• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.14 no.1
• /
• pp.52-57
• /
• 2005

In the foe of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a mai or change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.04a
• /
• pp.124-129
• /
• 2003

In the face of global competitor the requirements flor the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models fir simulation and quantitative description of the industrial operations involved. In this paper, a on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• Korean Journal of Materials Research
• /
• v.4 no.2
• /
• pp.241-249
• /
• 1994

We studied on the effects of hot-worm rolling on recrystalized structures and tensile strength in over-aged 7075 A1 alloy, to develop the process for improving properties. It showed more clear effect of the grain refinement with over-aging before plastic deformation. That means, the coarse precipitates from over-aging play a roll as nucleation sites in the course of recrystallization. And on this study, the relations between yield strength and grain size was not satisfied with Hall-Petch equation because of the elongated structure, but the yield strength is proportional to aspect ratio of grains. In TMT process for improving strength and toughness, the worm working is available for increase of those properties than cold working.

• Journal of Powder Materials
• /
• v.10 no.1
• /
• pp.15-20
• /
• 2003

Hybrid $A1_2O_3-TiC$ ceramic particle reinforced 6061 and 5083 Al composite powders were prepared by the combination of twin rolling and stone mill crushing process, followed by consolidating processes of cold compaction, degassing and hot extrusion. The composite bar consists of lamellar structure of ceramic particle rich area and matrix area, in which the hybrid was decomposed into each TiC of about $3-4\mutextrm{m}$ and $AI_2O_3$ particles of about $1-2\mutextrm{m}$ in diameter. It also found that fine $Mg_2Si$ precipitates of about 30 nm were embedded in the matrix, which have grains of about 3 $\mutextrm{m}$. Higher UTS was measured at the 5083 composite bar compared to the conventionally fabricated composite, due to again refinement effect by the rapid solidification. No particle was shown to form in the interface between the matrix and reinforcement, whereas carbon was diffused into the matrix.