## 3 Human-Centered Knowledge Graph-Based Concept towards Collaboration in Manufacturing
### Manufacturing Operations Management  
This section delves into an expanded MOM activity model, illustrated in Figure 2, where the components can be categorized based on the timing of their occurrence during the execution of the task. Although this aspect of the methodology has been previously documented by the authors in a conference paper [18], the inclusion of the associated MOMs here aims to enhance the comprehension of the HCKG framework. The temporal perspective of the general activity model concerning pre-, during, post-, and reference data is also emphasized [51]. Moreover, the supplementary modules for extending the standard activity model of MOM [52] are depicted in brown below. The MOM approach is designed to provide a detailed insight into the mechanisms linked to the operator's role in a general manufacturing task, while also emphasizing the characteristics of the additional monitoring and support framework components. The generic activity model is segmented into four sections based on a temporal perspective, indicated by green labels in the diagram, and is evaluated and deliberated upon in a similar manner. The Reference Data encompasses all the details regarding individual operators, including their skills, capabilities, and expertise in specific domains. The Resource and Definition Management segments of the MOM system compile this data and establish the foundational information for the subsequent operational segments of the model. As an expansion of the reference data segment, the Control and Optimization component is suggested, where the integration of machine learning or artificial intelligence solutions can enhance the ongoing manufacturing processes. The following section in Figure 2 represents the Pre-work phase, where Detailed Scheduling is employed based on the Operation Request, and Dispatching tasks are carried out. These actions ensure that all operators receive proper instructions, are efficiently scheduled, and are assigned tasks accordingly. The actual work segment of the MOM delineates the ongoing activities managed by Execution Management, while concurrently conducting Data Collection. Some elements centered on humans are integrated (marked in yellow text), such as Collaboration or the utilization of Human Activity Recognition (HAR) sensor technologies. To enhance real-time operator assistance, additional components like Alarm management, Monitoring and visualization are included as supplementary features. An intelligent monitoring system can gather data from various manufacturing parameters such as temperature, noise, or vibration, and display it graphically in real-time, issuing alerts in case of anomalies. In the post-work phase of the task, monitoring of operator activities is carried out to derive an operational response for the MOM. Additionally, the evaluation of operator performance is utilized, serving as the foundation for Key Performance Indicators (KPIs) and Human Resource Effectiveness (HRE), which are crucial components in the Knowledge Graph (KG) used to establish adaptable and resilient conditions for the operators. The expansion modules of the activity model are intricately linked to the KG through semantic technologies. The advancement of intelligent cyber-physical systems establishes an environment where each aspect of the intricate manufacturing system, involving humans and machines, is effectively supervised, and the information systems are compatible. The vital components of the extended MOM model, viewed from the shop floor perspective, include Operator Performance Analysis, HAR, and Monitoring, which plays a key role in KPI and metric evaluation. A thorough examination of operator performance can support skill-based matching and the development of skill clusters. With the growing need for adaptable production lines, conventional assembly lines might be substituted by self-sufficient work-stations, referred to as skill clusters, with mobile robots transitioning between them.