This paper describes statistical determination of fretting-induced failure of an electro-deposited coating. A fretting test is conducted using a ball-on-flat plate configuration. During a test, a frictional force is measured, along with the relative displacement between an AISI52100 ball and a coated flat specimen. Measured data are analyzed with statistical process control tools; a frictional ...

In manufacturing industries, development of measurement leads to increase the number of monitoring variables and eventually the importance of multivariate control comes to the fore. Statistical process control (SPC) is one of the most widely used as multivariate control chart. Nevertheless, SPC is restricted to apply in processes because its assumption of data as following specific distribution...

Statistical process control (SPC) requires statistical methodologies that detect changes in the pattern of data over time. The common methodologies, such as Shewhart, cumulative sum (cusum), and exponentially weighted moving average (EWMA) charting, require the in-control values of the process parameters, but these are rarely known accurately. Using estimated parameters, the run length behavior...

A control chart is one of the tools Statistical Process Control (SPC) used to monitor a production process. The charts ability detect data that crosses border often done using variable transformation. In this paper, we will introduce cumulative sum (CUSUM) based on Link Relative transformation technique regression approach. results showed with was more sensitive compared previous CUSUM and char...

This paper deals with the simultaneous statistical process control of several Poisson variables. The practitioner of this type of monitoring may employ a multiple scheme, i.e. one chart for controlling each variable, or may use a multivariate scheme, based on monitoring all the variables with a single control chart. If the user employs the multivariate schemes, he or she can choose from, for ex...

Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-norm...

A control chart is an important tool in statistical process monitoring that useful to monitor and improve production quality. In this article, attribute using repetitive sampling under a truncated life test proposed for the mean of product where lifetime follows Rayleigh distribution. The parameters limit coefficients are determined so in-control average run length (ARL) very close target ARL. ...