Process data visualization

Designing and building of the IoT-Ticket Dashboards for process History Data takes similar steps as for real-time process monitoring described earlier. Thus, following chapter takes into consideration only the details exclusive for History Data Dashboards and visualization.

For the reason of the the IoT-Ticket Data Server structure, few design rules must be applied when storing the data. A new device, ProcesssData was formed to hold the data for finished processes. According device is used for making the separation over the

ProcessMonitor device serving as real-time monitoring variables. The understandable difference welling from the structure of sorting the two distinct data and method pur-poses. Inside the ProcessData device data is structured under the two different process-es, CMT and COAXwire, respectively acting as IoT-Ticket paths. Basic information of the finished processes is further stored under each process BuildplatfromID path. Every new finished process is given a BuildplatfromID, formed similarly as database forms buildplatform primary key and table. These ID’s are turned as datanodes holding the according information. Each questioned process path holds the datanodes for all the gathered data. Same datanode holds the data for each of the processes. It would have been conveniently to produce a new datanode for each gathered data record after the each finished process. Furthermore, the user could have visualized these datanodes ac-cordingly. Unfortunately, IoT-Ticket does not hold a datatag selector widget with a tree structure option, accessible in finished Dashboard. Without a tree structure visualiza-tion, user would be forced to go through all the datanodes when searching the right pro-cess in question. Possible update is been revised, yet the option is not present at the cur-rent moment. Final History Data storing architecture is illustrated in the Figure 34.

Figure 34. IoT-Ticket datanode architecture for process History Data storing From the production Supervisory monitoring page (Figure 24), a button element is found for shifting into process History Data visualization. After reaching the button, initial page for the user is the main History Data visualization Dashboard. This page holds a summary of the finished processes and button elements for accessing either CMT or COAXwire for more detailed visualization. Additionally, a dedicated button can be used for returning the Supervisory monitoring page. Regardless of the accessed process, the operations within the History Data visualization are similar. Only change takes place with the gathered data. For this reason following considers CMT process with more details.

Dashboards for finished processes History Data are composed of four different sections and two distinct Dashboards are provided for the user. First of these Dashboards is

illus-trated in the Figure 35. Figure inside black rectangle is the one visualized for the user.

Additionally some parts are highlighted for better viewing. On the upper section, there is a table for portraying the critical information over the finished processes. On the left column of the table, ID’s of the process correspond on the right column holding the de-tails. These details are represented in the Appendix C (first and last line of the process file).. Middle segment is used for making the selection over the variable data. User can access two buttons, one for resetting the datatags selection(s) and another for refreshing the selected datatags after the made selection(s). Selections for requested data are han-dled with dropdown menus. User can select maximum of two datatags with one Boole-an variable. Adding more data with one chart would make the chart unreadable. From and To date selectors are used for viewing specific time in the process. User first searches the desired process from the above finished process table and inserts the de-sired time values with date selectors. Lowest part of the Dashboard holds the line chart for representing the values of the data. Finally, on the right hand side a Navigation Pan-el is located. Green line above the button gives the information over the current sPan-elected Dashboard. Additionally, green color was selected to act as headline color within Histo-ry Data Dashboards. Manner, which gives user more briefly the information of the lo-cated functionality.

For the actual process, Figure 35 portrays a situation from the application tests where real-time monitoring revealed that some error occurred with CMT current value during the initial layers of the artifact. After the process was finished and data inserted into IoT-Ticket CMT current was studied. A drop of the current was indeed located and fur-ther examination was conducted view IoT-Ticket ‘zoom’ feature. CMT current was ob-served together with wire feeding velocity. Combination of these two unveiled that wire feeding was dropped near zero and moments later current was dropped to zero. Occur-rence corresponds with knowledge where current must be lowered if no wire is fed.

When counting the samples and knowing that data storing frequency was 100 Hz (10 ms) wire feed was at zero level for total of 260 ms. Occurred phenomenon did not re-veal at any way in the final artifact. Yet, example indicates the usage of the real-time monitoring together with History Data observation.

Figure 35. History data plain values visualization for CMT process

User has additional Dashboard for viewing minimum, maximum and average values of the datatags. Tracing of these records takes place with similar user interface as the case was with plain values visualization page. According Dashboard is portrayed in the Fig-ure 36. Conceivable variables (datatags) are now reduced in one. With more variables in the same graph would make the chart unreadable. Viewer selects the time range with date selectors and datatag with variable menu. Refresh button is accessed for tracing the chart. Illustrated graphs shows minimum and maximum values as marked area and av-erage values with plain line records. Questioned figure illustrates a situation where ap-plication is started and CMT current minimum and maximum values are fluctuating.

This is due to the both process itself and user altering the wire feeding velocity for gain-ing more solid attachment for the artifact to the base material (build platform). Durgain-ing this short period of application test value is stabilized. Similar observation can be gained from the average value; line representation. Average value is lowering to the level where stable process might be continued. Unfortunately for other reasons this pro-cess was halted.

Figure 36. History data average and minimum-maximum values for CMT