Use of risk adjusted control charts for monitoring patients’ surgical outcomes is now popular.These charts are developed based on considering the patient’s pre-operation risks. Change point detection is a crucial problem in statistical process control (SPC).It helpsthe managers toanalyzeroot causes of out-of-control conditions more effectively. Since the control chart signals do not necessarily...

Statistical process control is a method of monitoring product in its development process using statistical techniques with the presumption that the products produced under identical process condition shall not always be alike with respect to some quality characteristic(s). However, if the observed variations are with in the tolerable limits statistical process control (SPC) methods would pass t...

Statistical Quality Control (SQC) is a branch of Total Quality Management (TQM) that defines a quality philosophy and set the guiding principles that represent the foundation for a continuously improving organisation. Statistical Process Control (SPC) and Acceptance Sampling are the two major parts of SQC. SPC is an effective tool that aims to get and keep processes under control and ensure tha...

Control charts are standard statistical process control (SPC) tools for detecting assignable causes. These charts trigger a signal when a process gets out of control but they do not indicate when the process change has begun. Identifying the real time of the change in the process, called the change point, is very important for eliminating the source(s) of the change. Knowing when a process has ...

BACKGROUND This study seeks to increase clinical operational efficiency and accelerator beam consistency by retrospectively investigating the application of statistical process control (SPC) to linear accelerator beam steering parameters to determine the utility of such a methodology in detecting changes prior to equipment failure (interlocks actuated). METHODS Steering coil currents (SCC) fo...

Statistical process control (SPC) charts have previously been advocated for infection control quality improvement. To determine their effectiveness, a multicentre randomised controlled trial was undertaken to explore whether monthly SPC feedback from infection control nurses (ICNs) to healthcare workers of ward-acquired meticillin-resistant Staphylococcus aureus (WA-MRSA) colonisation or infect...

Theoretical scheduling has reached a mature state but there are difficulties in using the theory in practice. One of the issues is the occurrence of disturbances. Studies have been done to investigate the possibility of using control chart techniques to detect disturbances in production planning and scheduling. Appropriate control chart techniques have been developed that avoid statistical prob...

In this paper, an attempt has been made to implement the some statistical process control (SPC) techniques in the industry that is offering its customers the widest and latest range of sealing solutions for various applications in the automotive industry. The power of SPC lies in the ability to examine a process and the sources of variation in that process, using tools that give weightage to ob...

Control limits in traditional Multivariate Quality Control Charts (MQCC), such as Hotelling's T control chart, Multivariate Cumulative Sum (MCUSUM) and Multivariate Exponentially-Weighted Moving Average (MEWMA) control charts are based on multivariate normal assumption. This assumption is not usually satisfied, especially in real life applications. The purpose of a control chart based on suppor...

This paper illustrates how Phase I estimators in statistical process control (SPC) can affect the performance of Phase II control charts. The deleterious impact of poor Phase I estimators on the performance of Phase II control charts is illustrated in the context of profile monitoring. Two types of Phase I estimators are discussed. One approach uses functional cluster analysis to initially dist...