# 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
#### 4.2.4 Summarization of DM with Big Data Application in Different Stages  
Figure 4 illustrates different functions used by the selected articles applied in different stages. It can be seen that the prediction, classification, and clustering functions are the top three functions employed for mining patterns at different stages. The six functions have been used in the production stage which indicates that there are diverse requirements of DM and Big Data application at this stage for different purposes, while the time series analysis and outlier detection function have seldom been used in the stage of design and SSR. Figure 5 illustrates the distribution of different knowledge areas considering the tasks of QI for design/production, DTCE, PTP, FDC, VM, R2R, SPC, CRM, and SCM according to Tables 9-13. The frequency in Figure 5 indicates that the QI for design, scheduling optimization, production time prediction, FDC, post hoc diagnosis, production yield/quality prediction, and optimization of sale and service for CRM are pervasive knowledge areas and tasks. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Functions** & **DMTs** & **Categories** & **Knowledge Area/Task** & **Product** & **Indicator** & **Ref.** \\ \hline \multirow{8}{*}{Prediction (6)} & Text mining + Regression & SA-oriented, KD-oriented & Purchase decisions prediction & iPhone, Mac, iPad, iPad and so forth. and components & - & [123] \\  & SVM & KD-oriented & Behavior prediction & Used hard disk & MAPE, MAE, MSE & [124] \\  & SVR + Bat K-means, SOM, FNN & KD-oriented SA-oriented, KD-oriented & Marketing and sale trends & PCB & MAPE, RMSE & [125] \\  & Fuzzy CBR & KD-oriented & prediction & & MAPE, RMSE & [126] \\  & Weighted evolving FNN & KD-oriented & & & MAPE, MAE, RMSE & [127] \\ \hline \multirow{2}{*}{Classification (1)} & Text mining + Regression & SA-oriented & Repair experience extraction & iPhone, Mac, iPad, iPad and so forth. and components & PPV, TPR & [123] \\ \hline \multirow{8}{*}{Clustering (2)} & \multirow{2}{*}{K-means, SOM, FNN} & \multirow{2}{*}{SA-oriented, KD-oriented} & Repaired products clustering & Camera, laptop, phone, printer, and so forth. & - & [129] \\  & & & Marketing and sale trends & PCB & - & [126] \\ \cline{1-1}  & & & prediction & & & \\ \hline Time series analysis (1) & Nonlinear least square & SA-oriented & Demand prediction & Semiconductor & MAPE, R2 & [130] \\ \hline \hline \end{tabular}
\end{table} 
Table 13: DM and Big Data application in the sale, service and recycling stage. The statistic of different categories of DMTs adopted in the 105 articles for different knowledge areas are conducted and the results are illustrated in Figure 6 from which we can see that the pervasively used DMTs are hybrids or integrations of the SA-oriented and KD-oriented DMTs, especially for the knowledge areas of PMO, AEC/APC, and QI for production, followed by the combination of different KD-oriented DMTs or only one KD-oriented DMT. However, only one SA-oriented approach and the ensemble of SA-oriented DMTs have been widely adopted by researchers compared to other approaches. Figure 4: DM function applications in different stages. Figure 5: Distribution of different knowledge areas. The commonly used 10 DMTs including ANN (back propagation neural network, fuzzy neural network, and so forth), fuzzy logic, DT (CART, CHAID, C5.0, and so forth), regression (MLR, MRA, stepwise regression, PLSR, logistic regression, and so forth), SVM (SVR, ASVR, and so forth), SOM, FCM, K-means, GA, and Apriori are given in Figure 7. Figure 8 presents different DMTs in different knowledge areas. It can be seen that the top DMT used is ANN followed by fuzzy logic because many ANNs are combined with fuzzy logic to solve the scheduling optimization and production time prediction. ANN has been applied in eight areas of the above-mentioned knowledge areas except for SPC and R2R. Fuzzy logic has been used mainly for the production time prediction, yield/quality prediction, and the optimization of CRM/SCM.