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Using cognitive appraisal theory, this study aims to propose and test an integrated framework – comprising robotic service quality, robotic service authenticity, customer existential authenticity and customer revisit intention – on diners with experience using robotic technology in restaurants. The moderating role of robotic appearance is in the hypothesised relationship.

Data was gathered through a Web-based survey delivered to 428 diners who had experience using robotic services in restaurants in China. The hypotheses were analysed using a structural equation model and multi-group analysis was used to analyse the moderating effect.

The findings indicate that functional service quality positively influences robotic service authenticity and existential authenticity. However, technical service quality only affects existential authenticity, which leads to revisit intention. Robotic appearance moderated the relationship between functional service quality and service authenticity.

Restaurateurs should enhance robotic service authenticity, existential authenticity and revisit intention by improving robotic technical service collaborating with robot manufacturers and operators.

Focusing on cognitive appraisal theory, the findings serve as a starting point for investigating robotic service quality and authenticity in robotic service settings theoretically and empirically.

This study aims to investigate the impact of indium (In) content on the thermal properties, microstructure and mechanical properties of Sn-3Ag-3Sb-xIn (x = 0, 1, 2, 3, 4, 5 Wt.%) solders to enhance the performance of tin-based solder under demanding conditions and to meet the urgent need for high-reliability microelectronic interconnection materials in emerging sectors such as automotive intelligent technology, 5G communication technology and high-performance computing.

In this study, Sn-3Ag-3Sb-xIn solder alloys were prepared. The thermal properties of the solder alloys were characterised by differential scanning calorimetry. Subsequently, optical microscopy, scanning electron microscopy, X-ray diffraction and an electron probe X-ray microanalyser were used to analyse the influence of the In content on the microstructure of the solder. The mechanical properties of solder alloys were determined through tensile testing.

As the In content increased, the melting temperature of the Sn-3Ag-3Sb-xIn solder decreased, accompanied by less nucleation undercooling and an expanded melting range. The incorporation of In led to an enhancement in the yield and tensile strengths of the Sn-3Ag-3Sb-xIn solder alloys, but with a concomitant decrease in plasticity. In comparison to commercial Sn-3.0Ag-0.5Cu solder alloys, the yield strength and tensile strength of the Sn-3Ag-3Sb-3In alloy increased by 8.64 and 21.69 MPa, respectively, while the elongation decreased by 11.48%.

Sn-3Ag-3Sb-3In solder alloy was the most appropriate and expected comprehensive properties. The enhancements will provide substantial assistance and precise data references for the interconnection requirements in high-strength interconnection fields, such as automotive intelligent technology, 5G communication technology and high-performance computing.

The application of industrial robots in modern production is becoming increasingly widespread. In the context of flexible production lines, quickly and accurately identifying and grasping specified workpieces is particularly important. This study aims to propose a grasping scheme that combines traditional methods with deep learning to improve grasping accuracy and efficiency.

First, a dataset generation method is proposed, which constructs a point cloud dataset close to the real scene without the need for extensive data collection. Then, the 3D object detection algorithm PointPillars is improved based on the features of the scene point cloud, allowing for the analysis of part poses to achieve grasping. Finally, a grasp detection strategy is proposed to match the optimal grasp pose.

Experimental results show that the proposed method can quickly and easily construct high-quality datasets, significantly reducing the time required for preliminary preparation. Additionally, it can effectively grasp specified workpieces, significantly improving grasping accuracy and reducing computation time.

The main contribution of this paper is the integration of a novel dataset generation method, improvements to the PointPillars algorithm for 3D object detection and the development of an optimal grasp detection strategy. These advancements enable the grasping system to handle real-world scenarios efficiently and accurately, demonstrating significant improvements over traditional methods.

To enhance the load capacity and dynamic characteristics of gas foil conical bearings (GFCBs), two kinds of microgrooves (sector and Fibonacci-like shape) are arranged on the top foil surface.

The Reynolds equation considering gas rarefaction effect is solved by the finite difference method, in which the 2D plate element stiffness model is used for the grooved top foil. The influence of groove on the static characteristics is studied, and the dynamic characteristics of novel bearing are obtained by the perturbation method.

The results show that the gas rarefaction effect on the load capacities is negligible, and the novel GFCB with microgrooved top foil has higher load capacities. Moreover, the deeper groove is conductive to the dynamic stability improvement. The positive Fibonacci-like groove seems to be the most suitable shape, which can largely increase the axial load capacity with little additional torque cost. And the improvement of dynamic characteristics for the Fibonacci-like grooved GFCB is also more favorable.

As the low cost of groove processing, it is an effective way to improve GFCB’s performance and even can be used to upgrade the bearings in service.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0148/