## 3 State-of-the-Art Techniques for Predictive Maintenance
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Ref.** & \
\begin{tabular}{c} **Class of Repair** \\ **and Maintenance** \\ \end{tabular} & **Industry** & **Application** &
\begin{tabular}{c} **Problem Type/** \\ **Approach** \\ \end{tabular} & **Algorithm/Technology** \\ \hline
[85] & Fabricated metal & Cloud services and & \
\begin{tabular}{c} The detection of \\ imminent hard \\ disk drive failures \\ in Backblaze \\ dataset [140] \\ \end{tabular} & Classification &
\begin{tabular}{c} Apache Spark, which is \\ an in-memory \\ distributed data analysis \\ platform, and RF \\ \end{tabular} \\ \hline
[86] & Electronic and & Smart & \
\begin{tabular}{c} A manufacturing \\ big data ecosystem \\ addressing the \\ issues of big data \\ ingestion, \\ management, and \\ analytics for \\ fault/anomaly \\ detection in \\ IoT-based smart \\ factories \\ \end{tabular} &
\begin{tabular}{c} The distributed K-means \\ clustering, \\ MapReduce-based \\ distributed PCA-based \\ T-squared, and SPE \\ algorithms \\ A data lake, NoSQL \\ database, and \\ encryption protocol on \\ the Apache Spark \\ platform \\ \end{tabular} \\ \hline
[87] & Transport & Transport & \begin{tabular}{c} PdM approach for \\ malfunction \\ evaluation in \\ relation to the \\ kilometers of the \\ train and the \\ periodicity of \\ faults in the Greek \\ Railway Company \\ \end{tabular} & \
\begin{tabular}{c} Regression \\ Classification \\ Classification \\ \end{tabular} &
\begin{tabular}{c} Classification trees J48 \\ and regression trees M5 \\ form algorithms \\ \end{tabular} \\ \hline
[88] & \begin{tabular}{c} Machinery and \\ equipment \\ \end{tabular} & Electronics & \
\begin{tabular}{c} Failure prediction \\ of the monitored \\ manufacturing \\ industrial \\ machinery by UCI \\ SECOM dataset \\ \end{tabular} & Classification &
\begin{tabular}{c} A fusion of data mining \\ and semantics \\ \end{tabular} \\ \hline
[89] & \begin{tabular}{c} Other machinery \\ and equipment \\ \end{tabular} & Textile & \
\begin{tabular}{c} Production quality \\ prediction in the \\ textile industry \\ \end{tabular} & Regression &
\begin{tabular}{c} Supervisory control and \\ data acquisition \\ (SCADA) architecture to \\ develop a cloud-based \\ analytics module \\ \end{tabular} \\ \hline
[90] & \begin{tabular}{c} Transport \\ equipment, except \\ motor vehicles \\ \end{tabular} & Logistics and & \
\begin{tabular}{c} A big data \\ analytics \\ framework for the \\ data-driven \\ prediction of \\ center package \\ breaks in smart \\ goods \\ transportation \\ systems \\ \end{tabular} &
\begin{tabular}{c} IoT networks \\ Gradient boosting \\ classifiers, SVM, logistic \\ regression, and Apache \\ Spark \\ \end{tabular} \\ \hline
[91] & - & \
\begin{tabular}{c} Vinyl flooring \\ \end{tabular} &
\begin{tabular}{c} Quality \\ management in the \\ vinyl flooring \\ industry \\ \end{tabular} & - & Big data analytics and \\
[91] & - & \
\begin{tabular}{c} Vinyl flooring \\ industry \\ \end{tabular} & - &
\begin{tabular}{c} Big data analytics and \\ optimization \\ Edge computing \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Cont. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Ref. ** & \begin{tabular}{c} **Class of Repair** \\ **and Maintenance** \\ \end{tabular}  & **Industry** & **Application** & \begin{tabular}{c} **Problem Type/** \\ **Approach** \\ \end{tabular}  & **Algorithm/Technology** \\ \hline \multirow{4}{*}{[92]} & \multirow{4}{*}{ \begin{tabular}{c} Electrical \\ equipment \\ \end{tabular}  } & \multirow{4}{*}{Industrial robots} & Health status & \multirow{4}{*}{Regression} & Programmable logic \\  & & & degradation & & controllers (PLC) \\  & & & assessment using & & One-class novelty \\  & & & real data of the & & \\  & & & ABB IRB 6400r & & & \\  & & & industrial robot & & \\ \hline \multirow{4}{*}{[93]} & \multirow{4}{*}{ \begin{tabular}{c} Electrical \\ equipment \\ \end{tabular}  } & \multirow{4}{*}{ \begin{tabular}{c} Metal and \\ metallurgy \\ \end{tabular}  } & \multirow{4}{*}{