There can be included a variety of uncertainties in all measurement results whether we can perceive or not on the causes. These uncertainties may end up in lowering the reliability of measurement results and also deteriorate the level of quality. For the purpose, we tried to combine the strengths of measurement uncertainty and measurement system analysis together to present a practical flowchart so as to verify those potential variation factors in general measurement processes. As a case study, we did an experiment and gathered data on the length between two holes of an engine cylinder head which is a core part for vehicles with a coordinate measuring machine and estimated nine uncertainty factors of it. Consequently, it was identified that the four primary factors among the nine which were related to the measurement standard, random errors or spread of the repeat measurements, differences between the coefficients of thermal expansion and the environment especially had been the influence around the laboratory. Since it is impossible to analyze the equipment and appraisal variations respectively through the only measurement uncertainty, we have used the measurement system analysis following the flowchart. Showing the result of being just about 0.5 % lower for the appraisal variation, and the equipment variation occupied about 7% for the total Gage R&R. Through this research, we have come to a conclusion that much more detail analysis on variation factors can be possible to be identified in measurement processes by using the developed flowchart which is composed of measurement uncertainty and measurement system analysis. Therefore, we expect engineers who are involved in quality and measurements to utilize this developed method.

The purpose of this research is to initiate discussion to simplify existing tools and methods for managing projects which make project management a harder job to perform and a tougher task to handle. Additionally, summarizing the definitions of “project” that have been found from reviewing the relevant literature, it deliberates on revising the duties and responsibilities of project manager and proposes performance expectancy triangle explaining a relationship among accountability, responsibility and authority – the Tri-butes. It sheds light on several factors critical to the success of projects. Finally, we propose a function indicating that customer demands or desires greatly affect project complexity.

Smart phones have drastically changed the life of today’s competitive world. Smart phone application (App) developers are trying their best to meet the customer requirements in the most efficient way while considering all its attributes. However smart phone service quality has been given less consideration comparatively during the last few years. This paper proposes a measurement method for improving service quality of smart phone application. This method combines the service quality performance model and process capability index. The service quality performance model is used to identify service items that require improvement. Process capability index is used to prioritize these items for improvement. We collected data on satisfaction level of customers who have used application service. By the proposed method, we found five significant service items from three categories - execution, security and resilience and prioritized those items for improvement.

Companies strive for quality improvement and use process data obtained through measurement process to monitor and control the process. Measurement data contain variation due to error of operator and instrument. The total variation is sum of product variat

Companies strive for quality improvement and use process data obtained through measurement process to monitor and control the process. Measurement data contain variation due to error of operator and instrument. The total variation is sum of product variation and measurement variation. Gage R&R is for repeatability and reproducibility of measurement system. Gage R&R study is usually conducted to analyze the measurement process. In performing the gage R&R study, several parameters such as the appropriate number of operators (o), sample size of parts (p), and replicate (r) are used. In this paper we propose how to determine the optimal combination of number of operators (o), sample size of parts (p), and replicates (r) considering measurement time and cost by statistical method.

Traditional quality control for manufacturing or service sector is not suitable for the quality control of a project as the project is one-time task constrained by time, cost, and quality. To meet the internal and external customers’ requirements, quality

Previous researches have focused on the efficiency of project execution and the satisfaction of internal customers in view of the fact that a project is successful if any defects are not found in the short-term performance test of the project final outcom

The need for accurate yield prediction is increasing for estimating productivity and production costs to secure high revenues in the semiconductor industry. Corresponding to this end, we introduce new spatial modeling approaches for spatially clustered defects on an integrated circuit (IC) wafer map. We use spatial location of an IC chip on the wafer as a covariate on corresponding defects count listed in a wafer map. Analysis results indicate that yield prediction can be greatly improved by capturing spatial features of defects. Tyagi and Bayoumi's (1994) wafer map data are used to illustrate the procedure.

We developed the basic SPC software named as 100 ？ Quality Renovation Software in 1998 as a government project supported by the Small and Medium Industry Administration and the Korean Standards Association. In 2002, Ministry of Industry and Energy conducted a survey research on the current status of quality management in the domestic industries including manufacturing and service industries. Among about 1000 answered industries, 40.6% has been using this 100？ S/W for their quality improvement activities. In this paper, we present our ways to help small and medium sized industries improve quality by our user-friendly SPC software.

Cusum control chart are widely used in process with small shifts. Because of cusum control chart has reasonable detection capability for small shifts. But Cusum control chart has unreasonable detection capability for recurring cycles or quickly change of small shifts. In Shewhart control charts with recurring cycles or quickly change of small shifts, when a point falls outside Shewhart control limits, the process is out of control. But, if assignable causes occur in process and the points falls inside its control limits, process can be considered in-control. For this situations, Shewhart control charts are used zones method ( ex＞ A, B, C ... ). ( We say ‘runs rules’ ) This paper investigated cumulative sum control chart for this some situations.

We developed the software named as Management Quality Renovation Software in 2002 as a government project supported by the Korean Standards Association. In this paper, we present our ways to help small and medium sized industries improve quality by Management Quality Renovation software.