Previously, it has been held that statistical process control (SPC) and engineering process control (EPC) were two distinct domains for process improvement. However, we design four control policies to integrate the two approaches using a proportional-integral-derivative (PID) feedback controller and Shewhart or moving centerline exponentially weighted moving average (MCEWMA) charts. We specific...

One-class classification problems have attracted a great deal of attention from various disciplines. In the present study, we attempt to extend the scope of application of the one-class classification technique to statistical process control (SPC) problems. We propose new multivariate control charts that apply the effectiveness of one-class classification to improvement of Phase I and Phase II ...

This paper proposes a novel approach that has the potential to hasten the eradication of gender disparities in employment. This approach relies upon the concept of statistical process control (SPC) to more systematically remedy disparate employment outcomes for women. SPC also serves as a new vehicle for conceptualizing the influence of industry on equal employment opportunity (EEO) outcomes. U...

As a provider of public transportation services in the Philadelphia area, the Southeastern Pennsylvania Transportation Authority operates and maintains a large number of transit vehicles for daily use. In an attempt to improve service quality and reduce costs, the Southeastern Pennsylvania Transportation Authority underwent a program to train staff on the use of Statistical Process Control to t...

Univariate and multivariate statistical process control (USPC and MSPC) methods have been widely used in process industries for fault detection. However, their practicability and achievable performance are limited due to the assumptions that a process is operated in a steady state and that variables are normally distributed. In the present work, external analysis is proposed to distinguish from...

the classical method of process capability analysis necessarily assumes that collected data are independent; nonetheless, some processes such as biological and chemical processes are autocorrelated and violate the independency assumption. many processes exhibit a certain degree of correlation and can be treated by autoregressive models among which the autoregressive model of order one (ar (1)) ...

Abstract—Different terms of the Statistical Process Control (SPC) has sketch in the fuzzy environment. However, Measurement System Analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through ...

Presentation There are several statistical process control (SPC) methods used in industry that can be applied in healthcare. However, as noted in the earlier discussion by Toulany et al. regarding quasi-experimental designs for quality improvement research, several considerations must be taken into account when adapting these methods for the complex, high-risk healthcare arena. Industrial metho...

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...