabled businesses to operate in an environmentally friendly manner. The present review examines 234 research articles and proposes a methodical literature review on GSCM, focusing on the aspects of sustainable development.

The work examines conceptual, analytical, empirical and non-empirical research articles, analyzing at all levels of the organization, such as firm, dyad, supply chain and network. The objective of the review is to provide insights into the state and scope of existing research in the domain of GSCM, to identify the prevalence of GSCM and to consolidate the trend of future research. The literature review follows a systematic methodology for analyzing the literature.

The findings can support researchers in identifying research areas with significant impact and streamline research on GSCM in the future. Practitioners can utilize this structured classification to strategize their green initiatives in their firms.

The work contributes to providing literature that explores a detailed review in GSCM. The proposed literature review captures critical aspects in the domain of GSCM and offers future research directions.

This research work has developed an integrated fuzzy Delphi and neutrosophic best–worst framework for selecting the sustailient (sustainable and resilient) supplier for an additive manufacturing (AM)-enabled industry.

An integrated fuzzy Delphi method (FDM) and neutrosophic best–worst method (N-BWM) approach is developed. 34 supplier evaluation criteria falling under 4 groups, that is, traditional, sustainable, resilient, and AM specific, are identified and validated using the FDM. Afterward, the weights of each criterion are measured by N-BWM. Later on, the performance evaluation is carried out to determine the best-suited supplier. Finally, sensitivity analysis is performed to know the stability and robustness of the proposed framework.

The outcome indicates the high performance of the suggested decision-making framework. The analysis reveals that supplier 4 (S4) is selected as the most appropriate for a given firm based on the FDM and N-BWM method.

The applicability of this framework is demonstrated through an industrial case of a 3D-printed trinket manufacturer. The proposed research helps AM decision-makers better understand resiliency, sustainability, and AM-related attributes. With this, the practitioners working in AM business can prioritize the supplier selection criteria.

This is the primitive study to undertake the most critical aspect of supplier selection for AM-enabled firms. Apart from this, an integrated FDM-N-BWM framework is a novel contribution to the literature on supplier selection.

Natural disasters cause serious operational risks and disruptions, which further impact the food supply in and around the disaster-impacted area. Resilient functions in the supply chain are required to absorb the impact of resultant disruptions in perishable food supply chains (FSC). The present study identifies specific resilient functions to overcome the problems created by natural disasters in the FSC context.

The quality function deployment (QFD) method is utilized for identifying these relations. Further, fuzzy term sets and the analytical hierarchy process (AHP) are used to prioritize the identified problems. The results obtained are employed to construct a QFD matrix with the solutions, followed by the technique for order of preference by similarity to the ideal solution (TOPSIS) on the house of quality (HOQ) matrix between the identified problems and functions.

The results from the study reflect that the shortage of employees in affected areas is the major problem caused by a natural disaster, followed by the food movement problem. The results from the analysis matrix conclude that information sharing should be kept at the highest priority by policymakers to build and increase resilient functions and sustainable crisis management in a perishable FSC network.

The study suggests practical implications for managing a FSC crisis during a natural disaster. The unique contribution of this research lies in finding the correlation and importance ranking among different resilience functions, which is crucial for managing a FSC crisis during a natural disaster.

There is a strong consensus among scholars that the international competitiveness of companies strongly depends on the support of institutions, which reduces uncertainty in transactions by giving form to economic interactions, while less attention was paid to the role of international standards within this context. This study intends to propose its contribution by deepening the role of process certifications in the competitiveness and internationalization strategies of companies, with specific reference to the wood-furniture sector.

Data were collected using a questionnaire survey distributed via computer-assisted web interviewing (CAWI) methodology and sent to a sample of 2,845 Italian companies which operate in the wood-furniture industry, using simple random sampling. Thanks to the survey administration, 228 companies participated to the survey.

The study shows that it is companies operating in international markets that define this tool as relevant; this underlines how certification is seen as a kind of business card for entering international markets. In this context, the role of business leadership emerges as fundamental in the practical definition of the objectives to be set by adopting a quality management systems and in the subsequent commitment to obtain them.

Up to now, the literature has taken these elements into analysis mainly considering the consumers' perspective. In sectors with a higher content of innovation, technology and design, such as the wood-furniture sector, the literature appears to be poor in terms of contributions.