High variance observed in the measurement system can cause high process variation that can affect process capability badly. Therefore, measurement system analysis is closely related to process capability analysis. Generally, the evaluation for measurement system and process variance is performed separately in the industry. That is, the measurement system analysis is implemented before process monitoring, process capability and process performance analysis even though these analyses are closely related. This paper presents the effective concurrent evaluation procedure for measurement system analysis and process capability analysis using the table that contains Process Performance (Pp), Gage Repeatability & Reproducibility (%R&R) and Number of Distinct Categories (NDC). Furthermore, the long-term process capability index (Pp), which takes into account both gage variance and process variance, is used instead of the short-term process capability (Cp) considering only process variance. The long-term capability index can reflect well the relationship between the measurement system and process capability. The quality measurement and improvement guidelines by region scale are also described in detail. In conclusion, this research proposes the procedure that can execute the measurement system analysis and process capability analysis at the same time. The proposed procedure can contribute to reduction of the measurement staff’s effort and to improvement of accurate evaluation.

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.