## 4 Bibliometric Analysis Results
### Engineering Asset Management  
As we also consider that the revealed maintenance methods should be applicable in the field of Engineering Asset Management, which is not used as a direct search string, we discuss this connection briefly. Therefore, we show connections between revealed papers and this research field using the definition of general asset management functions as presented by the authors in [15]. First, _Risk Management_ is the process of identifying risks and taking steps to reduce the latter [71]. In case of equipment maintenance, this would be the identification of the _Remaining Useful Life_ (RUL) [72]. It is evident that _Condition Monitoring_ can be directly found in our revealed papers, e.g., as shown by [73]. Next, the _Asset Usage Life Cycle_ is of paramount importance and [70] uses this concept for energy storage systems. Moreover, maintenance strategies have a great impact on Performance Measures, as  
\begin{table}
\begin{tabular}{c l l l l} \hline \hline \# & **Lead Document** & **Citations** & **Cluster Label** & **Technique** \\ \hline
1 & Smart meters for power grid: Challenges, issues, advantages and status [57] & 87 & Smart meters & Power Grid \\  & Prognostics and health management design & & & Prognostics and Health \\
2 & for rotary machinery systems-Reviews, methodology and applications [58] & 66 & Management (\({}^{3}\)) & Health Management \\
3 & Predictive analytics in information systems & 52 & Big Data Analysis & Statistical Model \\  & research [59] & & & \\  & Service-Oriented Infrastructure to Support & & & \\
4 & the Deployment of Evolvable Production & 47 & Automation Systems & Web Services \\  & Systems [60] & & & \\  & Data Science, Predictive Analytics, and Big & & & \\
5 & Data: A Revolution That Will Transform & 46 & Data Science & Supply Chain \\  & Supply Chain Design and Management [61] & & & management \\  & Development of an optimized & & & \\
6 & condition-based maintenance system by & 44 & Reliability-centered & Data Fusion \\  & data fusion and reliability-centered & 44 & Maintenance & \\  & maintenance [62] & & & \\
7 & In pursuit of implementation patterns: The & 44 & Total Productive & Total Productive \\  & control of Lean and Six Sigma [63] & & Maintenance & Maintenance \\
8 & Reliability-Centered Maintenance for Wind & 39 & Wind Turbine (\({}^{3}\)) & Failure Mode and \\  & & & & \\
8 & Turbines Based on Statistical Analysis and & 39 & Wind Turbine (\({}^{3}\)) & Effect Analysis \\  & Practical Experience [64] & & & \\
9 & Robust Self-Healing Concrete & 39 & Smart Material & Self-healing Concrete \\  & Sustainable Infrastructure [65] & & & \\  & Intelligent Systems for Improved Reliability & 28 & Smart Grid & Distribution Fault \\
10 & and Failure Diagnosis in Distribution & 28 & Smart Grid & Anticipation \\  & Systems [66] & & & \\
11 & Server consolidation frameworks for cloud & 27 & Cloud Computing (\({}^{3}\)) & VM Migration \\  & data centers [67] & & & \\  & State of the art review of inspection & & & \\
12 & technologies for condition assessment of & 26 & Road Maintenance & Non-destructive \\  & water pipes [68] & & & Inspection \\
13 & Direct Evaluation of IEC 61850-9-2 Process & 12 & Circuit Breakers & Smart Grids \\  & Bus Network Performance [69] & & & \\
14 & Electrical energy storage systems: & & & \\  & A comparative life cycle cost analysis [70] & 11 & Energy Systems & Monte Carlo \\ \hline \hline \end{tabular}
\end{table}
Table 7: Research Front Clusters.  
shown, for example, by the authors of [74]. Finally, Intelligent _Information Systems_ enrich maintenance approaches by improving the reliability [66]. In conclusion, our revealed papers cover many parts of the Engineering Asset Management field.