It is a very challenging task to develop effective process control methodologies for multi-operational manufacturing processes. Although Statistical Process Control (SPC) has been widely used as the primary method in the control of quality, it mainly serves as a change detection tool rather than a method to identify root causes of process changes. This paper proposes a systematic approach to ov...

Process monitoring and diagnosis have been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior and quality improvement. Although traditional statistical process control (SPC) tools are effective in simple manufacturing processes that generate a small volume of independent data, these tools are not capable of handling the large streams of mul...

Purpose: This article aims to present successful practices in the management of training processes based on virtual reality and augmented reality, namely a strategy for evaluating process with principle continuous improvement mind, monitoring its performance terms productivity waste levels. It is proposed apply Statistical Process Control (SPC) tools develop control charts individual events (i-...

Statistical Process Control (SPC) has long been used to monitor and control the performance of manufacturing processes. Its benefits in this arena are well known. By comparison, little attention has been paid to the use of quantitative tools for monitoring and controlling service processes, other than accounting data in financial reports and the use (and abuse) of numerical ratings in personnel...

Inventory control policies have been recognized as a contributory factor to the bullwhip effect and inventory instability. Previous studies have indicated that there is a trade-off between bullwhip effect and inventory performance where the bullwhip effect reduction might increase inventory instability. Therefore, there is a need for inventory control policies that can cope with supply chain dy...

The aim of the research is to control the quality of the pulp and the functional condition of the refiners using statistical process control (SPC) and fuzzy modelling techniques. The on-line measurements and the SPC parameters are combined with the Mamdani type fuzzy models. The models and the “indexes” are used for the optimisation and the fault diagnosis purposes in the industrial scale pulp ...

Statistical process control (SPC) is a method of monitoring, controlling, and improving a process through statistical analysis. An important SPC tool is the control chart, which can be used to detect changes in production processes, including animal production systems, with a statistical level of confidence. This paper introduces the philosophy and types of control charts, design and performanc...

Different statistical process control (SPC) approaches were proposed over the years for project management using earned value management/ earned schedule. A detailed examination of these approaches has led us to express a need for a unified framework in which to test and compare them. The main drivers for this need were the lack of a formal definition for a state of control, the unavailability ...