## 5 Assessment of Machine Performance  
Following the previous description, a prototype of the in-line measuring machine was built. This version of the machine was intended primarily for use in the laboratory, but it was also considered suitable for use in the plant for limited runs. The machine was deployed in a production line and was tested in relatively short runs, of around 400 parts or so, on multiple occasions over a period of 18 months. The system was used only for test purposes or as a redundant operation during this time. Figure 13 shows the prototype in different settings. This section presents an assessment of the system's performance, based on the characteristics that were described in Section 2. Figure 12: Dahsboard for monitoring machine utilization and operation times. Points correspond to measurements at a given time. The first target characteristics for an in-line measuring system are accuracy and repeatability. Part measurement immediately after manufacture is highly susceptible to shop conditions, particularly to variations of temperature [19]. Other important factors include operator skill and capacity of the measuring system. In this case, the target was to score better than 0.1 (10%) in a gauge repeatability and reproducibility (R&R) test for each of the points being measured. The prototype machine operates in one of two different modes: (workpiece) measurement and (R&R) test. The normal measurement mode is used when production is being monitored. In the test mode, a Gage R&R algorithm based on ANOVA technique implemented in the BBR is applied to check the process. A typical R&R test involves 10 different parts and 3 different operators. Each operator tests each part 3 times in a randomized manner (19 measurement points). Results of the measurements are analyzed to assess the repeatability (due mostly to machine performance) and reproducibility (due mainly to the operator's skill and training) of the measurement process. Appendix B presents some details of this algorithm. The Gage R&R study, environmental data, and acceleration registered by the 3-axis accelerometer are sent to the Cloud by the BBR. Table 2 shows the results of several tests performed in the lab prior to shipping to the plant, and subsequent trials on the shop floor. Tests were performed periodically per standard practices. In particular, given that the machine was used during specific intervals of production, a test had to be made after re-installation and before use in the production line. Figure 13: (**a**) Prototype of the machine in the laboratory, and (**b,c**) in use on the shop floor. The reported data shows that the system was capable of performing up to the standard required by the application (less than 10%). It is important to notice that tests on the shop floor included one more point for measurement than the lab tests. The engineering department requested this additional data for a feature that had raised concerns. The second design characteristic is speed. The initial target was to perform a measuring cycle from part mount to part dismount for 20 to 25 s. Vibration and shock affect the repeatability of the system. For this reason, experiments were made to establish how fast the system could move and still deliver an accurate measurement. In the end, a measuring cycle that consisted of five steps took the following times:  
* Part clamp and insertion into the workspace: 6 s.
* Measurement cycle: 9 s.
* Part extraction and unclamp: 5 s.
* Handling of the part to load and unload. In these cases, time varies depending on the operator's training. In the lab, the best times that could be achieved were around 28-29 s from part to part. On the other hand, operators in the field achieved as little as 22 s from part to part after gaining familiarity with the process. Figure 14 shows a histogram of part to part time for data reported in the last experimental campaign of the machine. The fastest times would correspond to parts that pass the test without problems.