• IE interfaces
• /
• v.9 no.1
• /
• pp.1-10
• /
• 1996

In this study, expert system for the selection of the optimal cutting speed and feed rate was developed using NEXPERT system shell. The NC system has been usually used inefficiently because the input command, which contains cutting speed, feed-rate and the depth of cut, is fixed value which depends on principally operator's experience and machining handbooks providing a guideline for applicable ranges. On the other hand, the optimal cutting conditions vary with time, and depend on tool and machine characteristics, work materials, and cost factor and so on. In this study, if cutting factors, such as, cutting method, material type, cutting depth, and tool nose radius are specified, our expert system gets the information about the standard cutting speed form the cutting speed database, and provides optimum feed rate for these cutting conditions. This cutting speed database can be updated by inputting valid cutting speed which is obtained form the practices.

• Journal of the Korean Society of Industry Convergence
• /
• v.11 no.2
• /
• pp.83-91
• /
• 2008

GMAW(Gas Metal Arc Welding) processes are usually used in industrial side in order to get its high productivity. But those are only adopted in the semi-automated welding equipment because of a lot of welding spatters. Many industrial robot actually percents from being engaged in the welding processes. The welding spatter problem of causes blocking them being a fully automated welding process.This study was carried out to investigate the optimal conditions for minimizing welding spatter generation at GMAW robot. The spatter can be significantly reduced below 2% of welding spatter generation at the following conditions ; First, below 18V at the wire-feed rate 2.0mm/min Second, below 23V at the wire-feed rate 3.6mm/min Third, below 24V at the wire-feed rate 5.5mm/min.

• Journal of the korean Society of Automotive Engineers
• /
• v.14 no.6
• /
• pp.113-126
• /
• 1992

Recently the multi-kind, small-amount manufacturing system has been replacing the mass manufacturing system, and domestic machining inustry also is eager to absorb the new technology because of its high productivity and cost reduction. The optimization of the cutting condition has been a vital problem in the machining industry, which would help increase the productivity and raise the international competitiveness. It is intended in this study to investigate the machining costs per unit time which is essential to the analysis of the optimal cutting condition, to computer the cutting speed that lead to the minimum machining costs and the maximum production to suggest the cutting speed range that enables efficient speed cutting, and to review the machining economy in relation to cutting depth and feed. Also considered are the optimal cutting speed and prodution rated in rrelation with feed. It is found that the minimum-cost cutting speed increases and the efficient cutting speed range is reduced as machining cost per unit time increases since the cutting speed for maximum production remains almost constant. The machining cost is also lowered and the production rate increases as the feed increases, and the feed should be selected to satisfy the required surface roughness. The machining cost and production rate are hardly affected by the cutting depth if the cutting speed stays below 100m/min, however, they are subject to change at larger cutting depth and the high-efficient speed range also is restricted. It can be established an adaptive optimal cutting conditions can be established in workshop by the auto-selection progam for optimal operation. It is expected that this method for choosing the optimal cutting conditions might contribute to the improvement of the productivity and reduced the cost. It is highly recommended to prepare the optimal cutting conditionthus obtained for future use in the programing of G-function of CNC machines. If proper programs that automatically select the optimal cutting conditions should be developed, it would be helpful to the works being done in the machine shops and would result in noticeable production raise and cost reduction.

• International Journal of Korean Welding Society
• /
• v.1 no.1
• /
• pp.44-50
• /
• 2001

A genetic algorithm was applied to the arc welding process as to determine the near-optimal settings of welding process parameters that produce the good weld quality. This method searches for optimal settings of welding parameters through the systematic experiments without the need for a model between the input and output variables. It has an advantage of being capable to find the optimal conditions with a fewer number of experiments rather than conventional full factorial designs. A genetic algorithm was applied to the optimization of the weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed. The output variables were the bead height bead width, and penetration. The number of levels for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions,2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions in less than 40 experiments.

• International Journal of Korean Welding Society
• /
• v.3 no.2
• /
• pp.15-23
• /
• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Welding and Joining
• /
• v.18 no.5
• /
• pp.63-69
• /
• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Journal of Welding and Joining
• /
• v.24 no.5
• /
• pp.67-73
• /
• 2006

Laser welding is suitable for welding to the aluminum alloy sheet. In order to apply the aluminum laser welding to production line, parameters should be optimized. In this study, the optimal welding condition was searched through the genetic algorithm in laser welding of AA5182 sheet with AA5356 filler wire. Second-order polynomial regression model to estimate the tensile strength model was developed using the laser power, welding speed and wire feed rate. Fitness function for showing the performance index was defined using the tensile strength, wire feed rate and welding speed which represent the weldability, product cost and productivity, respectively. The genetic algorithm searched the optimal welding condition that the wire feed rate was 2.7 m/min, the laser power was 4 kW and the welding speed was 7.95 m/min. At this welding condition, fitness function value was 137.1 and the estimated tensile strength was 282.2 $N/mm^2$.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.20 no.8
• /
• pp.2508-2515
• /
• 1996

Determination of an optimal feed rate is valuable in the sense of the precision and efficient machining. In this regard, a new surface roughness model for the face milling operation that considered the radial and axal runouts of the inserts in the cutter body was developed. The validity of the model was proved through the cutting experiments, and the model is able to predict the real machined surface roughness exactly with the information of the insert runouts and the cutting conditions. From the estimated surface roughness value, the maximum feed rate that obtains a maximum naterial removal rate under the given surface roughness constraint can be selected by using a bisection method. Therefore, this mehod for optimizing the feed rate can be well applied to the using a bisection method. Therefore, this method for optimizing the feed rate can be well applied to the using selsction of the cutting condition during the NC data generation in CAM.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.25 no.3
• /
• pp.399-407
• /
• 2001

The Surface, generated by end milling operation, is deteriorated by tool runout, vibration, friction, tool deflection, etc. Especially in cornering cut, surface accuracy is usually determined by varying cutting forces, which causes tool deflections. Cutting conditions like feed rate is usually kept constant during machining a part, which causes dimensional error in severe cutting. Cornering cut is a typical example of deterioration of surface accuracy when constant feed rate is applied. Therefore it becomes important to develop NC post processor module to determine optimal cutting conditions in various cutting situations. In this paper, cutting force is predicted in cornering cut with flat end mill and feed rate is determined by constraining constantly resultant force. Also some control characteristics of CNC machining center are evaluated.

• Journal of Animal Environmental Science
• /
• v.18 no.3
• /
• pp.137-144
• /
• 2012

This study was conducted to determine the effect of feed additives including probiotics, moisture and feed ingredients and the effect of fermented feed on digestibility and volatile fatty acid (VFA) level in finishing pigs. Feed was mixed with microbials including Saccharomyces, Lactobacillus, Enterococcus and Pediococcus together with different levels of probiotics, 0.25, 0.5, 1, 2, 3%. Addition of probiotics showed improved fermentation rate after 48 h incubation. To determine the optimal moisture level for fermentation, different levels of water, 30, 40, 50 and 60%, were added into the feed. Fermentation rate of feed with 40~50% moisture level was higher than that from 60% level at 60 h post-fermentation. In vitro fermentation rate of feed ingredients was analyzed by comparing VFA levels. Beet pulp and tapioca showed higher fermentation rate compare to other ingredients including canola meal or rapeseed meal. To determine the effect of administration of fermented feed In vivo, feces from finishing pigs were analyzed. Finishing pigs administrated with fermented feed showed improved digestibility and higher volatile fatty acid (VFA) level. In conclusion, results from the current study indicate that 40~50% of moisture with addition of beet pulp and tapioca in feed is optimal condition for fermentation. Furthermore, our data suggest that fermentation of feed can improve the feed quality and digestibility, thereby provide more nutrient in finishing pigs.