Results 271 to 280 of about 484,445 (306)

Statistical design of an adaptive synthetic X¯$\bar{X}$ control chart for autocorrelated processes

Quality and Reliability Engineering International, 2022
This paper aims to design a variable parameters synthetic X¯$\bar{X}$ control chart for first‐order AR(1) autocorrelated data following a Gaussian process.
Carmen Quintero‐Arteaga, R. Peñabaena-Niebles, J. I. Vélez, Maria Jubiz-Diaz   +3 more
semanticscholar   +1 more source

Minimum-loss design of x-bar charts for correlated data

Journal of Loss Prevention in the Process Industries, 2002
Abstract When the x-bar chart is used to monitor a production process, three parameters should be determined: the sample size, the sampling interval between successive samples, and the control limits for the chart. In 1956, Duncan presented a cost model to determine the three parameters, which is called the economic design of x-bar charts.
Hui-Rong Liu, Chao-Yu Chou, Chung-Ho Chen   +2 more
openaire   +1 more source

Integrated optimization for X-bar control chart, preventive maintenance and production rate

Reliability Engineering & System Safety
Yaping Li, Zhen Chen, Tangbin Xia, Ershun Pan, Sifeng Liu   +4 more
openaire   +2 more sources

Two Approaches for Assessing the Operating Characteristic of X-Bar Chart Using Triplet Estimates

2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA)
Our focus is to develop a 9-point method to determine the OC of x-bar chart using triplet estimates of mean and standard deviation generated by considering the 100(1-α) % confidence interval of the respective parameters.
Boya Venkatesu, Gopal Kumar Gupta
semanticscholar   +1 more source

Combined X-bar and CRL Charts for the Gamma Process

Computational Statistics, 2003
A quality control problem for non-normally distributed observations is considered. For combined \(\bar x\) and CRL charts (the synthetic charts) control limits and performance are investigated in the case of (shifted) gamma distribution of the observations (with known parameters).
openaire   +1 more source

Economic design of x-bar control chart under hybrid maintenance policy

Journal of Quality in Maintenance Engineering, 2018
Purpose According to the relevance of product quality and machine degradation state, a hybrid maintenance policy is designed. The paper aims to discuss this issue. Design/methodology/approach Product quality control and machine maintenance are considered simultaneously in this policy.
Xiaomei Yang, Jianchao Zeng
openaire   +1 more source

Operating characteristics of X-bar charts with asymmetric control limits

IIE Transactions, 2001
When the assumptions behind the Shewhart chart are not met, policies other than the traditional 3-sigma limits may enable speedier and more economical detection of process change. If a process has unequal probabilities of downward and upward shifts, downward shifts of differing magnitude from upward shifts, and/or standard deviations after downward ...
openaire   +1 more source

Economic-Statistical Design of X-bar Control Charts Using Taguchi Loss Functions

IFAC Proceedings Volumes, 2009
Abstract Duncan is the pioneer to provide a control chart design from economic-view point in 1956 and ensure that the economic design of control charts is really lower the cost compared with a conventional Shewhart charts. An economic design does not consider the statistics properties, such as type I or type II error and average time to signal (ATS).
Fong-Jung Yu, Hsuan-Kai Chen
openaire   +1 more source

Enhanced Designs for the Multi‐Region Run Sum X¯${{\bar{X}}}$ Control Chart Based on the Median Run Length Metric

Quality and Reliability Engineering International
Extensive research has focused on the multi‐region run sum X¯$\bar{X}$ control chart, a sophisticated procedure for monitoring process mean shifts, particularly utilising the average run length (ARL) metric.
W.L. Teoh, J. W. Teoh, Kai Le Goh, Zhi Song, S. Saha   +4 more
semanticscholar   +1 more source

X-Bar Control Charts for Non-Normal Correlated Data Under Repetitive Sampling

Journal of Testing and Evaluation, 2016
Abstract A control chart for non-normal correlated data under repetitive sampling is presented in this manuscript. A Burr distribution is employed to model the non-normal distribution. The proposed control chart is based on two sets of control limits whose coefficients are determined by considering the in-control average run length.
Muhammad Aslam, Nasrullah Khan, Muhammad Azam   +2 more
openaire   +1 more source