# Machine Learning-Supported Designing of Human-Machine Interfaces
## 3 Application of the Method on a Real-World Industrial System
### Discussion  
The study has shown that the method is useful in alarm management and in the optimisation of industrial control systems. Its applicability can be broadened, but some limitations must be considered.  
One potential issue can arise if one event is allocated to more displays. In this case, a decision has to be made regarding whether the display cluster will be a union of the touched displays, or the event is paired with only one display. Theoretically, an analysis could be performed to determine the display in which the interactions are made with the event the most frequently. In practise, the log file barely indicates this information. One solution is to create \"union\" displays, which is not an ideal solution; this \"error\" must be considered during the evaluation of the results. The chosen approach depends on the number of multi-display events. If this number is high, the sequence of events forms a multidimensional network, where the definition of multidimensional edges enables clustering of events [31]. If their number is relatively low, the issue can be handled with experience and knowledge of the actual system.  
Visualisation is also a key part of the method. If the number of nodes and edges is high, the readability of the network can quickly worsen. Using open source Python (the used version in the study was 3.9) solutions, this issue can be solved, for example, by changing the layout algorithm to find the most transparent view of the network.  
The number of new displays depends on the attributes of the network gained. In the case study, there were three workflows, but only one new display was recommended because the number of nodes was relatively low. If the number of nodes (events) exceeds a recommended threshold with regard to the human cognitive limits, e.g., the maximal information put on a display, the workflow has to be split. The number of splits (displays) has to be optimised considering the dynamics of the system that can be visualised on the network graph, for example, with node sizes and edge thickness. The proposed method  
Figure 6: The proposed synoptic HMI display. Blue dashed-line boxes represent the actual displays, black lines represent the product flow, red/bourdon lines represent auxiliary flows, arrows indicate the direction of the flow. Elements put between two displays are located on both. The figure is not an exact display; it only represents the proposed content.  
allows many information visualisation options, which support a quick understanding of the system mechanism.  
The main function of the proposed method, the process-related grouping of HMI elements, allows the development of dynamic HP-HMI screens. As the number of monitors in the control room is limited, it is recommended to display as much situation-aware information as possible. Figure 7 demonstrates a possible working principle of a fictive plant with six monitors in the control room. Again, the aim of the figure is to suggest the content of the screens. The actual displays should be enriched, for example, with trend charts, the visualisation and design should follow the suggestions of the ISA101 standard.