Predictive Control for Manual Plasma Arc Pipe Welding

Plasma arc welding (PAW) has several advantages over traditional gas tungsten arc welding (GTAW) process. However, due to its sensitivity to welding parameters, this process has not been widely used in industry, especially for manual welding applications where variations in welding parameters are substantial. This paper introduces and implements a model predictive control (MPC) method to adjust welding current in order to compensate the effects from these variations during manual plasma welding operation. A linear model with adequate accuracy has been selected for the design of control system. Closed-loop control experiments verified the effectiveness of developed control system.

The Study of Surface Roughness and MRR of Mild Steel Using Manual Plasma Arc Cutting Machining

Manufacturing companies define the qualities of thermal removing process based on the dimension and physical appearance of the cutting material surface. Therefore, the roughness of the surface area of the cutting material and the rate of the material being removed during the manual plasma arc cutting process was importantly considered. Plasma arc cutter Selco Genesis 90 was used to cut the specimens made from Standard AISI 1017 Steel manually based on the selected parameters setting. Two different thicknesses of specimens with 3mm and 6mm were used. The material removal rate (MRR) was measured by determining the weight of the specimens before and after the cutting process. The surface roughness (SR) analysis was conducted to determine the average roughness (Ra) value. Taguchi method was utilized as an experimental layout to obtain MRR and Ra values. The results reveal that for the case of manual plasma arc cutting machining, the SR values are inversely proportional to the MRR values. The quality of the surface roughness depends on the dross peak that occurred during the cutting process.