Condition monitoring is the foundation of a condition based maintenance (CBM). To relate the information obtained from the condition monitoring to the actual state of the system, it is usually required a stochastic model. On the other hand, considering the interactions and similarities that exist between CBM and statistical process control (SPC), the integrated models for CBM and SPC have been ...

Background: The utility of statistical process control (SPC) methods has received growing interest in the healthcare community to help improve clinical and administrative processes. SPC charts are chronological graphs of process data that are used in many other industries to help understand, control, and improve processes and that, although based in statistical theory, are easy for practitioner...

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...

This paper describes a simulation environment, called Prosim, which permits a user to define components, subsystems, and their interconnections to analyse a statistical process control (SPC) system. The components and systems are defined and analysed interactively. A library of standard SPC objects containing models for the Xbar, range, exponential weighted moving average, pchart and other SPC ...

Cost and schedule measures are the most important support activities for the success of a project; it provides the basis for process improvement and project management. This paper reports practical experiences on using EVM (Earned Value Management) and SPC(Statistical Process Control) in cost/ schedule measure. The analysis of experience data indicates the distributions of CPI(Cost Performance ...

This paper deals with the eff ective application of SPC on the lengthwise tonsure rolled plates process on double side scissors. After explanation of the SPC fundamentals, goals and mistakes during the SPC implementation, the methodical framework for the eff ective SPC application is defi ned. In the next part of the paper the description of practical application of SPC and its analysis from th...

Due to the rapid change of technology along with advanced data-collection systems, the simultaneous monitoring of two or more quality characteristics (or variables) is necessary. Multivariate Statistical Process Control (SPC) charts are able to effectively detect process disturbances. However, when a disturbance in a multivariate process is triggered by a multivariate SPC chart, process personn...

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...

Conventional statistical process control (SPC) charts require the normality assumption on the process response distribution. In reality, this assumption is often invalid. In such cases, it has been well demonstrated in the literature that results from control charts using the normality assumption may not be reliable in the sense that their actual false alarm rates could be substantially larger ...