## 4 Application of the Concepts: Design of an In-Line Measuring Machine
### Implementation of Connectivity
The information that is stored in each sheet is described in Table 1. This information is available for the engineering team in real-time. It is important to note that free cloud services such as Google's are invaluable while the system is under design. However, reliability and robustness cannot be expected from these services once the system is released for operation. For this reason, an account was created in a commercial cloud system. The same data that were uploaded to the free service were stored in the new account. To facilitate process monitoring, a dashboard was created to display process performance. In addition to the data traces, parameters such as Active Time and Machine Utilization are reported. Figure 12 shows the dashboard for a specific case. The ranges of measurements and stops are clearly visible. The user can establish the time span for which the analysis is requested. To calculate the utilization rate, some basic definitions were needed. The cycle time \(\Delta t\), defined as the time lapse between consecutive activations of the start button, is not a constant. A vector that contains \(N\) cycle times for a given period is first calculated, where \(t\) represents the clock time when the start button is pushed:  
\[\Delta t_{n}=t_{n+1}-t_{n} \tag{1}\]  
A second definition is an active time (\(\Delta T_{m}\)), which represents a particular instance of the cycle time in which it can be assumed that the machine is in use. To calculate this vector, a trimmed vector \(\Delta t_{n}\) is extracted out of the lapse vector \(\Delta t_{n}\) by removing all instances in which the lapse exceeds 100 s. After this, an instance of the active time vector is obtained whenever a lapse is smaller than 3 times the mean value of the trimmed vector. The resulting vector \(\Delta T_{m}\) contains \(M\) elements, where \(M\) < \(N\). Essentially:  
\[\Delta t_{n}\in\Delta t_{n}\big{|}\ \Delta t_{n}<100 \tag{2}\]  
\[\Delta T_{m}\in\Delta t_{n}\ \big{|}\ \Delta t_{n}<3\widehat{\Delta t_{n}} \tag{3}\]  
The utilization rate is then given by the total active time divided by the time under analysis as shown in Equation (4). \[U_{ac}=\frac{\sum_{m=1}^{M}\Delta T_{m}}{\sum_{n=1}^{N}\Delta t_{n}}\times 1 00\% \tag{4}\] \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**No of Sheet**} & \multirow{2}{*}{**Data Stored**} & \multicolumn{4}{c}{**Use**} \\ \cline{3-5}  & & **Asses Part Quality** & **Process Monitoring** & **Diagnostics/Forecast** \\ \hline \multirow{4}{*}{1} & Calculated values of height data for 19 & & & \\  & measurement points. Environment & & & \\  & data from XDK (taken & x & & x \\  & during measurement) & & & \\  & Environmental data from XDK when & & & \\
2 & clamps are activated (taken before & & x & x \\  & measuring cycle) & & & \\
3 & Laser measurement raw data. & & & \\  & 19 points & x & & \\
4 & Height of locating points. 3 values. & x & x & x \\
5 & Maximum accelerations of axis X & & x & x \\
6 & Maximum accelerations of axis Y & & x & x \\
7 & Results of R\&R Gage & & & x \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Description of contents of Google spreadsheet. Signals that are transferred to the Cloud, as well as their intended use. where  
\(\Delta t_{n}=\) nth element of the lapse vector  
\(\Delta T_{m}=\) mth element of the Active time vector  
\(\Delta\overline{tr}_{n}=\) mean of the trimmed lapse vector  
\(\sum\Delta t_{n}=\) Total observation time  
\(\sum\Delta T_{m}=\) Total active time  
\(U_{ac}=\) Utilization rate  
\(M=\) size of the trimmed vector  
\(N=\) size of vector containing the measurement cycles for selected time lapse