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Aero-engine components endure combined high and low cycle fatigue (CCF) loading during service, which has attracted more research attention in recent years. This study aims to construct a new framework for the prediction of probabilistic fatigue life and reliability evaluation of an aero-engine turbine shaft under CCF loading if considering the material uncertainty.

To study the CCF failure of the aero-engine turbine shaft, a CCF test is carried out. An improved damage accumulation model is first introduced to predict the CCF life and present high prediction accuracy in the CCF loading situation based on the test. Then, the probabilistic fatigue life of the turbine shaft is predicted based on the finite element analysis and Monte Carlo analysis, where the material uncertainty is taken into account. At last, the reliability evaluation of the turbine shaft is conducted by stress-strength interference models based on an improved damage accumulation model.

The results indicate that predictions agree well with the tested data. The improved damage accumulation model can accurately predict the CCF life because of interaction damage between low cycle fatigue loading and high cycle fatigue loading. As a result, a framework is available for accurate probabilistic fatigue life prediction and reliability evaluation.

The proposed framework and the presented testing in this study show high efficiency on probabilistic CCF fatigue life prediction and can provide technical support for fatigue optimization of the turbine shaft.

The novelty of this work is that CCF loading and material uncertainty are considered in probabilistic fatigue life prediction.

E-commerce live streaming is a new influencer advertising method that allows influencers to interact directly with consumers on e-commerce platforms. Although evidence suggests that influencer live-streaming advertisements (ads) on social media can increase consumers’ buying impulses, little research examined how this similar but new advertising method on e-commerce platforms may influence consumers’ urge to buy impulsively. This study explores the role of influencer credibility, celebrity effect, perceived entertainment, trust and perceived usefulness on consumers’ attitudes toward influencer ads and their urge to buy impulsively.

A questionnaire containing seven constructs was developed and distributed to participants using a convenient sample and snowball sampling approach. The constructs were measured based on validated measurement items from the literature and adjusted according to this study’s focus. A total of 236 valid responses were obtained from the survey and used for data analysis. A partial least squares structural equation modeling approach was employed for parameter estimation and model testing.

The empirical results show that all constructs influenced consumers’ urge to buy impulsively via attitude toward influencer ads. The proposed research model explains 61.7% of the variance in attitude toward influencer ads and 19.4% of the urge to buy impulsively.

This is an early study investigating the relationship between influencer advertising and impulse buying. The results provide valuable insights into improving the design of influencer ads and marketing strategies.

1. I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

2. Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

3. Influencer credibility affects consumer attitude via celebrity effect as a mediator.

4. Trust affects consumer attitude via perceived usefulness as a mediator.

5. Entertaining ads help develop favorable consumer attitude.

I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

Influencer credibility affects consumer attitude via celebrity effect as a mediator.

Trust affects consumer attitude via perceived usefulness as a mediator.

Entertaining ads help develop favorable consumer attitude.

The framework, methodology and development of pansystems cybernetics are introduced. Related contents include: the postmodernizational systems thought, the epitome of pansystems methods, hi‐tech mechanism, social cybernetics, pansystems views of value, labor, management and economics, pedagogy, history and futurology, systems mathematics, general clustering analysis, observocontrollability, generalized living systems, information metascience, regret information, general fuzzy control, generalized gray systems, entropy, large scale dynamical supercomplicated Shengke systems, function simulations, transformation theory, simplification, strengthening, forming substance of subsystems of living systems of Miller’s theory, etc.

The purpose of this paper is to present a state‐of‐the‐art review of dimensional tolerance synthesis and to demonstrate the evolution of tolerance synthesis from product to process‐oriented strategy, as well as to compare the same for single stage and multistage manufacturing systems (MMS). The main focus is in delineating the different approaches, methods and techniques used with critical appraisal of their uses, applicability and limitations, based on which future research directions and a generic methodology are proposed.

Starting with issues in tolerancing research, the review demonstrates the critical aspects of product and process‐oriented tolerance synthesis. The aspects considered are: construction of tolerance design functions; construction of optimization functions; and use of optimization methods. In describing the issues of process‐oriented tolerance synthesis, a comparative study of single and multistage manufacturing has been provided.

This study critically reviews: the relationship between the tolerance variables and the variations created through manufacturing operations; objective functions for tolerance synthesis; and suitable optimization methods based upon the nature of the tolerance variables and the design functions created.

This study is limited to dimensional tolerance synthesis problems and evolution of process‐oriented tolerance synthesis to counteract dimensional variation problems in assembly manufacturing.

The paper provides a comprehensive and step‐by‐step approach of review of dimensional tolerance synthesis.

The paper aims to reduce the low-frequency resonance and residual vibration of the robot during the operation, improve the working accuracy and efficiency. A reduced weight and large load-to-weight ratio can improve the practical application of a collaborative robot. However, flexibility caused by the reduced weight and large load-to-weight ratio leads to low-frequency resonance and residual vibration during the operation of the robot, which reduces the working accuracy and efficiency. The vibrations of the collaborative robot are suppressed using a modified trajectory-planning method.

A rigid-flexible coupling dynamics model of the collaborative robot is established using the finite element and Lagrange methods, and the vibration equation of the robot is derived. Trajectory planning is performed with the excitation force as the optimization objective, and the trajectory planning method is modified to reduce the vibration of the collaborative robot and ensure the precision of the robot terminal.

The vibration amplitude is reduced by 80%. The maximum torque amplitude of the joint before the vibration suppression reaches 50 N·m. After vibration suppression, the maximum torque amplitude of the joint is 10 N·m, and the resonance phenomenon is eliminated during the operation process. Consequently, the effectiveness of the modified trajectory planning method is verified, where the vibration and residual vibration in the movement of the collaborative robot are significantly reduced, and the positioning accuracy and working efficiency of the robot are improved.

This method can greatly reduce the vibration and residual vibration of the collaborative robot, improve the positioning accuracy and work efficiency and promote the rapid application and development of collaborative robots in the industrial and service fields.

Experiences of high quality games between top-class sports teams could influence sports fans’ decision to attend the domestic sports games. For example, soccer fans who watched the World Cup games between the best national teams are likely to be disappointed with the performance of their domestic league teams after the World Cup event, while more people might be attracted to watch a soccer game because of their increased interest in soccer games. The purpose of this paper is to investigate how the international sports event (i.e. the World Cup) influences the demand of the domestic sports league games in the non-hosting country.

To test these antithetical hypotheses, the authors collect the Chinese Super League game-level data from 2004 to 2011. For analysis, the authors propose two empirical models rigorously developed based on previous sports marketing theories.

The findings are surprising compared to previous studies for the hosting countries or countries that performed spectacularly during the World Cup tournaments. The authors find that the international event negatively influences the attendance of domestic games. Specifically, it gives salience to the competitive quality of a match and helps enhance the impact of star players. Furthermore, the authors find evidence of dynamic effects of the international event.

The study contributes to the previous sports literatures by expanding our understanding of the effect of international sports events. Particularly, the results shed light on international events’ impact on the domestic sports league demand in more general conditions based on its influence on people’s behavior, rather than focusing on the effect caused by facility development or dramatic performance during the international event.

B&B stays have enjoyed popularity in China over recent decades. This study examines the impacts of the three dimensions of tourist experiential quality on the perceived functional and emotional value and customer satisfaction with B&B stays in Southwestern China.

Questionnaires were collected from 433 Chinese visitors in Southwestern China. Partial least squares–structural equation modeling (PLS-SEM) was used to test the significance of the relationship that exists among experiential quality, perceived value and tourist satisfaction.

The research results proved that experiential quality predicts customer satisfaction with B&B stays as mediated by perceived functional and emotional values. The specific experiential quality - fun – has the strongest effect on both perceived functional value and emotional value between the three dimensions of experiential quality.

Since fun is viewed as the most significant element, B&B providers should consider creating a more joyful encounter for tourists. They should enrich the activities and improve service to strengthen the experiential quality perceived by the tourists. Both relational experiences and authentic local experiences should be incorporated into the activities and services provided.

This is likely to be the first study to investigate the influence of three dimensions of experiential quality on perceived functional and emotional value and satisfaction from the B&B industry in China. The findings provide value through actionable insights into experiential qualities, functional and emotional values that drive tourist satisfaction.

To ensure the motion attitude and stable contact force of massage robot working on unknown human tissue environment, this study aims to propose a robotic system for autonomous massage path planning and stable interaction control.

First, back region extraction and acupoint recognition based on deep learning is proposed, which provides a basis for determining the working area and path points of the robot. Second, to realize the standard approach and movement trajectory of the expert massage, 3D reconstruction and path planning of the massage area are performed, and normal vectors are calculated to control the normal orientation of robot-end. Finally, to cope with the soft and hard changes of human tissue state and body movement, an adaptive force tracking control strategy is presented to compensate the uncertainty of environmental position and tissue hardness online.

Improved network model can accomplish the acupoint recognition task with a large accuracy and integrate the point cloud to generate massage trajectories adapted to the shape of the human body. Experimental results show that the adaptive force tracking control can obtain a relatively smooth force, and the error is basically within ± 0.2 N during the online experiment.

This paper incorporates deep learning, 3D reconstruction and impedance control, the robot can understand the shape features of the massage area and adapt its planning massage path to carry out a stable and safe force tracking control during dynamic robot–human contact.

The purpose of this paper is to propose a hybrid algorithm of the heuristic algorithm and the orthogonal design to optimize schemes of welding points (WPs). Assembly variation plays an important role in product manufacture. Different schemes of WPs can influence the sensitivity matrices between part and assembly variations.

The paper proposes a hybrid algorithm to optimize schemes of WPs among components. The hybrid algorithm is composed of the heuristic algorithm and the orthogonal design. The heuristic algorithm is used to optimize the initial scheme; moreover, the last result is generated according to the orthogonal table. Although the algorithm cannot assure generating the optimal scheme, it can acquire the satisfying result by using few times of finite element analysis.

Finally, a rear bracket lamp assembly is illustrated to optimize the schemes of WPs between two components. Results show that the algorithm is efficient to generate the optimized WPs scheme for sheet metal assemblies.

A hybrid algorithm is proposed to optimize schemes of WPs among components, which is composed of the heuristic algorithm and the orthogonal design.