# Computer Architecture for Industrial Training Evaluation
## 3 Methodology
### Phase 3. Definition of the Components of Software Architecture
#### 3.3.4 Layer 4--Data  
The raw material is stored, processed, and refined to generate information. The proposed architecture divides the data layer of an enterprise architecture into two: information and data layers. This division allows the proposed architecture to be reused in other development contexts by changing the business logic in the information layer and the way in which data is obtained in the data layer.  
Figure 6 presents the process defined in the Information layer to carry out training and specifies the exact point where the data will be extracted with the assistance of the Systems and Application layer through technological platforms.  
Test Scenarios  
The data extraction process begins with the definition of the environment. In this research, the study scenario is constituted by industrial training processes. Therefore, it is necessary to define the test scenarios, including the type of machine, task, related processes, and involved actors.  
The types of machines analyzed in this research are:  
* The Winston Parallel Lathe is a high-precision mechanical lathe, whose name is due to its design, which has a bed parallel to the rotation axis. In addition to its capability to perform the turning process, this lathe can perform other processes such as threading, taper turning, and drilling.
* CNC lathes are Computer Numerical Control (CNC) machines. These can automate processing and quickly adapt to production changes. In this context, CNC lathes have become an essential tool for the mass production of high-precision parts.  
Table 3 describes the specific uses and parts that can be manufactured with the lathes according to the scenario type.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Scenario Type** & **Uses** \\ \hline Production and manufacturing industry & Screws, hinges, gears. \\ \hline Automotive industry & Axles, bearings, gears, camshafts, cylinders, pistons. \\ \hline Aerospace industry & Metal and plastic parts including aircraft and missile parts. \\ \hline IT industry & Hard drive and precision components for electronic devices. \\ \hline Medical industry & Production of prostheses, implants, bone fixation screws and other \\ \hline Electrical industry & Production of generators, transformers and other components of \\ \hline \multirow{2}{*}{Wood industry} & Production of wood in the form of columns, cylinders, rods, and other \\  & profiles. This includes the production of wooden parts for furniture, \\ \cline{1-1}  & musical instruments and other applications. \\ \hline \hline \end{tabular}
\end{table}
Table 3: Machine use scenarios.  
Figure 6: Data collection process.  
Figure 7 presents a model of the Winston lathe. Manual handling of the parallel lathe carriages requires highly qualified professionals to avoid errors in the geometry of the turned parts.  
For the testing phase with those interested in the training processes, two groups of people were selected for work. The first group (control group) corresponded to workers who learned to operate the machines with traditional training, that is, by transferring information from one person to another or reading a manual. The second group (experimental group) were students in the area of mechanics who, according to their study plan, had to learn to manipulate lathe-type machines and received training with the application. Table 4 presents the technical sheet of the tests carried out.