# A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry
## 4 Data Mining with Big Data Applications in the Electronics Industry
### Application of DM with Big Data in Different Stages
#### 4.2.3 Application of DM and Big Data for Sale, Service, and Recycling  
The stage of sale, service, and recycling (SSR) is to store produced products in a warehouse and transport them to customers in logistics, and then the customers use the product while a manufacturer provides remote service. If it can no longer be used, it comes to the end of its life such as remanufacturing and disposal [8].  
The summarization of DM application in the SSR stage is given in Table 13 and it can be seen that most of the applications related to CRM involve marketing and sales prediction [125; 126; 127], customer  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Functions (Frequency)** & **DMTs** & **Categories** & \begin{tabular}{c} **Knowledge** \\ **Area/Task** \\ \end{tabular} & **Indicator** & **Ref.** \\ \hline \multirow{8}{*}{Classification (11)} & SOM, K-means, DT & SA-oriented & \begin{tabular}{c} Quality \\ classification \\ \end{tabular} & DBI & [94] \\  & NB, SVM, ANN & KD-oriented & & ACC & [109] \\  & CHAID & SA-oriented & & TPR TNR, FPR, & [110] \\  & SVM & KD-oriented & & TPR, FPR & [111] \\  & PCA, SVM, adaptive & SA-oriented, & & & \\  & boosting, DT & KD-oriented & & & \\  & SVM & KD-oriented & & & \\  & Statistical model & SA-oriented & & & - & [114] \\  & CART & & & TPR, FPR & [115] \\  & SVM & KD-oriented & & & - & [116] \\  & K-means, DT & SA-oriented, & & & - & [117] \\  & Spatial statistics + & KD-oriented & & & - & [118] \\  & adaptive ANN, DT & & & & \\ \hline \multirow{8}{*}{Clustering (6)} & SOM, K-means, DT & & Quality & \multirow{2}{*}{DBI} & [94] \\  & & & classification & & \\  & SDC & & Post hoc & & \\  & & diagnosis & & & \\  & Regression, ANN, & & Yield & & \\  & K-means, clustering & SA-oriented, & prediction & & - & [101] \\  & FCM + GA + DT & KD-oriented & Quality & & ME & [105] \\  & K-means, DT & & Post hoc & - & [117] \\  & Spatial statistics + & & diagnosis & & - & [118] \\  & adaptive ANN, DT & & & & \\ \hline \multirow{8}{*}{Association (Sequence Analysis) (3)} & Association rule tree & SA-oriented, & \multirow{2}{*}{\
\begin{tabular}{c} Yield \\ prediction \\ \end{tabular} } & \multirow{2}{*}{MAPE} & \multirow{2}{*}{[102]} \\  & Bayesian network, & KD-oriented & & & \\ \cline{1-1}  & PLS, Apriori & & Post hoc & & ACC & [119] \\ \cline{1-1}  & Decision correlation & KD-oriented & & diagnosis & - & [120] \\ \hline \multirow{2}{*}{Time series analysis (1)} & Co-clustering & SA-oriented & \multirow{2}{*}{
\begin{tabular}{c} Quality \\ prediction \\ \end{tabular} } & \multirow{2}{*}{RMSE} & \multirow{2}{*}{[121]} \\ \cline{1-1}  & & & & \\ \hline Outlier detection (1) & Hierarchical clustering, DT & SA-oriented, & Post hoc & & \\ \cline{1-1}  & clustering, DT & KD-oriented & diagnosis & - & [122] \\ \hline \end{tabular}
\end{table}
Table 12: _Cont._service [129], and the SCM to achieve greater efficiencies and effectiveness in delivering customer value [130]. The detailed information indicates that one direction of the research is to mine the behavioral characteristics of customers on the product and maintenance, and therefore, identify customer's requirement for customer attraction and retention [123; 129]. Another one is to predict the marketing demand and price for customer identification and development, and therefore, to facilitate the plan optimization of production, procurement, and resource [125; 126; 127]. Only one article is related to the recycling of electronic products considering the storage behavior of customers [124]. From Table 13, it can also be seen that the prediction of marketing requirement and determination of a more reasonable price are the main functions while the clustering and classification have been taken to classify products and customer's requirement and identify the purchase feature of different customers. Text mining was utilized to excavate the knowledge from interaction records in some cases [123].