Evaluating measurement and process capabilities by GR&R with four quality measures Abbas Al-Refaie * , Nour Bata University of Jordan, Amman-Jordan University street, Amman 11942, Jordan article info Article history: Received 13 August 2009 Received in revised form 16 October 2009 Accepted 26 February 2010 Available online 4 March 2010 Keywords: GR&R study PTR SNR DR Process capability indices ANOVA abstract This paper proposes a procedure for assessing a measurement system and manufacturing process capabilities using Gage Repeatability and Reproducibility (GR&R) designed exper- iments with four quality measures. In this procedure, a GR&R study is conducted to obtain replicate measurements on units by several different operators. The gage and part variance components are then estimated by conducting analysis of variance (ANOVA) on the GR&R measurement observations. Finally, the acceptance and rejection criteria of the precision- to-tolerance ratio (PTR), signal-to-noise ratio (SNR), discrimination ratio (DR), and process capability index (C p or C pk ), are employed to assess the measurement and process capabil- ities. Three previously studied case studies are provided for illustration; in all of which the procedure provided efficient capability assessments at minimal computational and statis- tical efforts. In conclusion, the procedure proposed in this research using GR&R designed experiments provides valuable procedure and helpful guidelines to quality and production managers in assessing the capabilities of a measurement system and manufacturing pro- cess, and deciding the needed actions for improving performance. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Quality management efforts are often directed for zero defect production by reduction of variability. If a product is found nonconforming, it is usually claimed that the variability is attributed by process and thus improvement actions are implemented to enhance process capability. Unfortunately, such efforts may not necessarily result in improved process capability, because it is possible that the process is already capable enough, but there is no way of proving this due to inadequate measurement sys- tem. In addition, it may happen that the measurement sys- tem is already capable enough; however the measurement error is still unacceptable when compared to process vari- ability. Therefore, investigating both the variabilities of a measurement system and a manufacturing process is necessary before taking future improvement actions. Practically, a measurement system does not always pro- duce the exact dimension of the part, but it gives measure- ments that are deviated from the true value by some error. In any activity involving measurements, some of the ob- served variability will be due to variability in the product itself, r 2 p , whereas the rest will be due to the measurement error or gage variability, r 2 g . The variance of the total ob- served measurements can be expressed as [1] r 2 Total ¼ r 2 p þ r 2 g ð1Þ In many measurement system analysis studies, the gage is usually used to obtain replicate measurements on units by several different operators. Hence, two components of r 2 g are frequently generated, including the repeatability and reproducibility. Repeatability, r 2 Repeatability , represents the variation due to the gage itself when one operator uses the same gage to measure an identical quality characteris- tic of the same unit. Whereas, reproducibility, r 2 Reproducibility , reflects the variation caused by different operators using 0263-2241/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.measurement.2010.02.016 * Corresponding author. E-mail address: abbas.alrefai@ju.edu.jo (A. Al-Refaie). Measurement 43 (2010) 842–851 Contents lists available at ScienceDirect Measurement journal homepage: www.elsevier.com/locate/measurement