The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Xiaocong He - One of the best experts on this subject based on the ideXlab platform.
-
Coefficient of Variation and its application to strength prediction of self-piercing riveted joints
Scientific Research and Essays, 2011Co-Authors: Xiaocong HeAbstract:This study deals with an application of the method of the Coefficient of Variation in strength prediction of the self-piercing riveted joints. Defined as the ratio of the standard deviation to the mean, the Coefficient of Variation may be used in both the reliability-based design of self-piercing riveted joints and in the evaluation of existing products. In this study, the concept and definition of the Coefficient of Variation are stated. The procedure of the use of Coefficient of Variation for approximate calculations of tensile strength of the self-piercing riveted joints is presented and compared with the classical Taylor Expansion method. This is illustrated with a numerical example. Key words: Coefficient of Variation; self-piercing riveted joint; strength prediction; statistical parameter; approximate calculation.
-
An Approximate Method via Coefficient of Variation for Strength Prediction of Self-Piercing Riveted Joints
Applied Mechanics and Materials, 2010Co-Authors: Xiaocong HeAbstract:This study deals with an application of the method of the Coefficient of Variation in strength prediction of the self-piercing riveted joints. Defined as the ratio of the standard deviation to the mean, the Coefficient of Variation may be used in both the reliability-based design of self-piercing riveted joints and in the evaluation of existing products. In this study, the concept and definition of the Coefficient of Variation are stated. The procedure of the use of Coefficient of Variation for approximate calculations of strength of the self-piercing riveted joints is presented and compared with the classical Taylor expansion method. This is illustrated with a numerical example.
-
Coefficient of Variation and Its Application to Strength Prediction of Adhesively Bonded Joints
2009 International Conference on Measuring Technology and Mechatronics Automation, 2009Co-Authors: Xiaocong HeAbstract:This study deals with an application of the method of the Coefficient of Variation in strength prediction of structural adhesive joints. Defined as the ratio of the standard deviation to the mean, the Coefficient of Variation may be used in both the reliability-based design of adhesively bonded joints and in the evaluation of existing products. In this study, the concept and definition of the Coefficient of Variation are stated. The procedure of the use of Coefficient of Variation for approximate calculations of statistical parameters is then presented and compared with the classical Taylor expansion method. This is illustrated with a numerical example.
-
application of Coefficient of Variation in reliability based mechanical design and manufacture
Journal of Materials Processing Technology, 2001Co-Authors: Xiaocong He, S O OyadijiAbstract:Abstract This paper deals with an application of the method of Coefficient of Variation to the characteristic analysis of the statistical distributions of material properties, including ultimate strength or fatigue limit, failure rates and structural/material reliability. The Coefficient of Variation, which is defined as the ratio of the standard deviation to the mean, can be used in both the reliability-based design of mechanical systems or components and in the evaluation of an existing product. The complicated functional relationship may be transformed into simple form by using the concept of Coefficient of Variation. The concept simplifies greatly the calculation of statistical parameters and the results obtained are very close to those derived directly from the original functional relation. By determining the simplified relation between Coefficient of Variation and statistical parameters, one can analyze the characteristics of statistical distributions by means of Coefficient of Variation. By means of a numerical example, it is shown that the method of the Coefficient of Variation can give an identical result to that of the Taylor expansion method. However, the method of the Coefficient of Variation has the advantage that it is much simpler to use than the Taylor expansion method.
Giovanni Celano - One of the best experts on this subject based on the ideXlab platform.
-
a variable sampling interval shewhart control chart for monitoring the Coefficient of Variation in short production runs
International Journal of Production Research, 2017Co-Authors: Asma Amdouni, Philippe Castagliola, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation (CV) allows process monitoring to be performed when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few research papers have investigated the monitoring of the CV in a short production run context. This paper investigates the design and implementation of a Variable Sampling Interval Shewhart control chart to monitor the Coefficient of Variation in a short production run context. Formulas for the truncated average time to signal are derived and a performance comparison is carried out with a Fixed Sampling Rate Shewhart chart monitoring the CV. An example illustrates the use of this chart on real industrial data.
-
monitoring the Coefficient of Variation using a variable sample size control chart in short production runs
The International Journal of Advanced Manufacturing Technology, 2015Co-Authors: Asma Amdouni, Philippe Castagliola, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation (CV) is an effective approach to monitor a process when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few contributions have investigated the monitoring of the CV for short production runs. This paper proposes an adaptive Shewhart control chart implementing a variable sample size (VSS) strategy in order to monitor the Coefficient of Variation in a short production run context. Formulas for the truncated average run length are derived. Moreover, a comparison is performed with a Fixed Sampling Rate Shewhart chart for the CV in order to evaluate the performance of each chart in a short run context. An example illustrates the use of this chart on real data.
-
monitoring the Coefficient of Variation using a variable sample size control chart
The International Journal of Advanced Manufacturing Technology, 2015Co-Authors: Philippe Castagliola, Giovanni Celano, Hassen Taleb, Ali Achouri, Stelios PsarakisAbstract:This paper proposes an adaptive Shewhart control chart implementing a variable sample size strategy in order to monitor the Coefficient of Variation. The goals of this paper are as follows: (a) to propose an easy-to-use 3-parameter logarithmic transformation for the Coefficient of Variation in order to handle the variable sample size aspect; (b) to derive the formulas for computing the average run length, the standard deviation run length, and the average sample size and to evaluate the performance of the proposed chart based on these criteria; (c) to present ready-to-use tables with optimal chart parameters minimizing the out-of-control average run length as well as the out-of-control average sample size; and (d) to compare this chart with the fixed sampling rate, variable sampling interval, and synthetic control charts. An example illustrates the use of the variable sample size control chart on real data gathered from a casting process.
-
one sided shewhart type charts for monitoring the Coefficient of Variation in short production runs
Quality Technology and Quantitative Management, 2015Co-Authors: Philippe Castagliola, Asma Amdouni, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation is an effective approach to Statistical Process Control when the process mean and standard deviation are not constant but their ratio is constant. Until now, research has not investigated the monitoring of the Coefficient of Variation for short production runs. Viewed under this perspective, this paper proposes a new method to monitor the Coefficient of Variation for a finite horizon production by means of one-sided Shewhart-type charts. Tables are provided for the statistical properties of the proposed charts when the shift size is deterministic. Two illustrative examples are given in order to illustrate the use of these charts on real data.
-
monitoring the Coefficient of Variation using ewma charts
Journal of Quality Technology, 2011Co-Authors: Philippe Castagliola, Giovanni Celano, Stelios PsarakisAbstract:The Coefficient of Variation (CV) is a quality characteristic that has several applications in applied statistics and is receiving increasing attention in quality control. This paper suggests a new method to monitor the CV.
Philippe Castagliola - One of the best experts on this subject based on the ideXlab platform.
-
a variable sampling interval shewhart control chart for monitoring the Coefficient of Variation in short production runs
International Journal of Production Research, 2017Co-Authors: Asma Amdouni, Philippe Castagliola, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation (CV) allows process monitoring to be performed when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few research papers have investigated the monitoring of the CV in a short production run context. This paper investigates the design and implementation of a Variable Sampling Interval Shewhart control chart to monitor the Coefficient of Variation in a short production run context. Formulas for the truncated average time to signal are derived and a performance comparison is carried out with a Fixed Sampling Rate Shewhart chart monitoring the CV. An example illustrates the use of this chart on real industrial data.
-
monitoring the Coefficient of Variation using a variable sample size control chart in short production runs
The International Journal of Advanced Manufacturing Technology, 2015Co-Authors: Asma Amdouni, Philippe Castagliola, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation (CV) is an effective approach to monitor a process when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few contributions have investigated the monitoring of the CV for short production runs. This paper proposes an adaptive Shewhart control chart implementing a variable sample size (VSS) strategy in order to monitor the Coefficient of Variation in a short production run context. Formulas for the truncated average run length are derived. Moreover, a comparison is performed with a Fixed Sampling Rate Shewhart chart for the CV in order to evaluate the performance of each chart in a short run context. An example illustrates the use of this chart on real data.
-
monitoring the Coefficient of Variation using a variable sample size control chart
The International Journal of Advanced Manufacturing Technology, 2015Co-Authors: Philippe Castagliola, Giovanni Celano, Hassen Taleb, Ali Achouri, Stelios PsarakisAbstract:This paper proposes an adaptive Shewhart control chart implementing a variable sample size strategy in order to monitor the Coefficient of Variation. The goals of this paper are as follows: (a) to propose an easy-to-use 3-parameter logarithmic transformation for the Coefficient of Variation in order to handle the variable sample size aspect; (b) to derive the formulas for computing the average run length, the standard deviation run length, and the average sample size and to evaluate the performance of the proposed chart based on these criteria; (c) to present ready-to-use tables with optimal chart parameters minimizing the out-of-control average run length as well as the out-of-control average sample size; and (d) to compare this chart with the fixed sampling rate, variable sampling interval, and synthetic control charts. An example illustrates the use of the variable sample size control chart on real data gathered from a casting process.
-
one sided shewhart type charts for monitoring the Coefficient of Variation in short production runs
Quality Technology and Quantitative Management, 2015Co-Authors: Philippe Castagliola, Asma Amdouni, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation is an effective approach to Statistical Process Control when the process mean and standard deviation are not constant but their ratio is constant. Until now, research has not investigated the monitoring of the Coefficient of Variation for short production runs. Viewed under this perspective, this paper proposes a new method to monitor the Coefficient of Variation for a finite horizon production by means of one-sided Shewhart-type charts. Tables are provided for the statistical properties of the proposed charts when the shift size is deterministic. Two illustrative examples are given in order to illustrate the use of these charts on real data.
-
monitoring the Coefficient of Variation using ewma charts
Journal of Quality Technology, 2011Co-Authors: Philippe Castagliola, Giovanni Celano, Stelios PsarakisAbstract:The Coefficient of Variation (CV) is a quality characteristic that has several applications in applied statistics and is receiving increasing attention in quality control. This paper suggests a new method to monitor the CV.
Stelios Psarakis - One of the best experts on this subject based on the ideXlab platform.
-
monitoring the Coefficient of Variation using a variable sample size control chart
The International Journal of Advanced Manufacturing Technology, 2015Co-Authors: Philippe Castagliola, Giovanni Celano, Hassen Taleb, Ali Achouri, Stelios PsarakisAbstract:This paper proposes an adaptive Shewhart control chart implementing a variable sample size strategy in order to monitor the Coefficient of Variation. The goals of this paper are as follows: (a) to propose an easy-to-use 3-parameter logarithmic transformation for the Coefficient of Variation in order to handle the variable sample size aspect; (b) to derive the formulas for computing the average run length, the standard deviation run length, and the average sample size and to evaluate the performance of the proposed chart based on these criteria; (c) to present ready-to-use tables with optimal chart parameters minimizing the out-of-control average run length as well as the out-of-control average sample size; and (d) to compare this chart with the fixed sampling rate, variable sampling interval, and synthetic control charts. An example illustrates the use of the variable sample size control chart on real data gathered from a casting process.
-
monitoring the Coefficient of Variation using ewma charts
Journal of Quality Technology, 2011Co-Authors: Philippe Castagliola, Giovanni Celano, Stelios PsarakisAbstract:The Coefficient of Variation (CV) is a quality characteristic that has several applications in applied statistics and is receiving increasing attention in quality control. This paper suggests a new method to monitor the CV.
Asma Amdouni - One of the best experts on this subject based on the ideXlab platform.
-
a variable sampling interval shewhart control chart for monitoring the Coefficient of Variation in short production runs
International Journal of Production Research, 2017Co-Authors: Asma Amdouni, Philippe Castagliola, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation (CV) allows process monitoring to be performed when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few research papers have investigated the monitoring of the CV in a short production run context. This paper investigates the design and implementation of a Variable Sampling Interval Shewhart control chart to monitor the Coefficient of Variation in a short production run context. Formulas for the truncated average time to signal are derived and a performance comparison is carried out with a Fixed Sampling Rate Shewhart chart monitoring the CV. An example illustrates the use of this chart on real industrial data.
-
monitoring the Coefficient of Variation using a variable sample size control chart in short production runs
The International Journal of Advanced Manufacturing Technology, 2015Co-Authors: Asma Amdouni, Philippe Castagliola, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation (CV) is an effective approach to monitor a process when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few contributions have investigated the monitoring of the CV for short production runs. This paper proposes an adaptive Shewhart control chart implementing a variable sample size (VSS) strategy in order to monitor the Coefficient of Variation in a short production run context. Formulas for the truncated average run length are derived. Moreover, a comparison is performed with a Fixed Sampling Rate Shewhart chart for the CV in order to evaluate the performance of each chart in a short run context. An example illustrates the use of this chart on real data.
-
one sided shewhart type charts for monitoring the Coefficient of Variation in short production runs
Quality Technology and Quantitative Management, 2015Co-Authors: Philippe Castagliola, Asma Amdouni, Hassen Taleb, Giovanni CelanoAbstract:Monitoring the Coefficient of Variation is an effective approach to Statistical Process Control when the process mean and standard deviation are not constant but their ratio is constant. Until now, research has not investigated the monitoring of the Coefficient of Variation for short production runs. Viewed under this perspective, this paper proposes a new method to monitor the Coefficient of Variation for a finite horizon production by means of one-sided Shewhart-type charts. Tables are provided for the statistical properties of the proposed charts when the shift size is deterministic. Two illustrative examples are given in order to illustrate the use of these charts on real data.
