**4. Conclusions**

In the final section of this work, we address the open challenges pertaining to DTF realization in EM CM and PM:

An important but indirect usage of an established DTF in industry is the safety and risk assessment of the system. Worker safety is one of the pillars of CM, as heavy machinery faults can endanger the lives of personnel and material damages. There is no extensive research yet, but the excellent work of [60] follows the discussed paradigms, provides extensive coverage and proposes a DT catering to the issue.

Following on the ambiguity of literature, there exists no benchmark or general guideline concerning the creation of an industry standard DT. While this paper aims to introduce this full concept, future work is needed to establish a working prototype and framework which can be validated and criticized by fellow researchers. Afterwards, the DTF itself can aid in methodology benchmarking, which is another CM research topic in dire need of evolution.

Information technologies are the main enabling factor of the DTF. As we mentioned before, DT elements fall into the category of Big Data and require new approaches and validations thereof. Analysis and review of these approaches is deemed out of scope of this work but remains an open challenge. Relevant, extensive work in DT data handling can be found in [61–63].

DT offers a unique opportunity for AI integration into CM in the form of appropriate data structures and connections. AI integration is the focus of state-of-the-art PM research as decision-making offers the biggest upgrade value, since conventional methodologies already are at peak performance [63].

DT technology further enables a better UI, especially through AR [64]. The data integration and sensor technology allow for seamless UI improvements through ancillary systems. While secondary work (post realization and validation), this approach will combine the DT and the human element, encapsulating, training, maintenance, control, and validation, main endeavors of the DTF.

Our final statement for this work is that the DTF is observed to be the state-of-the-art approach in the scientific community. Enabling technologies and guiding principles are intertwined with modern Electrical Engineering and Power Systems concepts such as RES, EVs, Distribution Networks, EM PM, and manufacturing. The Internet of Everything era and Industry 4.0 call for co-operation of research and technologies. We surmise that the DTF is the connecting catalyst for this next generation of industry. The first step is to establish the guiding principles for DTF realization catering to the necessities of each sector. This work aims to explain DTF integration with the requirements of the EM PM community, a brief analysis of which can be found in [65]. Future prospects include working proof of concept and its usage in state-of-the-art research, namely: benchmarking, validation, AI training, combination of methodologies, and commissioning time reduction.

**Author Contributions:** Conceptualization, G.F. and A.K.; methodology, G.F.; software, G.F.; validation, A.K.; formal analysis, A.K.; resources, G.F.; writing—original draft preparation, G.F.; writing— review and editing, G.F. and A.K.; visualization, G.F.; supervision, A.K.; project administration, A.K. Both authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.
