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This study investigates how federated learning (FL) and human–robot collaboration (HRC) can be used to manage diverse industrial environments effectively. We aim to demonstrate how these technologies not only improve cooperation between humans and robots but also significantly enhance productivity and innovation within industrial settings. Our research proposes a new framework that integrates these advancements, paving the way for smarter and more efficient factories.

This paper looks into the difficulties of handling diverse industrial setups and explores how combining FL and HRC in the mark of Industry 5.0 paradigm could help. A literature review is conducted to explore the theoretical insights, methods and applications of these technologies that justify our proposal. Based on this, a conceptual framework is proposed that integrates these technologies to manage heterogeneous industrial environments.

The findings drawn from the literature review performed, demonstrate that personalized FL can empower robots to evolve into intelligent collaborators capable of seamlessly aligning their actions and responses with the intricacies of factory environments and the preferences of human workers. This enhanced adaptability results in more efficient, harmonious and context-sensitive collaborations, ultimately enhancing productivity and adaptability in industrial operations.

This research underscores the innovative potential of personalized FL in reshaping the HRC landscape for manage heterogeneous industrial environments, marking a transformative shift from traditional automation to intelligent collaboration. It lays the foundation for a future where human–robot interactions are not only more efficient but also more harmonious and contextually aware, offering significant value to the industrial sector.

Recent emerging information technologies like digital twin (DT) provide new concepts and transform information management processes in the architecture, engineering and construction (AEC) industry. Although numerous articles are pertinent to DT applications, existing research areas and potential future directions related to the state-of-the-art DT in project operation and maintenance (O&M) are yet to be studied. Therefore, this paper aims to review the state-of-the-art research on DT applications in project O&M.

The current review adopted four methodological steps, including literature search, literature selection, science mapping analysis and qualitative discussion to gain a deeper understanding of DT in project O&M. The impact and contribution of keywords and documents were examined from a total of 444 journal articles retrieved from the Scopus database.

Five mainstream research topics were identified, including (1) DT-based artificial intelligence technology for project O&M, (2) DT-enabled smart city and sustainability, (3) DT applications for project asset management, (4) Blockchain-integrated DT for project O&M and (5) DT for advanced project management. Subsequently, research gaps and future research directions were proposed.

This study intends to raise awareness of future research by summarizing the current DT development phases and their impact on DT implementation in project O&M among researchers and practitioners.

Liquid-assisted laser surface texturing technology was used to create composite microtextures on triangular guide rail surfaces to enhance their tribological properties.

Numerical simulations were used to investigate the impact of various microtextures on fluid dynamic lubrication. Reciprocating friction and wear tests, followed by mechanistic analysis, examined the combined tribological effects of microtextured surfaces and lubricants.

The numerical simulation outcomes reveal a significant augmentation in the influence of fluid dynamic pressure due to composite microtextures, consequently amplifying the load-bearing capacity of the oil film. The average friction coefficient of composite microtextured samples was approximately 0.136 in reciprocating pin-on-disk friction tests, representing approximately 17% decrease compared to polished samples. Triangular guide rails with composite microtextures demonstrated the lowest average coefficient under conditions of high-speed and heavy-loading in the reciprocating friction and wear tests. Additionally, the presence of composite microtextures was found to promote the formation of adsorbed and friction films during friction, potentially contributing to the enhancement of tribological properties.

Triangular guide rails face high friction and wear, limiting their stability in demanding applications like machine tool guideways. This paper proposes a novel approach for steel triangular guide rails, involving composite microtexturing, numerical fluid simulations, liquid-assisted laser surface texturing and friction-wear testing. By implementing composite microtextures, the method aims to reduce friction coefficients and extend guideway service life, thereby saving energy and reducing maintenance costs. Enhancing the antifriction and antiwear properties of machine tool guideways is crucial for improving performance and longevity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0183/

The set of 2,509 documents related to the human-centric aspect of manufacturing were retrieved from Scopus database and systmatically analyzed. Using an unsupervised machine learning approach based on Latent Dirichlet Allocation we were able to identify latent topics related to human-centric aspect of Industry 5.0.

This study aims to create a scientific map of the human-centric aspect of manufacturing and thus provide a systematic framework for further research development of Industry 5.0.

In this study a 140 unique research topics were identified, 19 of which had sufficient research impact and research interest so that we could mark them as the most significant. In addition to the most significant topics, this study contains a detailed analysis of their development and points out their connections.

Industry 5.0 has three pillars – human-centric, sustainable, and resilient. The sustainable and resilient aspect of manufacturing has been the subject of many studies in the past. The human-centric aspect of such a systematic description and deep analysis of latent topics is currently just passing through.

This research aims to develop and validate a framework for eradicating women’s discrimination in architectural design firms (ADFs) in Egypt and propose strategies for prospective adoption in the Gulf Cooperation Council (GCC) countries to increase the transformational impact of women on the architectural and urban developments of the Gulf region.

A combined qualitative and quantitative research approach was designed to accomplish four objectives. Firstly, to investigate the nature of business in ADFs, women’s discrimination and policies for gender equity (PGE) in architecture. Secondly, to analyse three case studies to validate the identified causes and impacts of women’s discrimination and examine the role of PGE towards eradicating women’s discrimination in ADFs. Thirdly, to conduct a survey questionnaire with a representative sample of ADFs to investigate their perception of women’s discrimination and the correlation between PGE towards eradicating women’s discrimination in ADFs. Based on the above, the research developed and validated a framework to eradicate women’s discrimination in ADFs in Egypt and suggested strategies for potential application in the GCC countries to increase the transformational role of women in the architectural and urban developments of the Gulf region.

Through literature review and case studies, the research identified and validated the causes and impacts of women’s discrimination as well as PGE in Architecture. The findings of data analysis showed that the highest-ranked causes of women discrimination in ADFs were “customs and beliefs” followed by “Underestimating women’s work” and “Recruiting males more than females”. Moreover, the highest-ranked impacts of women’s discrimination were “career shift and leaving the profession” followed by “decrease in creativity and innovation” and “decrease in economic growth”. Furthermore, the Spearman correlation test showed that while some PGE were correlated, others were not. These findings helped in the development of the proposed framework and proposed strategies.

This research presents a practical framework to eliminate women’s discrimination in ADFs in Egypt based on the findings of literature review, case studies and survey questionnaire. The framework explained in a workable way the objectives of the framework functions; activities; tools and techniques; involved personnel and needed resources as well as enforcing mechanisms. It was validated by a representative sample of ADFs in Egypt to ensure its practicability and viability and suggested strategies for implementation in the GCC countries to increase women’s role in architectural and urban development.

The research identified and validated the causes and impacts of women’s discrimination as well as PGE in Architecture. Moreover, the research investigated the perception of women’s discrimination and the correlation between PGE through conducting a survey questionnaire with a representative of ADFs in Egypt. The research tackled a topic that received scant attention in construction literature, especially in Egypt and the GCC countries. The research developed and validated a framework to eradicate women’s discrimination in ADFs in Egypt. It represents a synthesis that is novel and creative in thought and adds value to the knowledge in a manner that has not previously occurred. The research suggested several strategies for the prospective implementation of the framework in the GCC countries as an approach to enhancing the transformational role of women in the architectural and urban developments of the Gulf region.

This study combines different perspectives on herding, viewing it as a social network heuristic in comparison to other heuristics. The purpose is to use the heuristic view of herding as found in early literature and test it on grounds of efficiency and payoff, in essence, combining the heuristic and rational agent view of herding. The simulated double auction setting includes agents embedded in a social network, allowing for an examination of herding alongside rational behaviour and imperfect signals.

In each round of the simulation, levels of homophily, density and fractions of types of agents is set and agents are allowed to follow their respective heuristics under those conditions. Characteristics of the social network, such as the size, levels of different homophilies, density and fractions of different types of agents are varied randomly to gauge their effect on the performance of herders vis-à-vis others and the overall market efficiency through simulation based approach. The data used for the study has been developed in Python and linear models are estimated using R.

Herding decreases total surplus in private value double auctions, but herders are not worse off than other agents and perform equally in common value auctions. Further, herders and random offerers reduce payoffs of other agents as well, and herding effects the surplus per transaction and not the quantum.

This study explores herding as a strategic behaviour coexisting with rationality and other strategies in specific circumstances. It presents intriguing findings on the impact of herding on individual outcomes and market efficiency, raising new avenues for future research. Implication to research includes a dent on the “sieve” argument of markets rooting out irrationality and from it, a policy implication that follows is the need for corrective measures as markets cannot self-correct this, given herders do not perform worse than others.

The study links the phenomenon of herding to the dynamics of social networks and heuristic-based learning mechanisms that sets apart this research from the majority of existing literature, which predominantly conceptualizes herding as an outcome derived from a perfect Bayesian Equilibrium and a rational learning process.

This study was conducted to analyze the effects of machining parameters on the specific energy consumption in the computerized numerical control lathe turning operation of a hardened alloy steel roll at low cutting speeds. The aim was to minimize its consumption.

The design matrix was based on three variable factors at three levels. Response surface methodology was used for the analysis of experimental results. Optimization was carried out by using the desirability function and genetic algorithm. A multiple regression model was used for relationship build-up.

According to desirability function, genetic algorithm and multiple regression analysis, optimal machining parameters were cutting speed 40 m/min, feed 0.2 mm/rev and depth of cut 0.50 mm, which resulted in minimal specific energy consumption of 0.78, 0.772 and 0.78 kJ/mm³, respectively. Correlation analysis and multiple regression model found a quadratic relationship between specific energy consumption with power consumption and material removal rate.

In the past, many researchers have developed mathematical models for specific energy consumption, but these models were developed at high cutting speed, and a majority of the models were based on the material removal rate as the independent variable. This research work developed a mathematical model based on the machining parameters as an independent variable at low cutting speeds, for a new type of large-sized hardened alloy steel roll. A multiple regression model was developed to build a quadratic relationship of specific energy consumption with power consumption and material removal rate. This work has a practical application in hot rolling industry.

This research explores the relationships between financial awareness and investor satisfaction about retirement planning, particularly in the Indian context. We developed a conceptual model involving double moderation effects of post-retirement objectives and external factors influencing investor satisfaction.

A carefully crafted survey instrument was designed to collect data from the 480 employees working in six administrative departments in the northern part of India. After checking the measurement properties of the survey instrument through the Lisrel package of structural equation modeling, the hypotheses were tested using Hayes PROCESS macros.

The results indicate that financial awareness is positively related to (1) investor satisfaction and (2) investment purpose; investment purpose is positively related to investor satisfaction; post-retirement objectives moderate the relationship between financial awareness and investment purpose; external factors moderate the moderated relationship between financial awareness and post-retirement objectives (first moderator) and investor satisfaction mediated through investment purpose.

The outcomes of this study have important implications for the employees embarking on making decisions concerning their retirement. The conceptual model provides a simple framework explaining how financial awareness and investor satisfaction are affected by the post-retirement objectives of individuals. This study highlights the importance of considering the effect of external factors influencing financial decisions.

The three-way interactions in this exploratory research contribute to the growing literature on behavioral finance, particularly concerning retirement planning involving pension.

The purpose of this paper is to examine the mechanical characteristics and optimization of wear parameters of hybrid (TiO₂ + Y₂O₃) nanoparticles with Al matrix using squeeze casting technique.

The hybrid aluminium matrix nanocomposites (HAMNCs) were fabricated with varying concentrations of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃), from 2.5 to 10 Wt.% in 2.5 Wt.% increments. Dry sliding wear test variables were optimized using the Taguchi method.

The introduction of hybrid nanoparticles in the aluminium (Al) matrix was evenly distributed in contrast to the base matrix. HAMNC6 (5 Wt.% TiO₂ + 5 Wt.% Y₂O₃) reported the maximum enhancement in mechanical properties (tensile strength, flexural strength, impact strength and density) and decrease in porosity% and elongation% among other HAMNCs. The results showed that the optimal combination of parameters to achieve the lowest wear rate was A3B3C1, or 15 N load, 1.5 m/s sliding velocity and 200 m sliding distance. The sliding distance showed the greatest effect on the dry sliding wear rate of HAMNC6 followed by applied load and sliding velocity. The fractured surfaces of the tensile sample showed traces of cracking as well as substantial craters with fine dimples and the wear worn surfaces were caused by abrasion, cracks and delamination of HAMNC6.

Squeeze-cast Al-reinforced hybrid (TiO₂+Y₂O₃) nanoparticles have been investigated for their impact on mechanical properties and optimization of wear parameters.

The purpose of this study is to review the different facets associated with Industry 5.0 (I5.0) and propose a conceptual framework to boost the applicability of this novel technological cum social aspects within industrial organizations for improved organizational sustainability.

This research work adopted a bibliometric analysis that encapsulates a quantitative set of tools for bibliometric and bibliographic information. This study uses the database of Scopus to acquire data related to different facets of I5.0. The study implies a different spectrum of terms to reach the final corpus of 91 articles related to I5.0. Furthermore, a conceptual define, measure, analyze, improve and control (DMAIC)-based framework based on different literature findings is proposed and validated based on the input of experts from different parts of the world.

The results indicate that I5.0 is still in its infancy. The wider applicability of I5.0 demands comprehensive theoretical knowledge of different facets of this new paradigm and the development of a framework to adopt it on a larger scale. Organizations that are in the race to adopt I5.0 face major challenges related to the digitization of processes along with well-defined cyber-physical systems and the lack of a dedicated framework to execute I5.0. Furthermore, the result also suggests that manufacturing industries are more ready to adopt I5.0 practices as compared to service industries, which can be attributed to well-defined technological measures available in manufacturing settings.

To the best of the authors’ knowledge, this is one of the first studies that explore different know-how and challenges and provides a holistic view of I5.0 by providing a systematic adoption framework.