scholarly journals Pengembangan Bagan Kendali 3 Sigma Berbasis Simulasi Untuk Pengawasan Variabilitas Proses Multivariat

2020 ◽  
Vol 6 (2) ◽  
pp. 158
Author(s):  
Rahmat Sagara ◽  
Khoirul Umam
Keyword(s):  
Standard Deviation ◽  
Control Charts ◽  
Simulated Data ◽  
Least Square Method ◽  
Least Square ◽  
Process Variability ◽  
Generalized Variance ◽  
Constant Multiplier ◽  
The Mean ◽  
Control Limits

This article describes a method in developing control charts for generalized variance as a quality statistics in terms of process variability through simulation. Mathematical equation that maps sample size n and number of quality variables p onto constant multiplier of standard deviation K is obtained thorough least square method using simulated data. The constant K for a certain n and p is used for control charts with the  upper control limits of UCL=μ+Kσ where μ and σ are the mean and the standard deviation of the generalized variance, respectively. The simulation of finding the constant K is used with the constraint of 3 sigma paradigm.

A Camera Calibration Method Based on Free Points

2011 ◽  
Vol 130-134 ◽  
pp. 1885-1888
Author(s):  
Jing Lei Zhang ◽  
Kai Bo Fan ◽  
Yan Jiao Wang
Keyword(s):  
Standard Deviation ◽  
Ccd Camera ◽  
Least Square Method ◽  
Calibration Method ◽  
Initial Guess ◽  
Least Square ◽  
Camera Model ◽  
Extrinsic Parameters ◽  
The Mean ◽  
Constraint Method

A new accurate calibrating technique for intrinsic parameters and extrinsic parameters of CCD camera is described. The camera model is derived by the pinhole projection theory. Then other parameters of the model are resolved under the radial alignment constraints and orthogonal constraints. In order to get a fine initial guess for the nonlinear searching solution, the least square method is introduced, and finally uses radial alignment constraint method to get the results. The experimental results show that the mean absolute differences in x direction and y direction are 0.0070 and 0.1430 separately while the standard deviation are 0.5006 and 1.2046 separately.

Single-Subgroup Performance Measures and Diagnostic Procedures for X-Bar Control Charts

1994 ◽  
Vol 116 (2) ◽  
pp. 216-224
Author(s):  
G. E. Rahn ◽  
S. G. Kapoor ◽  
R. E. DeVor
Keyword(s):  
Performance Measures ◽  
Control Charts ◽  
Simulated Data ◽  
Diagnostic Procedures ◽  
Shewhart Control Charts ◽  
Operational Characteristics ◽  
Shewhart Control ◽  
The Mean ◽  
Measures Of Performance ◽  
Tremendous Impact

Although Shewhart control charts have had a tremendous impact on quality improvement, the inability to precisely measure chart performance has limited their role, and subsequently overall effectiveness in the control of manufacturing processes. Measures of performance in terms of operational characteristics (OC) are defined on two distinct levels: (a) single-subgroup level, which examines the probability of a rule violation at any given subgroup (b) multiple-subgroup level, which considers the probability of one or more rule violations throughout process monitoring. Single-subgroup performance measures for X-bar charts that employ four rules are formulated. These measures are exact expressions of operational characteristics, except for the numerical approximation to the integral of the normal distribution. Applications of these models to simulated data demonstrate their accuracy in predicting chart performance. In addition, a diagnostic methodology is described which utilizes the derived performance measures to predict the mean of a shifted distribution. The proposed diagnostic procedure is illustrated in validation and application examples.

Application of Photoelectric Sensor in Vehicle Power Control System

2020 ◽  
Vol 15 (6) ◽  
pp. 700-706
Author(s):  
Yifan Zhao ◽  
Mengyu Wang ◽  
Kai Wang
Keyword(s):  
Power Control ◽  
Electric Energy ◽  
Least Square Method ◽  
Least Square ◽  
Motor Speed ◽  
Time Calculation ◽  
The Mean ◽  
The Difference ◽  
Artificial Neural Network Ann ◽  
Mean Square Errors

Due to its characteristics of using clean electric energy and bringing no damage to the environment, electric vehicles (EVs) have become a new developmental direction for the automotive industry. Its reliability issues have also attracted the attention of experts and professionals. In the field of automotive power control, from the perspective of motor control, this study uses the photoelectric sensors (PSs) as the research objects and elaborates on the measurement principles of motor speed with PSs. Meanwhile, a diagnosis scheme is proposed for various faults in the measurement. Among them, the measurement speed is converted by the photoelectric signal, and the measured waveform is amplified. In the fault detection process, the Radial Basis Function (RBF) artificial neural network (ANN) is analyzed. By using this method, the difference in the motor speed detected by the sensor is calculated to determine the cause of the failure. The test uses the least-square method to compare the tested motor speed with the actual motor speed. The results show that PSs can measure the motor speed of EVs. As for the motor failures, the mean square errors (MSEs) of motor speeds generated by different faults are compared to determine the fault points according to the speed changes. In addition, the cause of motor failure can be determined by the real-time calculation of the speed differences. The above tests fully prove the effectiveness of measuring the speed of electric motors by PSs; therefore, PSs have broad application prospects in vehicle power control systems.

scholarly journals Economic Design of EWMA Control Charts with Variable Sampling Intervals for Monitoring the Mean and Standard Deviation under Preventive Maintenance and Taguchi’s Loss Functions

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Li Xue ◽  
Zhen He
Keyword(s):  
Standard Deviation ◽  
Control Chart ◽  
Economic Model ◽  
Preventive Maintenance ◽  
Control Charts ◽  
Loss Functions ◽  
Variable Sampling ◽  
Sampling Intervals ◽  
Optimal Values ◽  
The Mean

The control chart and the maintenance management need to control process quality and reduce out-of-control cost. They are two key tools in the production process; however, they have usually been analyzed separately in the literature. Moreover, the existing studies integrating these two concepts suffer from three significant drawbacks as follows: (1) using control charts with fixed parameters to monitor the process, so that the small and middle shifts are detected slowly; (2) monitoring the mean and standard deviation separately, whereas, in real condition, the mean and standard deviation should be monitored simultaneously; (3) quality loss function is not usually used to design economic model, which leads to a large social quality loss in the monitoring process of control chart. To eliminate these weaknesses, the economic design of the exponential weighted moving average (EWMA) control chart with variable sampling intervals (VSI) for monitoring the mean and standard deviation under preventive maintenance and Taguchi’s loss functions is proposed. The optimal values of the parameters are determined to minimize the loss-per-item in an average cycle process. In addition, a genetic algorithm is used in a numerical example to search for the optimal values of the parameters. According to the sensitivity analysis, the effect of the model parameters on the solution of the economic model is obtained. Finally, the comparison study shows that the VSI EWMA control charts designed by the joint economic model are expected to reduce loss.

scholarly journals SAMPLE STANDARD DEVIATION(s) CHART UNDER THE ASSUMPTION OF MODERATENESS AND ITS PERFORMANCE ANALYSIS

2017 ◽  
Vol 5 (6) ◽  
pp. 368-377
Author(s):  
Kalpesh S. Tailor
Keyword(s):  
Standard Deviation ◽  
Performance Analysis ◽  
Normal Distribution ◽  
Control Chart ◽  
Control Charts ◽  
Curve Analysis ◽  
Mean Deviation ◽  
Sample Standard Deviation ◽  
Underlying Distribution ◽  
Control Limits

Moderate distribution proposed by Naik V.D and Desai J.M., is a sound alternative of normal distribution, which has mean and mean deviation as pivotal parameters and which has properties similar to normal distribution. Mean deviation (δ) is a very good alternative of standard deviation (σ) as mean deviation is considered to be the most intuitively and rationally defined measure of dispersion. This fact can be very useful in the field of quality control to construct the control limits of the control charts. On the basis of this fact Naik V.D. and Tailor K.S. have proposed 3δ control limits. In 3δ control limits, the upper and lower control limits are set at 3δ distance from the central line where δ is the mean deviation of sampling distribution of the statistic being used for constructing the control chart. In this paper assuming that the underlying distribution of the variable of interest follows moderate distribution proposed by Naik V.D and Desai J.M, 3δ control limits of sample standard deviation(s) chart are derived. Also the performance analysis of the control chart is carried out with the help of OC curve analysis and ARL curve analysis.

The Research on the Methods of the Aero Engine Blades Evaluation

2013 ◽  
Vol 333-335 ◽  
pp. 322-326
Author(s):  
Wen Qi Ma ◽  
Shu Gui Liu
Keyword(s):  
Engine Performance ◽  
Least Square Method ◽  
Chord Length ◽  
Least Square ◽  
Trailing Edge ◽  
Inspection Method ◽  
Maximum Thickness ◽  
Spline Fitting ◽  
Aero Engine ◽  
The Mean

As an important part of the aero engine, the quality of the blade seriously affects the engine performance, so the inspection method of the blade is significant. Based on the research of the HB 5647-98<<to mark dimensions, tolerances of the vane type and the surface roughness of the blade body>> , this paper concludes different evaluation methods of the blade. The main evaluated parameters include the leading and trailing edge radius, the chord length, the maximum thickness of blade profile, the mean camber line, and the surface twist and so on. Here we mainly discuss the previous three terms. The least square method is adopted to fit the arc of the leading and trailing edge; introduce the projection method to calculate the chord length; at last, we employ the spline fitting method to get the mean line and then obtain the maximum thickness of the blade section.

scholarly journals Monitoring bivariate process

2009 ◽  
Vol 29 (3) ◽  
pp. 547-562 ◽  
Author(s):  
Marcela A. G. Machado ◽  
Antonio F. B. Costa ◽  
Fernando A. E. Claro
Keyword(s):  
Covariance Matrix ◽  
Control Charts ◽  
Joint Control ◽  
Multivariate Processes ◽  
Generalized Variance ◽  
Main Drawback ◽  
The Mean ◽  
Sample Variances ◽  
Mean Vector

The T² chart and the generalized variance |S| chart are the usual tools for monitoring the mean vector and the covariance matrix of multivariate processes. The main drawback of these charts is the difficulty to obtain and to interpret the values of their monitoring statistics. In this paper, we study control charts for monitoring bivariate processes that only requires the computation of sample means (the ZMAX chart) for monitoring the mean vector, sample variances (the VMAX chart) for monitoring the covariance matrix, or both sample means and sample variances (the MCMAX chart) in the case of the joint control of the mean vector and the covariance matrix.

scholarly journals A regression approach for prediction of Youtube views

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Lau Tian Rui ◽  
Zehan Afizah Afif ◽  
R. D. Rohmat Saedudin ◽  
Aida Mustapha ◽  
Nazim Razali
Keyword(s):  
Least Square Method ◽  
Absolute Error ◽  
Descent Method ◽  
Least Square ◽  
Gradient Descent Method ◽  
Ordinary Least Square ◽  
The Public ◽  
Dependent Variables ◽  
Regression Approach ◽  
The Mean

YouTube has grown to be the number one video streaming platform on Internet and home to millions of content creator around the globe. Predicting the potential amount of YouTube views has proven to be extremely important for helping content creator to understand what type of videos the audience prefers to watch. In this paper, we will be introducing two types of regression models for predicting the total number of views a YouTube video can get based on the statistic that are available to our disposal. The dataset we will be using are released by YouTube to the public. The accuracy of both models are then compared by evaluating the mean absolute error and relative absolute error taken from the result of our experiment. The results showed that Ordinary Least Square method is more capable as compared to the Online Gradient Descent Method in providing a more accurate output because the algorithm allows us to find a gradient that is close as possible to the dependent variables despite having an only above average prediction.

scholarly journals Construction of Fuzzy Mean using Standard Deviation ( X  S  ) Control Chart with Process Capability

2019 ◽  
Vol 8 (4) ◽  
pp. 5390-5396
Keyword(s):  
Quality Control ◽  
Standard Deviation ◽  
Set Theory ◽  
Control Chart ◽  
Control Charts ◽  
Total Quality ◽  
Statistical Process ◽  
Research Article ◽  
Fuzzy Mean ◽  
Control Limits

The Quality has established over a number of points such as inspection, quality control, quality assurance, and total quality control and the effects produced by the above phases are used to check and develop the production/service procedure. Statistical process control (SPC) is a powerful collection of problem solving tools valuable in attaining process steadiness and enlightening capability through the decline of variability. Fuzzy set theory is a utilitarian tool to succeed the uncertainty environmental circumstances and the Fuzzy control limits provide a more accurate and flexible rating than the traditional control charts. The purpose of this research article is to construct the fuzzy mean using standard deviation ( X S   ) control chart with the assistance of process capabilityThe Quality has established over a number of points such as inspection, quality control, quality assurance, and total quality control and the effects produced by the above phases are used to check and develop the production/service procedure. Statistical process control (SPC) is a powerful collection of problem solving tools valuable in attaining process steadiness and enlightening capability through the decline of variability. Fuzzy set theory is a utilitarian tool to succeed the uncertainty environmental circumstances and the Fuzzy control limits provide a more accurate and flexible rating than the traditional control charts. The purpose of this research article is to construct the fuzzy mean using standard deviation ( X S   ) control chart with the assistance of process capability

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