The purpose of this paper is to monitor small shifts in the process mean and/or variance for which observational data meet significant autocorrelation.
Abstract
Purpose
The purpose of this paper is to monitor small shifts in the process mean and/or variance for which observational data meet significant autocorrelation.
Design/methodology/approach
A generally weighted moving average (GWMA) control chart for monitoring a process is introduced in which the observations can be modelled as a first‐order autoregressive process with a random error. Using simulation, the average run lengths (ARLs) of control schemes are compared.
Findings
The results showed that the GWMA control chart of observations requires less time to detect small shifts in the process mean and/or variance than the EWMA control chart.
Originality/value
The paper presents a useful discussion of a method that enables the detecting ability of the EWMA control chart to be enhanced and shows that when the observations are drawn from an AR(1) process with random error, the EWMA control chart is far more useful than the Shewhart control chart in detecting small shifts. The GWMA control chart of observations is shown to be superior to the EWMA control chart in detecting small shifts in the process mean and variance. The GWMA control chart of observations requires less time to detect small process mean and/or variance shifts as the level of autocorrelation declines. However, the GWMA and EWMA control charts of observations perform poorly for large shifts.
Details
Keywords
– The purpose of this paper is to improve the forecasting efficiency of a grey model.
Abstract
Purpose
The purpose of this paper is to improve the forecasting efficiency of a grey model.
Design/methodology/approach
The exponentially weighted moving average (EWMA) algorithm is proposed to modify background values for a new grey model optimization.
Findings
The experimental results reveal that the proposed models (EGM, REGM) outperform traditional grey models.
Originality/value
A genetic algorithm (GA) optimizer is used to select the optimal weights for the background values of the EGM(1,1) and REGM(1,1) forecast models. The results of the current study are very encouraging, as the empirical results show that the REGM(1,1) and EGM(1,1) models reduce the MAPE rates over the traditional GM(1,1) and RGM(1,1) models.
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Keywords
Chia-Ling Chang, Yen-Liang Chen and Jia-Shin Li
The purpose of this paper is to provide a cross-platform recommendation system that recommends the most suitable public Instagram accounts to Facebook users.
Abstract
Purpose
The purpose of this paper is to provide a cross-platform recommendation system that recommends the most suitable public Instagram accounts to Facebook users.
Design/methodology/approach
We collect data from both Facebook and Instagram and then propose a similarity matching mechanism for recommending the most appropriate Instagram accounts to Facebook users. By removing the data disparity between the two heterogeneous platforms and integrating them, the system is able to make more accurate recommendations.
Findings
The results show that the method proposed in this paper can recommend suitable public Instagram accounts to Facebook users with very high accuracy.
Originality/value
To the best of the authors’ knowledge, this is the first study to propose a recommender system to recommend Instagram public accounts to Facebook users. Second, our proposed method can integrate heterogeneous data from two different platforms to generate collaborative recommendations. Furthermore, our cross-platform system reveals an innovative concept of how multiple platforms can promote their respective platforms in a unified, cooperative and collaborative manner.
Details
Keywords
Shijie Dai, Shining Li, Wenbin Ji, Zhenlin Sun and Yufeng Zhao
This study aims to realize the constant force grinding of automobile wheel hub.
Abstract
Purpose
This study aims to realize the constant force grinding of automobile wheel hub.
Design/methodology/approach
A force control strategy of backstepping + proportion integration differentiation (PID) is proposed. The grinding end effector is installed on the flange of the robot. The robot controls the position and posture of the grinding end actuator and the grinding end actuator controls the grinding force output. First, the modeling and analysis of the grinding end effector are carried out, and then the backstepping + PID method is adopted to control the grinding end effector to track the expected grinding force. Finally, the feasibility of the proposed method is verified by simulation and experiment.
Findings
The simulation and experimental results show that the backstepping + PID strategy can track the expected force quickly, and improve the dynamic response performance of the system and the quality of grinding and polishing of automobile wheel hub.
Research limitations/implications
The mathematical model is based on the pneumatic system and ideal gas, and ignores the influence of friction in the working process of the cylinder, so the mathematical model proposed in this study has certain limitations. A new control strategy is proposed, which is not only used to control the grinding force of automobile wheels, but also promotes the development of industrial control.
Social implications
The automatic constant force grinding of automobile wheel hub is realized, and the manpower is liberated.
Originality/value
First, the modeling and analysis of the grinding end effector are carried out, and then the backstepping + PID method is adopted to control the grinding end effector to track the expected grinding force. The nonlinear model of the system is controlled by backstepping method, and in the process, the linear system composed of errors is obtained, and then the linear system is controlled by PID to realize the combination of backstepping and PID control.