Taylor & Francis

 Journal

 Double Exponentially Weighted Moving Average Control Chart With Supplementary Runs-rules

 Olatunde A. Adeoti & Jean-Claude Malela-Majika

 2019

Enhancing the sensitivity of control charts for detecting small process shift is desirable and may be done in different ways. In this paper, we propose the double exponentially weighted moving average (DEWMA) control chart using the 2-of-2 and 1-of-1 or 2-of-2 runs-rules schemes for monitoring process mean shifts. The performances of the resulting control schemes are investigated in terms of the average run-length (ARL), standard deviation of the run-length (SDRL) and selective percentiles of the run-length (PRL). In addition, the overall performance of the proposed runs-rules charts are examined and compared with those of the existing charts in terms of the ARL, average extra quadratic loss (AEQL), average ratio of the average run-length (ARARL) and performance comparison index (PCI) values. It is observed that the proposed control schemes are more efficient in many situations and improve the ability of the existing DEWMA schemes in detecting small, moderate and large mean shifts. 

 Taylor And Francis

 Journal

 Capability Index-based Control Chart For Monitoring Process Mean Using Repetitive Sampling

 Olatunde A. Adeoti And John O. Olaomi

 2018

A new process capability index (PCI) control chart for monitoring the process mean using repetitive sampling is presented. The design of the proposed control chart is based on an unbiased estimator ˆσ = . s c4 of the process standard deviation for a normally distributed quality characteristic. The formulae for the in-control and out-of-control average run length and the standard deviation of the run length (SDRL) are derived. Tables of in-control and out-of-control average run length (ARL) and SDRL for various shifts, δ are presented. The proposed control chart outperforms existing control chart in detecting relatively small process mean shifts in terms of ARLs and SDRLs. Numerical example is presented to demonstrate the application of the proposed chart.

 

 Emerald

 Journal

 A New Double Exponentially Weighted Moving Average Control Chart Using Repetitive Sampling

 Olatunde A. Adeoti

 2018

Purpose – The purpose of this paper is to propose a double exponentially weighted moving average control

chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the

efficiency of detecting small process mean shift.

Design/methodology/approach – The algorithm for the implementation of the proposed chart is developed

and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs

are presented for various process mean shift. The performance of the proposed chart is investigated in terms of

the average run-length for small process mean shift and compared with the existing DEWMA control chart.

Numerical examples are given as illustration of the design and implementation of the proposed chart.

Findings – The proposed control chart ismore efficient than the existing DEWMA control chart in the detection

of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift.

However, the performance of the proposed chart relatively deteriorates for large smoothing constants.

Practical implications – The application of repetitive sampling in the control chart literature is gaining

wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in

the detection of small process mean shift by process control personnel.

Originality/value – This paper fills a gap in the literature by examining the performance of the repetitive

sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in

the literature, however, its use based on the DEWMA statistic has not been considered in this context.

 

 South African Institute Of Industrial Engineering

 Journal

 PROCESS CAPABILITY INDEX-BASED CONTROL CHART FOR VARIABLES

 O.A. Adeoti And J.O. Olaomi

 2017

 This paper proposes a process capability index-based control chart for variables using the Downton estimator with a specified Cp value. The proposed chart is able to address the issue of control and capability simultaneously. We also provide a control chart constant to construct the process capability index-based control chart. A numerical example is presented to demonstrate the application of the proposed chart, and the effect of non-normality is discussed. The result shows that the proposed control chart performs better in monitoring and assessing processes, and eliminates the usual two-stage procedure reflected in the literature

 

 John Wiley & Sons, Ltd

 Journal

 Control Chart Limits For Monitoring Process Mean Based On Downton’s Estimator

 Olatunde A. Adeoti, John O. Olaomi And Kayode S. Adekeye

 2016

Control charts are important tools in statistical process control used to monitor shift in process mean and variance. This paper proposes a control chart for monitoring the process mean using the Downton estimator and provides table of constant factors for computing the control limits for sample size (n ≤ 10). The derived control limits for process mean were compared with control limits based on range statistic. The performance of the proposed control charts was evaluated using the average run length for normal and non-normal process situations. The obtained results showed that the XD control chart, using the Downton statistic, performed better than Shewhart Xbar chart using range statistic for detection of small shift in the process mean when the process is non-normal and compares favourably well with Shewhart Xbar chart that is normally distributed.

 

 Taylor And Francis

 Journal

 A Moving Average S Control Chart For Monitoring Process Variability

 Olatunde A. Adeoti And John. O. Olaomi

 2016

An efficient alternative to the S control chart for detecting shifts of small magnitude in the process variability using a moving average based on the sample standard deviation s statistic is proposed. Control limit factors are derived for the chart for different values of sample size and span w. The performance of the moving average S chart is compared to the S chart in terms of average run length. The result shows that the performance of moving average S chart for varying values of w outweigh those of the S chart for small and moderate shifts in process variability

 

 Scientific And Academic Publishing,

 Journal

 Application Of Cusum Control Chart For Monitoring HIV/AIDS Patients In Nigeria

 Olatunde A. Adeoti

 2013

 In this paper cumulative Sum (CUSUM) chart is applied to monitor increase (changes) in the number of HIV/AIDS incidences in Nigeria using the screening result of HIV/AIDS data in Oyo state. The designed scheme is apply to demonstrate the application of the chart and evaluate the performance of the chart in the non manufacturing area. From the evaluation, the chart has a good potential as a SPC tool for monitoring changes in the number of infectious diseases in Nigeria

 

 Foundation Of Computer Science (FCS)

 Journal

 Effect Of Training Algorithms On The Performance Of ANN For Pattern Recognition Of Bivariate Process

 Adeoti O.A And Osanaiye P.A

 2013

Artificial Neural Network (ANN) which is designed to mimic the human brain have been used in the literature for identifying variable(s) that is(are) responsible for out-of-control signal and the training algorithms have played a significant role in the identification of the aberrant variable(s). In this paper the effect of three algorithms in the training of ANN for pattern recognition of bivariate process is studied. Situations in which the algorithms performed satisfactorily with respect to recognition accuracy (in percentages), epochs and MSE were identified. The result of study shows that the Levenberg-Marquardt (trainlm) is the best algorithm for pattern recognition of bivariate manufacturing process in terms of recognition accuracy and the resilient backpropagation (trainrp) is best in terms of speed and mean square error performance 

  International Institute Of Science And Technology Education

 Journal

 Performance Analysis Of ANN On Dataset Allocations For Pattern Recognition Of Bivariate Process

 Adeoti O.A And Osanaiye P.A

 2012

Several approaches to identifying the out-of-control variables after the detection of abnormal pattern has been most intensively studied and used in practice. One of the several approaches is the Artificial Neural Network (ANN) based model for diagnosis of out-of-control signal of multivariate process mean shift. In spite of the number of years of research in neural network, limited research (if any) have been done on the effect of dataset allocations in percentages for training and testing on the performance of ANN. In this paper, we investigate the use of different percentages of dataset allocation into training, validation and testing on the performance of ANN in pattern recognition of bivariate process using six selected training algorithms. The result of study showed that large allocation of dataset for training was found suitable, having higher recognition accuracy for ANN learning and perform better for pattern recognition of bivariate process. 

 Faculty Of Science, University Of Ibadan

 Journal

 Monitoring The Composition Of Some Physico-chemical Properties Of Ground Water Using Hotelling’s T2 Chart

 Adeoti O.A And Ipeayeda A.R

 2010

The physico-chemical characteristics properties of groundwater has direct impact on the water quality index and determines if the water is fit for use or not. Monitoring the characteristics using separate univariate charts may produce misleading results as it does not take into consideration the correlation structure of these characteristics. Therefore, the multivariate control chart is used to monitor the characteristics of the samples and the sensitivity of detecting an out-of-control situation is achieved using the Hotelling multivariate control chart