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Prior investigations concerning misalignment resulting from journal deformation typically relied on predefined misaligned angles. Nevertheless, scant attention has been devoted to the determination of these misaligned angles. Furthermore, existing studies commonly treat the journal as rigid under such circumstances. Therefore, the present study aims to introduce a framework for determining misaligned angles and to compare outcomes between rigid and flexible journal configurations.

The bearing forces are considered as an external load leading to journal deformation. This deformation is calculated using the finite element method. The pressure distribution producing the bearing force is solved using the finite difference method. The mesh grids in the finite element and finite difference methods are matched for coupling calculation. By iteration, the pressure distribution of the lubricant film at the equilibrium position is determined.

Results show that the deformation-induced misalignment has a significant influence on the performance of the bearing when the journal flexibility is taken into account. The parametric study reveals that the misalignment relies on system parameters such as bearing length-diameter ratio and static load.

The investigation of this work provides a quantification method of misalignment of hydrodynamic bearings considering the elastic deformation of the journal, which assists in the design of bearing in a rotor-bearing system.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0337/

This study aims to improve the robot’s performance during interactions with human and uncertain environments.

A joint stiffness model was established according to the molecular current method and the virtual displacement method. The position and stiffness coordination controller and fuzzy adaptive controller of variable stiffness joint are designed, and the principle prototype of variable stiffness joint is built. The position step and trajectory tracking performance of the variable stiffness joint are verified through experiments.

Experimental test shows that the joint stiffness can be quickly adjusted. The accuracy of position and trajectory tracking of the joint increases with higher stiffness and decreases with increasing frequency. The fuzzy adaptive controller performed better than the position and stiffness coordination controller in controlling the position step and trajectory tracking of the variable stiffness joint.

A hybrid flux adjustment mechanism is proposed for the components of variable stiffness robot joints, which reduces the mass of the output end of variable stiffness joints and the speed of joint stiffness adjustment. Aiming at the change of system controller performance caused by the change of joint stiffness, a fuzzy adaptive controller is proposed to improve the position step and trajectory tracking characteristics of variable stiffness joints.

In response to the navigation challenges faced by coal mine tunnel inspection robots in semistructured underground intersection environments, many current studies rely on structured map-based planning algorithms and trajectory tracking techniques. However, this approach is highly dependent on the accuracy of the global map, which can lead to deviations from the predetermined route or collisions with obstacles. To improve the environmental adaptability and navigation precision of the robot, this paper aims to propose an adaptive navigation system based on a two-dimensional (2D) LiDAR.

Leveraging the geometric features of coal mine tunnel environments, the clustering and fitting algorithms are used to construct a geometric model within the navigation system. This not only reduces the complexity of the navigation system but also optimizes local positioning. By constructing a local potential field, there is no need for path-fitting planning, thus enhancing the robot’s adaptability in intersection environments. The feasibility of the algorithm principles is validated through MATLAB and robot operating system simulations in this paper.

The experiments demonstrate that this method enables autonomous driving and optimized positioning capabilities in harsh environments, with high real-time performance and environmental adaptability, achieving a positioning error rate of less than 3%.

This paper presents an adaptive navigation system for a coal mine tunnel inspection robot using a 2D LiDAR sensor. The system improves robot attitude estimation and motion control accuracy to ensure safe and reliable navigation, especially at tunnel intersections.

This study aims to propose an optimization framework using deep neural networks (DNN) coupled with nondominated sorting genetic algorithm II and technique for order preference by similarity to an ideal solution method to improve the tribological properties of camshaft bearing pairs of internal combustion engine.

A lubrication model based on the theory of elastohydrodynamic lubrication and flexible multibody dynamics was developed for a V6 diesel engine. Setting DNN model as fitness function, the multi-objective optimization genetic algorithm and decision-making method were used to optimize the bearing pair structure with the goal of minimizing the total friction loss and the difference of the average values of minimum oil film thickness.

The results show that the lubrication state corresponding to the optimized bearing pair structure is elastohydrodynamic lubrication. Compared with the original structure, the optimized structure significantly reduces the total friction loss.

The optimized performance and corresponding structural parameters are obtained, and the optimization results were verified through multibody dynamics simulation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0417/

With the development trend of China’s service-oriented manufacturing moving toward intelligence and personalization, the deep integration of manufacturing and service has become a synergistic challenge for enterprises.

An improved migratory bird optimization (IMBO) algorithm is proposed to solve the multiobjective FJSP model. First, this paper designs an integer encoding method based on job-machine. The algorithm adopts the greedy decoding method to obtain the optimal scheduling solution. Second, this paper combines three initialization rules to enhance the quality of the initial population. Third, three neighborhood search strategies are combined to improve the search capability and convergence of the solution space. Furthermore, the IMBO algorithm introduces the concepts of nondominated ranking and crowding degree to update the population better. Finally, the optimal solution is obtained after multiple iterations.

Through the simulation of 15 benchmark studies and a production example of a furniture enterprise, the IMBO algorithm is compared with three other algorithms: the improved particle swarm optimization algorithm, the global and local search with reinitialization-based genetic algorithm and the hybrid grey wolf optimization algorithm. The experiment results show the effectiveness of the IMBO algorithm in solving the multiobjective FJSP.

The study does not consider the influence of disturbance factors, such as emergency interventions and equipment failures, on scheduling in actual production processing. It is necessary to further study the dynamic FJSP problem.

The study proposes an IMBO algorithm to solve the multiobjective FJSP problem. It also uses three initialization rules to broaden the range of the solution space. The study applies multiple crossover strategies to avoid the algorithm falling into local optimality.

This study examines the effect of Human Resource Management (HRM) policies in respect to workplace flexibility and employee empowerment on two employee behaviour related outcomes (employee organisational commitment (EOC) and collegiality) and organisational resilience during the COVID-19 pandemic.

Data were collected using an online survey questionnaire managed by Qualtrics. The questionnaire was distributed to the lower, middle and senior managers of 1,000 Australian organisations with 337 responses used in the analysis.

The findings indicate that workplace flexibility exhibits a direct and indirect (through collegiality) significant positive association with organisational resilience, and employee empowerment exhibits a direct and indirect (through both EOC and collegiality) significant positive association with organisational resilience.

The results highlight the importance of implementing desirable HRM policies in respect to empowering employees and enhancing workplace flexibility due to their role in facilitating organisational resilience both directly and indirectly through their influence on employee behaviour related outcomes, specifically EOC and collegiality.

This study aims to provide a new perspective and path to reduce the unsafe behavior of new generation of construction workers (NGCWs) in China. The purpose of this study is to explore the influencing mechanism of work-family balance on the unsafe behavior of NGCWs and test the mediating effect of job satisfaction and the moderating effect of group safety climate.

A theoretical model on the influencing mechanism of work-family balance on unsafe behavior of NGCWs was constructed through theoretical analysis. Research data were collected from 502 NGCWs via a questionnaire survey, and research hypotheses were testified with regression analysis.

The results show that work-family balance not only directly reduces NGCWs’ unsafe behavior but also indirectly reduces it through job satisfaction, which plays a partial mediating role. In addition to positively moderating the relationship between work-family balance and NGCWs’ unsafe behavior, group safety climate can also moderate the relationship between work-family balance and job satisfaction in a positive way.

This study provides practical implications for construction companies to reduce the unsafe behaviors of NGCWs from the perspective of work-family balance. Specifically, construction companies should adopt more flexible work rules, such as flexible organization and rotation systems, to increase their work autonomy. Meanwhile, construction companies need to improve the work environment and basic conditions for NGCWs, establish a reasonable salary system and provide attractive promotion opportunities to increase their job satisfaction. In addition, construction companies should provide active safety lectures and training, and supervisors should improve safety communication and interaction levels. Co-workers should remind workers about their safety attitudes and behaviors promptly. A good group safety climate will be created through the efforts of construction companies, supervisors and co-workers.

This study clarifies the influencing mechanism of work-family balance on the NGCWs’ unsafe behavior and further tests the partial mediating role of job satisfaction and the positively moderating effect of group safety climate on the influence relationship of work-family balance on job satisfaction and NGCWs’ unsafe behavior, which defines the boundary conditions of the relationship between work-family balance and NGCWs’ unsafe behavior, and promotes the effective integration of social exchange theory and theoretical system of influencing mechanism of construction workers’ unsafe behavior.

While scholarly studies focus on the role of technology in digital transformation, an important direction of research still requires examining HR-related factors in this regard specifically. This study aims to analyze factors pertaining to human and organizational resources in the context of digital transformation within healthcare enterprises. The study examines the possible impacts of organizational energy (OE) and human resource flexibility (HRF) on digital transformation (DT). The study also seeks to investigate the influence of organizational inertia (OI) on the relationships being examined, according to the theory of change principles.

The empirical study used a survey method on 355 Mansoura University Hospitals employees, Egypt. The study data were analyzed using structural equations modeling with WarpPLS V. 8.0.

The results showed that all OE dimensions directly affected DT and HRF dimensions. Through HRF, OE indirectly affected DT. The study also found that all dimensions of OI negatively moderated the OE-DT and HRF-DT relationships. Based on the study's results, theoretical and practical implications were drawn.

This study develops a novel model to empirically investigate the quantitative relationships between OE, HRF, OI, and DT. This study provides an addition to understanding how human resources and organizational mechanisms work in technology-based experiments such as digital transformation and adds contributions in this regard to the health sector in particular.

The COVID-19 pandemic has compelled higher education institutions (HEI) in the United Arab Emirates (UAE) and globally to shift to a new pedagogy that is sustainable and resilient to crises and disruptions. It necessitated the integration of technologies as part of pedagogical innovation and modification of higher education practices – advancing toward a more holistic integration of physical and digital tools and methods to enable more flexible, creative, collaborative and participatory learning. In terms of pedagogy, an open approach to learning is essential, combining in-person teaching with technological tools and online learning.

This paper examines theoretical and empirical literature to define the potential benefits of utilizing open educational practices (OEP) in higher education, including better access, furthering equity and enhancing teaching, learning and assessment.

It proposes a comprehensive framework built on a continuum of open pedagogy (OP) that comprises “Emphasis”, “Essentials” and “Evolution”. Based on this framework, a set of recommendations for using OEP for successful knowledge building is provided.

The research determined the significance of increased OEP involvement for sustainable learning possibilities and the UAE’s initiatives in developing educators to support innovative pedagogies and technology-enabled teaching-learning standards. The study suggests placing more emphasis on faculty and student scaffolding while using OP for better learning experiences and outcomes, as well as more institutional support and the need for policy development to transform the UAE into a global hub for sustainable education.

The use of a force sensor to estimate the external force of manipulator not only needs to deal with the signal noise of the sensor itself but also needs to solve the coupling interference of the sensor itself, especially the axial force. The purpose of this paper is to develop a three-dimensional fiber Bragg grating (FBG) wrist force sensor, which has a simple structure and reduces the coupling influence between several axes.

A particular separation elastic structure with four FBGs is devised for the three-axial force sensor. One FBG is suspended on the profile of central cylinder and the other three FBGs are pasted on the elastic beam surface of the over and under measuring bodies, respectively. Finite element analysis (FEA) simulation has been implemented to the strain distribution characteristics, the output characteristics of each direction and the coupling effects of the structure. Furthermore, theoretical derivation and experimental results are used to compare, which have a good consistency.

The experiment results show that the maximum repeatability error of the sensor is 6.75%, the maximum nonlinear error is 5.36%, the maximum coupling interference is 4.73% and the minimum sensitivity is 1.58 pm/N.

A three-dimensional force sensor based on FBG adopts a particular separation elastic structure. The sensor can reduce the coupling influence between several axes, especially the coupling interference in the z-direction is 0.