This paper presents a statistical process control (SPC) chart for variables in a new feature for the paper machine in the paper industry. The traditional control charts like X-bar and R charts may be inadequate sometimes when the process exhibits abnormal situations which could lead to false decisions. When we are interested in detecting small shifts, Exponentially Weighted Moving average (EWMA) control chart provides the correct picture to make right decisions without affecting the process unnecessarily. This study is aimed at designing EWMA control chart in paper manufacturing process.

Nowadays, with the increasing number of projects in organizations, managers are enthusiastic about managing and controlling projects, and as projects become more complex and cause unforeseen risks, project management becomes even more critical. Using the earned value management method to control the current status of projects, and predicting the future status of projects has had many advantages. Representing the status of the project, and predicting the project performance by various indicators are some features of this method. As these indicators are deterministic, the risk of the prediction increases when the number of risks goes up in a project. Therefore, statistical methods can be employed to estimate the statistical distribution of risks and notably boost predicting accuracy. The purpose of this paper is to present a method for predicting project duration and cost of the project and selecting the best action plan. Control charts are used along with the earned value management method to increase accuracy. This model also provides the possibility of selecting the best action plan to improve project performance. Moreover, this method can be applied in each project phase separately. Finally, a case study is used to investigate the validity of the proposed method.

An important problem in control chart implementation is the availability of resources to collect and analyze data for control charts implementation. This paper proposes a method to prioritize and select final product parameters to control. The prioritization is based on cost of quality and technical criticality of those parameters. The prioritization method is demonstrated by a case study of flexible printed circuit manufacturing.

The popularity of Six Sigma, as a means for improving quality, has grown exponentially in recent years. It is a proven methodology to achieve breakthrough improvement in process performance that generates significant savings to bottom line of an organization. This paper illustrates how Six Sigma methodology may be used to improve service processes. The purpose of this paper is to develop Six Sigma DMAIC methodologies that would help service organizations look into their processes. In addition, it demonstrates the vital linkages between process improvement and process variation. The study identifies critical process parameters and suggests a team structure for Six Sigma project in service operations.