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Since the cold roll forming process is currently used in the production of different sections, it is necessary for manufacturers to further improve the quality of these products. Therefore, it is essential to study various factors influencing the production of these products in detail and provide effective solutions to reduce the factors causing defects in such products. This paper investigates the effect of plastic anisotropy and various factors such as strip thickness, the inter distance between stands, web width, and angle increment on the longitudinal bowing and then compares the results with the practical experiments. Accordingly, a model considering the effect of these parameters on the longitudinal bowing of the final section is considered with the accuracy of 88%. The results show that strip thickness and the increment angle at each stand, and the web width have the most influence on the longitudinal bowing, while strip anisotropy and the inter distance has the least effect on bowing.

The surface roughness model in the turning of 34CrMo4 steel was developed in terms of cutting speed, feed rate and depth of cut and tool nose radius using response surface methodology. Machining tests were carried out using several tools with several tool radius under different cutting conditions. The roughness equations of cutting tools when machining the steels were achieved by using the experimental data. The results are presented in terms of mean values and confidence levels.The established equation and graphs show that the feed rate and cutting speed were found to be main influencing factor on the surface roughness. It increased with increasing the feed rate and depth of cut, but decreased with increasing the cutting speed, respectively. The variance analysis for the second-order model shows that the interaction terms and the square terms were statistically insignificant. However, it could be seen that the first-order affect of feed rate was significant while cutting speed and depth of cut was insignificant.The predicted surface roughness model of the samples was found to lie close to that of the experimentally observed ones with 95% confident intervals.

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