## 6 Discussion  
The diagrams presented in Figures 10 and 11 provide a clear representation of the hard connections and the data formats being used. They are particularly helpful for documentation. For the purposes of design, the diagrams can be used as the starting point for the design of Connectivity. Figure 14: Part measurement cycle time on shop floor conditions. Interval between times in which the start button is pressed in consecutive cycles. In principle, Connectivity allows the transfer of data from different sources to the Cloud. This in turn opens up new options for the purposes of monitoring, forecasting, and controlling operations on the shop floor. In certain instances, the information that can provide a glimpse to the health of the operation is relatively obvious. In other cases, experience will dictate what kind of information can be extracted out of the data. An example of the type of information that was anticipated as useful during the design stage is the knowledge that can be obtained from the time stamp associated with each entry into the cloud datasheet. These data can be used to monitor cycle times and machine uptime. A direct application of this concept was shown in Figure 14, which was used to analyze the time it takes operators to go from part to part. A target specification was to perform the measuring cycle in 20-25 s. This value was based on the time it takes for the current system.. On the shop floor, operators were able to get closer to the minimum value but did not quite reach the optimum. However, during interviews with the operators, this shortcoming was completely ignored as an area of opportunity. Basically, operators felt comfortable with the performance of the machine in this regard. This indicates that there are other factors that may play a more important role in the effectiveness of the measuring process, such as the time to fix the part, or casting process uptime. Another example of knowledge that can be extracted from the time stamp is machine utilization and uptime. The dashboard presented in Figure 12 illustrates this use. A simple glance at the data allows a supervisor to visualize the pace of production. However, automatic extraction of information from the data is not a straightforward task. Equations (1) through (4) were developed to make the pertinent calculations. While simple, the terminology had to be developed in such a way that the correct information is communicated. As in the case of the cycle time, this information is derived directly from the time saved in the sheets and its use was anticipated from the start of the development process. A potential use of this information is a better synchronization of this operation with other stations to optimize material flow, or monitoring of operator fatigue. Implementation would require the use of more sophisticated analysis techniques. For the most part, the data produced by ambient sensors and accelerometers require analysis before an application is developed. Figure 15a shows an interesting behavior of the positioning system. As the ambient temperature rises, the maximum acceleration reached by the system appears to increase too, which is consistent with experience. The temperature measurement is made inside the measurement volume of the machine, and the rise may be caused by a combination of the environment around the machine as well as the heat generated by the linear motors as they perform their duties. The behavior seems to indicate that as the environment increases its temperature, the machine can reach higher speeds. This would be consistent with the observation that as the shift progresses, cycle times are reduced, as shown in Figure 15b. The reduction in cycle time may be caused by the combination of factors such as a faster machine and operator improved dexterity as the process progresses. A safe recommendation is to try to maintain the machine running as consistently as possible to allow for it to reach its maximum speeds.