scholarly journals THE CLASSIFICATION AND CHARACTERISTICS OF CONTROL CHARTS

2017 ◽  
Vol 5 ◽  
pp. 86-93
Author(s):  
Izabela Dagmara Czabak-Górska
Keyword(s):  
Mass Production ◽  
Manufacturing Process ◽  
Control Charts ◽  
Empirical Distribution ◽  
Traditional Approach ◽  
Measurement Data ◽  
Basic Tool ◽  
Dominant Type ◽  
Advanced Control ◽  
New Literature

Control Charts are the basic tool for quality control. They were developed in the 1920s when the dominant type of production was mass production. In order to properly use classic Control Charts, the data from the manufacturing process should meet the following assumptions: an empirical distribution of measurement data should be normally distributed or close to a normal distribution, measurement data should be independent, the manufacturing process should be capable of quality depending on the type of Control Chart, a sample that is large enough (sometimes made of several elements) must be taken. Currently, a shift can be observed from mass production towards short production runs, which causes the proper use of the traditional approach to be impossible. In recent years, control charts are once again in the spotlight, and consequently many scientists, i.e. Reynolds, Zimmer, Costa, Calvin and Chan have undertaken the task to adapt the classic idea of keeping Control Charts to modern conditions of production. The development of science in this area allows for the avoidance of making major mistakes in the conduct of Control Charts and for making the wrong decisions based on erroneous analysis. However, the appearance of new literature pieces implies the need to classify Control Charts, therefore, this article describes the idea of conduct, the most important assumptions and distribution of classical Shewhart's Control Charts, as well as a suggestion for the distribution of advanced Control Charts that meet the needs of the currently used production types. The work also contains a concise description of the chosen control charts as well as the threats resulting from their inappropriate selection. This elaboration is an extension to the article of Czabak-Górska (2017).

Process Mean Shift Detection Using Prediction Error Analysis

1998 ◽  
Vol 120 (3) ◽  
pp. 489-495 ◽  
Author(s):  
S. J. Hu ◽  
Y. G. Liu
Keyword(s):  
Error Analysis ◽  
Prediction Error ◽  
Control Charts ◽  
Mean Shift ◽  
Measurement Data ◽  
Step Function ◽  
False Alarms ◽  
Prediction Errors ◽  
Function Type ◽  
Shift Detection

Autocorrelation in 100 percent measurement data results in false alarms when the traditional control charts, such as X and R charts, are applied in process monitoring. A popular approach proposed in the literature is based on prediction error analysis (PEA), i.e., using time series models to remove the autocorrelation, and then applying the control charts to the residuals, or prediction errors. This paper uses a step function type mean shift as an example to investigate the effect of prediction error analysis on the speed of mean shift detection. The use of PEA results in two changes in the 100 percent measurement data: (1) change in the variance, and (2) change in the magnitude of the mean shift. Both changes affect the speed of mean shift detection. These effects are model parameter dependent and are obtained quantitatively for AR(1) and ARMA(2,1) models. Simulations and examples from automobile body assembly processes are used to demonstrate these effects. It is shown that depending on the parameters of the AMRA models, the speed of detection could be increased or decreased significantly.

BiNem® manufacturing process for mass production

2003 ◽  
Vol 11 (3) ◽  
pp. 533 ◽  
Author(s):  
Jacques Angelé ◽  
Alain Boissier ◽  
Sylvain Lallemant ◽  
François Leblanc ◽  
Bertrand Pécout ◽  
...  
Keyword(s):  
Mass Production ◽  
Manufacturing Process

High-Speed Wired Drill Pipe and its Corresponding Manufacture & Test Technology Research

2021 ◽  
Author(s):  
Haochen Han ◽  
Yong Zhang ◽  
Jia Chen ◽  
Qi Sun ◽  
Zhimeng Fang ◽  
...  
Keyword(s):  
Mass Production ◽  
Manufacturing Process ◽  
High Speed ◽  
Transmission Rate ◽  
Drill Pipe ◽  
Pass Rate ◽  
Series System ◽  
Validation Test ◽  
Test Technology ◽  
Drill Pipes

Abstract High-speed wired drill pipe and its corresponding communication technology not only can achieve high-speed transmission rate and high-capacity, but also can realize real-time monitoring and dual-way communication in whole section, which can prevent downhole problems effectively. As a series system, the homogeneity and robustness of these wired drill pipes are crucial. This paper focuses on how to overcome the difficulty in manufacturing process of information drill pipe and complete the validation test. In order to guarantee the quality of information drill pipe and satisfy the technological requirements of mass production, we optimize the manufacturing process and put forward reasonable test techniques. The optimizations of manufacturing process include the analysis on constant tension of pressure pipe, quantitative cutting pipe and perforation in pipe nozzle. The testing techniques includes magnetic coupling coil impedance test, high pressure test, communication performance test of both single pipe and series system. The test result can be judged and evaluated by the attenuation value of the signal attenuation test and the signal reflection waveform as well as sealing reliability. With the help of the optimization of the manufacturing process and the application of new tooling, the quality and robustness of information drill pipe is improved obviously. Pass rate in primary assembly is increased from 70% to 92%. After the second assembly, pass rate can be increased to 99.5%. Besides, the work efficiency is greatly improved and the process requirements of mass production are satisfied. The validation test can screen out the drill pipe with poor quality and performance effectively thus to improve the reliability of the whole system. By means of the improvement of manufacturing and the validation test, the comprehensive pass rate of information drill pipes is increased from 84% to 95%. During three field tests in Jilin and Daqing Oilfield, the information drill pipes functioned well and accomplished all the test tasks successfully. High-speed wired drill pipe can improve the downhole data transmission on a large margin. The theorical transmission rate can be up to 100 kbps, 10,000 times as much as the traditional mud impulse telemetry. The manufacturing optimization and test technology can guarantee the performance and realize downhole data highway.

Measurement System Analysis Combined with Shewhart’s Approach

2015 ◽  
Vol 637 ◽  
pp. 7-11 ◽  
Author(s):  
Magdalena Diering ◽  
Adam Hamrol ◽  
Agnieszka Kujawińska
Keyword(s):  
Process Control ◽  
Control Chart ◽  
Measurement System ◽  
Manufacturing Process ◽  
Control Charts ◽  
System Analysis ◽  
Standard Procedure ◽  
Reference Value ◽  
Measurement Systems ◽  
On Line

The paper presents new procedure of methodology for statistical assessment of measurement systems variation (methodology known in the literature as Measurement Systems Analysis, MSA). This procedure allows for calculation and monitoring in real time (that is on-line) of measurement system (MS) characteristics which determine its usability for manufacturing process control. The presented solution pointed out the gap in process control, which consists in lack of methods for monitoring measurement processes in the on-line way. Their key point consists of taking samples that are also needed for the process control chart for the needs of the MSA method. This means that the samples are taken directly from the production line and during the production process. The method is combined with the standard procedure of statistical process control (SPC) with the use of process control charts. It is based on two control charts. The first one is called AD-chart (Average Difference chart) and it allows to estimate the variation between the operators and stability of the monitored measurement system. The second control chart illustrates the %R&R index (Repeatability and Reproducibility) and allows to monitor the MS capability.The paper also presents authors’ proposal of guidelines about the reference value for the %R&R index calculation and assessment. Recommendations and guidelines for choosing the reference value are based on two criteria: information about sample and manufacturing process variation and the purpose of using MS (product or process control).

scholarly journals Control charts based on quantiles: New approaches

2020 ◽  
Vol 12 (2) ◽  
pp. 99-104
Author(s):  
Vesna Jevremovć ◽  
Atif Avdović
Keyword(s):  
Quality Control ◽  
Control Charts ◽  
Empirical Distribution Function ◽  
Empirical Distribution ◽  
Statistical Quality Control ◽  
P Value ◽  
Applied Statistics ◽  
Production Processes ◽  
New Ideas ◽  
Contemporary Development

Contemporary development of Statistical quality control includes researches on different control charts, which could be easily implemented in production processes due to facilities offered by computers. New control charts give more information about production processes than the conventional ones, that's why there is a lot of investigation in this area of applied statistics. In this paper, we shall explain some new ideas concerning the construction of control charts based on quantiles, empirical distribution function and p-value.

scholarly journals Comparison of short runs control chart and T2 Hotelling control chart for monitoring sunergy glass production process

2021 ◽  
Vol 2106 (1) ◽  
pp. 012019
Author(s):  
M Qori’atunnadyah ◽  
Wibawati ◽  
W M Udiatami ◽  
M Ahsan ◽  
H Khusna
Keyword(s):  
Production Process ◽  
Control Chart ◽  
Mass Production ◽  
Control Charts ◽  
Manufacturing Industry ◽  
Average Run Length ◽  
Glass Production ◽  
Short Run ◽  
Multivariate Control Chart ◽  
Multivariate Control

Abstract In recent years, the manufacturing industry has tended to reduce mass production and produce in small quantities, which is called “Short Run Production”. In such a situation, the course of the production process is short, usually, the number of productions is less than 50. Therefore, a control chart for the short run production process is required. This paper discusses the comparison between multivariate control chart for short run production (V control chart) and T2 Hotelling control chart applied to sunergy glass data. Furthermore, a simulation of Average Run Length (ARL) was carried out to determine the performance of the two control charts. The results obtained are that the production process has not been statistically controlled using either the V control chart or the T2 Hotelling control chart. The number of out-of-control on the control chart V using the the EWMA test is more than the T2 Hotelling control chart. Based on the ARL value, it shows that the V control chart is more sensitive than the T2 Hotelling control chart.

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