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The present work reports the effect of nitrogen ion implantation on aluminum alloy 7075. The microhardness, corrosion resistance, and surface nanostructure were investigated. The implantation was carried out at energy 60 keV with the ion doses used were 1.70 × 1017 ion/cm2, 1.86 × 1017 ion/cm2, 2.02 × 1017 ion/cm2, 2.17 × 1017 ion/cm2, and 2.33 × 1017 ion/cm2. The microhardness test was performed to study the hardness of the implanted layer which was characterized by X-ray Diffraction (XRD). The potentiodynamic corrosion test was performed in a 0.5 mol/l NaCl solution. The surface nanostructure was investigated by atomic force microscopy (AFM) to study the surface roughness after implantation. The results showed that the microhardness after implantation at 2.17 × 1017 ion/cm2 increased by 90.81%. The increase was attributed to the formation of the AlN phase. The AlN phase was confirmed at 2-theta peaks of 39.53°, 45.84°, 66.90°, and 80.54°. The corrosion test showed the improvement of corrosion resistance by the decrease of corrosion rate from 4.49 mpy to 1.43 mpy. The atomic force microscopy showed the arithmetical mean height (Sa) value was 37.5 nm and the root means square (Sq) value was 47.6 nm. The ion implantation induced the change of material surface due to the penetration of nitrogen ion into the material.

The examination of defects in radiographic films necessitates specialized knowledge, as indicated by an expert radiographer (AR) degree, yet the subjectivity of AR in identifying defects is problematic. To overcome this subjectivity, an automatic welding defect identification is needed. This is executed by using Matlab to create artificial neural networks, which is beneficial for users with the graphical user interface (GUI) feature. One of the breakthroughs in the figure extraction into seven feature vector values is the geometric invariant moment theory. This prevents translation, rotation, and scaling from changing the figure's characteristics. Therefore, a welding defect identification system with a geometric invariant moment was created in the digital radiographic film figure to overcome the reading error by AR. The identification system obtained an accuracy rating of 89.9%.

The vibration of the secondary cooling system the Kartini reactor works to remove heat from the primary cooling system so that the heating element stays below the safety limit of the specified operating temperature. One component that is supported is a pump that is needed one of them by the vibration analysis method. By using vibration analysis, the type of cause of damage to the pump can be detected without dismantling the pump, so that it can provide predictability of maintenance time, scheduling repairs, picking up damaged equipment before hazardous needs. Vibration measurement with vibration meter (Lutron VB 8202) is carried out on the bearing housing of the secondary cooling pump motor housing in the direction: vertical, horizontal and axial. The value of the vibration compared with the vibration pump standard (ISO 10816-3). From the results of pump vibration measurements, there are several pump parts whose conditions are classified as vibrations that can cause damage to these components, namely the pump motor section. The average vibration on the pump motor is 5.74 mm / s greater than 4.5 mm/s that is classified as a vibration velocity value which can cause damage to other pump components. The results of the symptom analysis of variations in the vibration of abnormal values in the pump motor are caused by looseness of rotation and damage to roller bearings.

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