## 7 Conclusions
The models represent an analogy of the evolution of functions along the industrial revolution and help to assess the organizational performance as well as to identify weak points thanks to the detection of inefficiencies. The benefits along the models provide global optimization of the production system grounded in higher manufacturing process performance, better distribution and planning of tasks at the operative level, improved quality control leading to better product quality, and maintenance management providing higher manufacturing system availability, followed by improved IT systems, logistics, quality management, and Industry 4.0 technologies. The results show how several factors can limit the potential of the functions, and as a result, the capabilities of an organization lead to a decreased probability of remaining viable over time. Among the relevant factors, there are technical, organizational structure and processes, as well as human-related factors. In conclusion, the conceptual approach and the applied simulation case study provide managers with a decision-making model for successful management and control of operations while also ensuring well-directed continuous optimization based on a successful diagnosis of improvement potentials in any function of the organization. Limitations of the research work:  
* The conceptual framework of the assessment methodology was not developed in the operative level and for specific cases. Individual interactions among staff, machines, robots, and other elements were not considered in the simulation model. * The full complexity of manufacturing processes was not built in detail. * The organization structure and interfaces were not considered in the simulation model. * Certain quality requirements of the product were not considered. * Investment and costs were assumed. * The concept was not proved in any company. Future research based on this study's findings could focus on the following:
* Transferring this research method to real manufacturing organization and applying it as a digital twin tool or an assistance tool for strategic, CEOs and vice presidents, for tactical level, sales, production, quality and maintenance leaders, and operative levels, by centralizing all data related to the manufacturing organization, functional area, or function, thereby allowing better planning based on updated information of all interrelated factors as well as providing a tool for the assessment and the simulation of what-if-scenarios in real time. * Considering organization units, persons, relationships, and their communication within the simulation model. * Improving the model based on implementation feedbacks as well as applying it to production networks with several production plants. * Improving the simulation model with better connection to the physical world as well as with expanded data analytics and artificial intelligence to provide suggestions in order to assist human decision-making activities. In summary, this study highlights the potential benefits of the conceptual approach and the applied simulation case study, allowing better decision making for top managers, department leaders, and operative management levels. This ensures continuous optimization along the organizational functional structure. The proposed model offers an example of how manufacturing organizations can be assessed, managed, and controlled in an integral way. As a result, the proposed methodology represents a useful tool for organizations and managers in order to increase their efficiency, competitiveness, and therefore, viability over time. Conceptualization, S.G.-G. and M.G.-G.; methodology, M.W. and S.G.-G.; software and programming, S.G.-G.; Validation, M.W. and S.G.-G.; data analysis, S.G.-G.; writing (review and editing), S.G.-G. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The authors declare no conflict of interest.