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This study aims to investigate how Lean Six Sigma (LSS), a widely used paradigm that promotes competitive advantage of different organisations in a more sustainable and environmentally friendly way, affects operational performance in different organisational contexts. Although LSS is widely used to improve operational performance, the impact of LSS on operational performance appears to be different in different organisational contexts, prompting the attention of researchers and managers to shift from lean philosophy to the impact of contextual variables on the effectiveness of LSS implementation.

This study uses a quantitative research design and conducts an empirical study in Pakistan. The sample consists of 339 management employees with an effective response rate of 67.8% in various sectors. In this study, partial least square structural equation modelling is used to examine the relationships among the variables using the resource-based view (RBV) and dynamic capability theory (DCT) to support the model of this study.

This study reveals that the relationship between LSS and operational performance is partially mediated by green human resource management (GHRM) and internal environmental management (IEM). The moderating effect of the organisational developmental culture between LSS and operational performance is not identified, implying that the effect of developmental culture could vary under different cultures.

There is a lack of empirical studies investigating the role of GHRM, IEM and developmental culture in developing countries. This study extends the literature on the RBV and DCT in operational performance. The study’s outcome provides theoretical and practical implications for enhancing the effect of LSS implementation on operational performance in focal small and medium-sized enterprises (SMEs) through human and environmental management factors.

The study aims to explore how young consumers perceive and adopt the online e-waste collection platform, by developing a conceptual framework that integrates the theory of planned behavior, the technology acceptance model and the perceived risk. Based on conceptual framework, the study further identifies factors that positively or negatively influence the Chinese millennials' decision on the use of online collection platform.

The study conducts a questionnaire survey from 807 Chinese millennials living in urban and rural areas. Based on the collected data, the partial least squares structural equation modeling (PLS-SEM) is employed to conduct PLS path modeling and multi-group analysis.

The study results support the proposed conceptual framework and confirm its robustness in investigating Chinese millennials' intentions to adopt online e-waste collection platform. The findings suggest that the perceived usefulness, perceived ease of use, attitude, subjective norms and perceived behavioral control have positive impact, while perceived risk has negative impact on the behavioral intentions of millennials on the adoption of the platform.

With the emergence of Internet technology, online e-waste collection platform has arisen as an innovative and alternative solution to improve environmental sustainability by encouraging e-waste collection through formal recycling channels in China. In order to divert the consumers from informal recycling channels to online e-waste collection platform, it is necessary to understand what factors impact the adoption of this platform among consumers. The study provides theoretical contribution and practical implications relevant to regulators and practitioners to encourage the adoption of online e-waste collection platform.

This paper investigates how the configuration of a supplier’s sustainable operations practices (SOPs) with a high sustainable performance affects a buyer’s organizational performance in the buyer-supplier dyad.

This study first identifies the key SOPs using bibliometric and content analyses. Then, the research hypotheses are proposed using complexity theory and the resource-based view. This study applies fuzzy-set qualitative comparative analysis (fsQCA) on a sample of 74 buyer-supplier dyads in China to explore the configurations of a supplier’s SOPs that may attain a high sustainable performance. An analysis of variance (ANOVA) is performed to test the effects of these configurations on a buyer’s financial and operational performance.

The empirical findings inform that six configurations of a supplier’s key SOPs lead to a high sustainable performance, and are linked to a buyer’s operational and financial performance. A buyer’s financial performance is highest when its supplier adopts a combination of SOPs corresponding to the defensive, accommodative, and proactive sustainability strategies. A buyer’s operational performance is relatively high when its supplier adopts a combination of SOPs corresponding to the defensive and accommodative sustainability strategies.

This study is the first to draw on complexity theory and the resource-based view as complementary frameworks to analyze how the configuration of a supplier’s SOPs with a high sustainable performance affects a buyer’s organizational performance in the buyer-supplier dyad.

The purpose of this paper is to study the controller design of flexible manipulator. Flexible manipulator system is a nonlinear, strong coupling, time-varying system, which is introduced elastodynamics in the study and complicated to control. However, due to the flexible manipulator, system has a significant advantage in response speed, control accuracy and load weight ratio to attract a lot of researchers.

Since the order of flexible manipulator system is high, designing controller process will be complex, and have a large amount of calculation, but this paper will use the dynamic surface control method to solve this problem.

Dynamic surface control method as a controller design method which can effectively solve the problem with the system contains nonlinear and reduced design complexity.

The authors assume that the dynamic parameters of flexible manipulator system are unknown, and use Radial Basis Function neural network to approach the unknown system, combined with the dynamic surface control method to design the controller.

This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions.

The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems.

The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints.

The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs.

This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.

The purpose of this paper is to enhance the performance of robots in peg-in-hole assembly tasks, enabling them to swiftly and robustly accomplish the task. It also focuses on the robot’s ability to generalize across assemblies with different hole sizes.

Human behavior in peg-in-hole assembly serves as inspiration, where individuals visually locate the hole firstly and then continuously adjust the peg pose based on force/torque feedback during the insertion process. This paper proposes a novel framework that integrate visual servo and adjustment based on force/torque feedback, the authors use deep neural network (DNN) and image processing techniques to determine the pose of hole, then an incremental learning approach based on a broad learning system (BLS) is used to simulate human learning ability, the number of adjustments required for insertion process is continuously reduced.

The author conducted experiments on visual servo, adjustment based on force/torque feedback, and the proposed framework. Visual servo inferred the pixel position and orientation of the target hole in only about 0.12 s, and the robot achieved peg insertion with 1–3 adjustments based on force/torque feedback. The success rate for peg-in-hole assembly using the proposed framework was 100%. These results proved the effectiveness of the proposed framework.

This paper proposes a framework for peg-in-hole assembly that combines visual servo and adjustment based on force/torque feedback. The assembly tasks are accomplished using DNN, image processing and BLS. To the best of the authors’ knowledge, no similar methods were found in other people’s work. Therefore, the authors believe that this work is original.

This paper aims to deal with the force and position tracking problem when a robot performs a task in interaction with an unknown environment and presents a hybrid control strategy based on variable admittance control and fixed-time control.

A hybrid control strategy based on variable admittance control and fixed-time control is presented. Firstly, a variable stiffness admittance model control based on proportional integral and differential (PID) is adopted to maintain the expected force value during the task execution. Secondly, a fixed-time controller based on radial basis function neural network (RBFNN) is introduced to handle the model uncertainties and ensure the fast position tracking convergence of the robot system, while the singularity problem is also avoided by designing the virtual control variable with piecewise function.

Simulation studies conducted on the robot manipulator with two degrees of freedom have verified the superior performance of the proposed control strategy comparing with other methods.

A hybrid control scheme for robot–environment interaction is presented, in which the variable stiffness admittance method is adopted to adjust the interaction force to the desired value, and the RBFNN-based fixed-time position controller without singularity problem is designed to ensure the fast convergence of the robot system with model uncertainty.

Bolted joint is the most important connection method in aircraft composite/metal stacked connections due to its large load transfer capacity and high manufacturing reliability. Aircraft components are subjected to complex hybrid variable loads during service, and the mechanical properties of composite/metal bolted joint directly affect the overall safety of aircraft structures. Research on composite/metal bolted joint and their mechanical properties has also become a topic of general interests. This article reviews the current research status of aeronautical composite/metal bolted joint and its mechanical properties and looks forward to future research directions.

This article reviews the research progress on static strength failure and fatigue failure of composite/metal bolted joint, focusing on exploring failure analysis and prediction methods from the perspective of the theoretical models. At the same time, the influence and correlation mechanism of hole-making quality and assembly accuracy on the mechanical properties of their connections are summarized from the hole-making processes and damage of composite/metal stacked structures.

The progressive damage analysis method can accurately analyze and predict the static strength failure of composite/metal stacked bolted joint structures by establishing a stress analysis model combined with composite material performance degradation schemes and failure criteria. The use of mature metal material fatigue cumulative damage models and composite material fatigue progressive damage analysis methods can effectively predict the fatigue of composite/metal bolted joints. The geometric errors such as aperture accuracy and holes perpendicularity have the most significant impact on the connection performance, and their mechanical responses mainly include ultimate strength, bearing stiffness, secondary bending effect and fatigue life.

Current research on the theoretical prediction of the mechanical properties of composite/metal bolted joints is mainly based on ideal fits with no gaps or uniform gaps in the thickness direction, without considering the hole shape characteristics generated by stacked drilling. At the same time, the service performance evaluation of composite/metal stacked bolted joints structures is currently limited to static strength and fatigue failure tests of the sample-level components and needs to be improved and verified in higher complexity structures. At the same time, it also needs to be extended to the mechanical performance research under more complex forms of the external loads in more environments.

The mechanical performance of the connection structure directly affects the overall structural safety of the aircraft. Many scholars actively explore the theoretical prediction methods for static strength and fatigue failure of composite/metal bolted joints as well as the impact of hole-making accuracy on their mechanical properties. This article provides an original overview of the current research status of aeronautical composite/metal bolted joint and its mechanical properties, with a focus on exploring the failure analysis and prediction methods from the perspective of theoretical models for static strength and fatigue failure of composite/metal bolt joints and looks forward to future research directions.