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This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

This paper aims to propose a general framework of shared control for human–robot interaction.

Human dynamics are considered in analysis of the coupled human–robot system. Motion intentions of both human and robot are taken into account in the control objective of the robot. Reinforcement learning is developed to achieve the control objective subject to unknown dynamics of human and robot. The closed-loop system performance is discussed through a rigorous proof.

Simulations are conducted to demonstrate the learning capability of the proposed method and its feasibility in handling various situations.

Compared to existing works, the proposed framework combines motion intentions of both human and robot in a human–robot shared control system, without the requirement of the knowledge of human’s and robot’s dynamics.

This paper aims to analyze factors based on organizational knowledge management (KM; transactional memory systems and knowledge-oriented leadership [K-OL]) that help firms to mitigate conflicts based on task management at work, with the aim to improve their innovation capabilities (IC). The knowledge-based view of the firm, conflict management theory and cognitive collective engagement theory have been used to build a model of relationships that connects the development of positive KM contexts and management of dysfunctional conflict with IC improvement.

Data survey collected from inland hotel establishments in Spain is used to test seven hypotheses by means of structural equations modeling, applying the partial least squares technique. Direct, indirect and mediating relationships between variables are examined from the structural path model.

The results confirm that, as expected, IC improve when K-OL and transactive memory systems (TMSs) are properly implemented by hotel establishments, which leads them to reduce negative effects of task management conflict (TMC). Significant direct effects are found between the key variables of the study and also a significant indirect effect between K-OL and IC through TMS reinforcement and the mitigation of TMC.

This paper provides useful ideas for hotel managers about how to improve KM contexts in their establishments while avoiding TMC. Efforts devoted to creating those contexts by hotel establishments are shown to be effective to improve their IC and create competitive advantages.

The analysis of IC improvement by studying TMC mitigation had not been researched to date by the KM literature. The consideration and testing of a model that integrates KM-related tools such as K-OL and TMS to avoid TMC in the hotel industry is the main contribution of this study.

This paper seeks to develop a mid-range theory of how change recipient sensemaking processes affect the realization of strategic flexibility during simultaneous change in professional service firms.

The research presented is based on an exploratory embedded case study adopting a qualitative interpretive methodology, conducted at a professional service organization. A sensemaking lens was adopted in order to study organizational change processes. Data was collected through semi-structured open-ended in-depth interviews, and analyzed using first and second order analysis, inspired by the methodology used by Corley and Gioia (2004).

We identified four determinants of change recipient sensemaking: professional identification, dominant organizational discourse, equivocality of expectations, and cross-understanding between thought worlds. Case findings indicate that cognitive and affective dimensions of change recipient sensemaking are strongly interwoven in their effect on realizing strategic flexibility.

We contribute to the competence-based strategic management literature by introducing the concept of change recipient sensemaking in understanding the realization of strategic flexibility; by identifying four major determinants in a context of simultaneous change in a professional service organization; and by highlighting the interwoven and mutually reinforcing cognitive and affective dimensions of professional’s process of constructing meaning.

This study aims to explore how social networks could be used in the measurement of transactive memory systems (TMS) or other team constructs and provide motivation for future analyses of TMS measurement.

TMSs describe the structures and processes that teams use to share information, work together and accomplish shared goals. This paper proposes the use of social network analysis in measuring TMS. This is accomplished by describing the creation and administration of a TMS network instrument and evaluating the relation of the proposed network measures, previous measures of TMS and performance.

Findings include that proposed network measures perform similarly to previously proposed, frequently used measures of TMS.

To the best of the authors’ knowledge, this is among the first papers to propose network measures for the evaluation of TMS.

Tribology at The University of Aston in Birmingham grew out of the existing research interests of members of the Departments of Mechanical Engineering and Physics. The Tribo‐Engineering group lead by Dr. G. K. Lewis, deals mainly with hydro‐dynamic and hydrostatic lubrication problems, whilst the Tribo‐Physics groups, led by Dr. T. F. J. Quinn, deals mainly with the application of modern physical techniques to tribology.

As a kind of knowledge-intensive team coordinated across physical distance, it is necessary to construct a meta-knowledge driven transactive memory system (TMS) for the knowledge management of distributed agile team (DAT). This study aims to explore the comprehensive antecedents of TMS establishment in DATs and considers how TMS establishment is affected by herding behavior under the artificial intelligence (AI)-related knowledge work environment that emerges with technology penetration.

The data derived from 177 students of 52 DATs in a well-known Chinese business school, which were divided into 26 traditional knowledge work groups and 26 AI-related task groups to conduct a random comparative experiment. The ordinary least squares method was used to analyze the conceptual model and ANOVA was used to examine the differences in herding behavior between the control groups (traditional knowledge work DATs) and treatment groups (DATs engaged in AI-related knowledge work).

The results showed that knowledge diversity, professional knowledge, self-efficacy and social system use had significantly positive effects on the establishment of TMS. Interestingly, the authors also find that herding behavior may promote the process of establishing TMS of the new team, and this effect will be more significant when AI tasks are involved in team knowledge work.

By exploring the comprehensive antecedents of the establishment of TMS, this study provided a theoretical basis for knowledge management of DATs, especially in AI knowledge work teams. From a practical perspective, when the DAT is involved in AI-related knowledge works, managers should appropriately guide the convergence of employees’ behaviors and use the herding effects to accelerate the establishment of TMS, which will improve team knowledge sharing and innovation.

Social relationships play an important role in organizational entrepreneurship. They are crucial to entrepreneurs’ decisions because, despite the bleeding-edge technological advancements observed nowadays, entrepreneurs as human beings will always strive to be social. During the COVID-19 pandemic many companies moved activities into the virtual world and as a result offline Social relationships became rarer, but as it turns out, even more valuable, likewise, the inter-organizational cooperation enabling many companies to survive.

This chapter aims to develop knowledge about entrepreneurs’ SR and their links with inter-organizational cooperation. The results of an integrative systematic literature review show that the concept of Social relationships, although often investigated, lacks a clear definition, conceptualization, and operationalization. This chapter revealed a great diversity of definitions for Social relationships, including different scopes of meaning and levels of analysis. The authors identify 10 building blocks and nine sources of entrepreneurs’ Social relationships. The authors offer an original typology of Social relationships using 12 criteria. Interestingly, with regard to building blocks, besides those frequently considered such as trust, reciprocity and commitment, the authors also point to others more rarely and narrowly discussed, such as gratitude, satisfaction and affection. Similarly, the authors discuss the varied scope of sources, including workplace, family/friendship, past relationships, and ethnic or religious bonds. The findings of this study point to a variety of links between Social relationships and inter-organizational cooperation, including their positive and negative influences on one another. These links appear to be extremely dynamic, bi-directional and highly complex.

This study aims to optimize control strategies for multi-unmanned aerial vehicle (UAV) systems by integrating differential game theory with sliding mode control and neural networks. This approach addresses challenges in dynamic and uncertain environments, enhancing UAV system coordination, operational stability and precision under varying flight conditions.

The methodology combines sliding mode control, differential game theory and neural network algorithms to devise a robust control framework for multi-UAV systems. Using a nonsingular fast terminal sliding mode observer and Nash equilibrium concepts, the approach counters external disturbances and optimizes UAV interactions for complex task execution.

Simulations demonstrate the effectiveness of the proposed control strategy, showcasing enhanced stability and robustness in managing multi-UAV operations. The integration of neural networks successfully solves high-dimensional Hamilton–Jacobi–Bellman equations, validating the precision and adaptability of the control strategy under simulated external disturbances.

This research introduces a novel control framework for multi-UAV systems that uniquely combines differential game theory, sliding mode control and neural networks. The approach significantly enhances UAV coordination and operational stability in dynamic environments, providing a robust solution to high-dimensional control challenges. The use of neural networks to solve complex Hamilton–Jacobi–Bellman equations for real-time multi-UAV management represents a groundbreaking advancement in autonomous aerial vehicle research.

This paper aims to study the application of reinforcement learning (RL) in the control of an output-constrained flapping-wing micro aerial vehicle (FWMAV) with system uncertainty.

A six-degrees-of-freedom hummingbird model is used without consideration of the inertial effects of the wings. A RL algorithm based on actor–critic framework is applied, which consists of an actor network with unknown policy gradient and a critic network with unknown value function. Considering the good performance of neural network (NN) in fitting nonlinearity and its optimum characteristics, an actor–critic NN optimization algorithm is designed, in which the actor and critic NNs are used to generate a policy and approximate the cost functions, respectively. In addition, to ensure the safe and stable flight of the FWMAV, a barrier Lyapunov function is used to make the flight states constrained in predefined regions. Based on the Lyapunov stability theory, the stability of the system is analyzed, and finally, the feasibility of RL in the control of a FWMAV is verified through simulation.

The proposed RL control scheme works well in ensuring the trajectory tracking of the FWMAV in the presence of output constraint and system uncertainty.

A novel RL algorithm based on actor–critic framework is applied to the control of a FWMAV with system uncertainty. For the stable and safe flight of the FWMAV, the output constraint problem is considered and solved by barrier Lyapunov function-based control.