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The purpose of this paper is to establish mechanisms for process improvement so that production efficiency and product quality can be expected, and create a sustainable development in terms of circular economy.

The authors obtain a critical value from statistical hypothesis testing, and thereby construct a process capability indices chart, which both lowers the chance of quality level misjudgment caused by sampling error and provides reference for the processes improvement in poor quality levels. The authors used the bottom bracket of bicycles as an example to demonstrate the model and methods proposed in this study.

This approach enables us to plot multiple quality characteristics, despite varying attributes and specifications, onto the same process capability analysis chart. And it therefore increases accuracy and precision to reduce rework and scrap rates (reduce), increase product availability, reduce maintenance frequency and increase reuse (reuse), increase the recycle rates of components (recycle) and lengthen service life, which will delay recovery time (recovery).

Parts manufacturers in the industry chain can upload their production data to the cloud platform. The quality control center of the bicycle manufacturer can utilized the production data analysis model to identify critical-to-quality characteristics. The platform also offers reference for improvement and adds the improvement achievements and experience to its knowledge management to provide the entire industry chain. Feedback is also given to the R&D department of the bicycle manufacturer as reference for more robust product designs, more reasonable tolerance designs, and selection criteria for better parts suppliers, thereby forming an intelligent manufacturing loop system.

In prior literature, online endorsement system allowing the users to “like” or “dislike” shared information is found very useful in information filtering and trust elicitation in most social networks. This paper shows that such systems could fail in the context of investment communities due to several psychological biases.

This study develops a series of regression analyses to model the “like”/“dislike” voting process and whether or not such endorsement distinguishes between valuable information and noise. Trading simulations are also used to validate the practical implications of the findings.

The main findings of this research are twofold: (1) in the context of investment communities, online endorsement system fails to signify value-relevant information and (2) bullish information and “wisdom over the past event” information receive more “likes” and fewer “dislikes” on average, but they underperform in stock market price discovery.

This study demonstrates that biased endorsement may lead to the failure of the online endorsement system as information gatekeeper in investment communities. Two underlying mechanisms are proposed and tested. This study opens up new research opportunities to investigate the causes of biased endorsement in online environment and motivates the development of alternative information filtering systems.

The aim of this study was to integrate the hierarchical model of the perceived service quality (PSQ) theory with the bottom-up theory of satisfaction. It was hypothesised that satisfaction with sporting events would mediate the relationship between PSQ and life satisfaction. Study 1 was conducted to translate the Perceived Service Quality questionnaire (PSQQ) (Brady & Cronin, 2011) into Chinese and to validate it for sporting events. Study 2 was conducted to examine the main hypothesis. The results indicated that satisfaction-withevent partially mediated the relationship between PSQ and life satisfaction. The results are discussed in terms of both the examined theories.

The membrane wall is one of the most important components in the boiler industry and numerous studs are welded on its surface. The membrane wall welding still remains a sector intensive in the manual and arduous works. This paper aims to propose a dual-robot system to automatically weld studs on the membrane wall.

In this paper, the authors proposed a dual-robot stud welding system for membrane walls. First, the membrane wall is divided into several zones and the welding paths are planned. Then, the pose of the pipes is calculated based on the data measured by light section sensors. The planned paths are compensated by the pose. Finally, the robots weld studs based on the compensated paths.

The method effectively eliminates manufacturing errors and welding distortions. The system can weld straight type and L-type membrane walls with high efficiency, high quality and high accuracy.

The system can weld straight type and L-type membrane walls with high efficiency and high quality. Experiments were performed in a factory to demonstrate the practicability of the method. The dual-robot system with two welding machines has approximately twice the efficiency of the manual welder with only one welding machine. The quality and accuracy of robot welding systems are higher than that of manual welding.

As a core rotating component of power machinery and working machinery, the rotor system is widely used in the fields of machinery, electric power and aviation. When the system operates at high speed, the system stability is of great importance. To enhance the system stability, squeeze film damper (SFD) is being installed in the rotor system to alleviate vibration. The purpose of this paper is to first classify the rotor system into two types, the dual rotor system and the single rotor system, and to comprehensively and specifically mention the method of generating the dynamic model. Next, based on the establishment of a dynamic model with and without SFD in the rotor system, the optimization design of the rotor system with SFD was carried out using a genetic algorithm. Through sensitivity analysis, SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system, and the objective function was the minimization of the maximum amplitude of the rotor system with SFD within the operation speed range.

In this paper, first, the rotor system was classified into two types, namely, the dual rotor system and the single rotor system, and the method of creating a dynamic model was comprehensively and specifically mentioned. Here, the dynamic model of the rotor system was derived in detail for the single rotor system and the dual rotor system with and without SFD. Next, based on the establishment of a dynamic model with and without SFD in the rotor system, the optimization design of the rotor system with SFD was carried out using a genetic algorithm. The sensitivity analysis of the unbalanced response was carried out to determine the design variables of the optimization design. Through sensitivity analysis, SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system, and the objective function was the minimization of the maximum amplitude of the rotor system with SFD within the operation speed range.

SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system through sensitivity analysis of the unbalanced response. These three variables are basic factors affecting the amplitude of the rotor system with SFD.

In the existing studies, only a dynamic model of a single rotor system with SFD was created, and the characteristic values of pure SFD were selected as optimization variables and optimization design was carried out. But in this study, the rotor system was classified into two types, namely, the dual rotor system and the single rotor system, and the method of creating a dynamic model was comprehensively and specifically mentioned. In addition, optimization design variables were selected and optimized design was performed through sensitivity analysis on the unbalanced response of factors affecting the vibration characteristics of the rotor system.

The purpose of this paper is to evaluate design performance of 51 gear shaping machines by using data envelopment analysis (DEA).

Existing studies extend traditional DEA by handling bounded and discrete data based on envelopment models. However, value judgment is usually neglected and fail to be incorporated in these envelopment models. In many cases, there is a need for prior preferences. Using existing DEA approaches as a backdrop, the current paper presents a methodology for incorporating assurance region (AR) restrictions into DEA with bounded and discrete data, i.e. the assurance region bounded discrete (AR-BD) DEA model. Then, the AR-BD DEA model is combined with a context-dependent DEA to obtain an efficiency stratification.

The authors examine different AR restrictions and calculate efficiency scores of five scenarios of AR restrictions by using the proposed AR-BD DEA model. It shows that AR restrictions have a great impact on the efficiency scores. The authors also identify nine efficient frontiers in total. For each decision-making unit, it could set benchmarks and improve its performance based on each higher efficient frontier.

This paper first evaluates efficiency of gear shaping machines by considering different (bounded and discrete) variable types of data and including AR restrictions. The AR-BD DEA model and context-dependent AR-BD DEA model proposed in this paper further enrich the DEA theory. The findings in this paper certainly provide useful information for both producers and consumers to make smart decisions.

This paper aims to solve the nonlinear problem in the uncertainty evaluation of the measurement of the positioning repeatability (RP) of industrial robots and provide guidance to restrict the uncertainty of measurement of RP (u_RP).

Firstly, some uncertain sources existing in the measurement procedure of RP are identified. Secondly, the probability distribution function (PDF) of every source is established on the basis of its measurements. Some spatial combined normal distributions are adopted. Then, a method, based on Monte Carlo method (MCM) and established measurement model, is developed for the estimation of u_RP. Thirdly, some tests are developed for the identification and validation of the selected PDFs of uncertain sources. Afterwards, the proposed method is applied for the evaluation and validation of the u_RP. Finally, influence analyses of some key factors are proposed for the quantification of their relative contributions to u_RP.

Results show that the proposed method can reasonably and objectively estimate the u_RP of the selected industrial robot, and changes of the industrial robots’ position and the laser trackers measurement are correlated. Additionally, the u_RP of the selected industrial robot can be restricted by using the results of its key factors on u_RP.

This paper proposes the spatial combined normal distribution to model the uncertainty of the repeatability of the laser tracker and industrial robot. Meanwhile, the proposed method and influence analyses can be used in estimating and restricting the u_RP and thus useful in determining whether the RP of a tested industrial robot meets its requirements.