際際滷shows by User: 112525 / http://www.slideshare.net/images/logo.gif 際際滷shows by User: 112525 / Mon, 16 Jun 2014 06:33:20 GMT 際際滷Share feed for 際際滷shows by User: 112525 Machining of duplex stainless steels: a comparative study /slideshow/machining-of-duplexstainlesssteelsacomparativestudy/35916776 machiningofduplexstainlesssteelsacomparativestudy-140616063320-phpapp02
This paper investigates the machining of super duplex EN 1.4410, standard duplex EN 1.4462 and austenitic EN 1.4404 stainless steels through a two-phase experimental study. In the first phase, a new methodology based on Mamdani fuzzy interference of classified chip shapes in chip breaking charts to predict the chip volume ratio is presented. Chip volume ratios, specific cutting pressures, cutting powers and resultant cutting forces are considered as performance characteristics and converted into single indices using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), VIKOR method and Utility Analysis (UA). An expert system based on fuzzy rule modelling approach is then adopted to combine the computed indices into a single Universal Characteristics Index (UCI). Results showed that converting the output of different Multiple Attribute Decision Making (MADM) methods into a single UCI index is a simple and efficient technique in determining an optimal combination of the cutting parameters. Constrained simulated annealing optimization procedure is then employed to evaluate the optimal process parameters thereby satisfying conflicting requirements of each of performance factors. First ranking UCI values are analyzed and compared with the output of multi-objective optimization techniques (MOO) using Weighted Sum Method. A remarkable improve in reduction of cutting power consumption, specific cutting pressure, resultant cutting forces are reported when first rank UCI value is directly reported as optimum point instead of performing conventional optimization. In the second phase, cutting force and machine current consumption signals are adopted as indirect cutting tool wear monitoring techniques to graph the tool wear progression. Results showed that the tool life strongly affected by cutting speed and workpiece material.]]>
This paper investigates the machining of super duplex EN 1.4410, standard duplex EN 1.4462 and austenitic EN 1.4404 stainless steels through a two-phase experimental study. In the first phase, a new methodology based on Mamdani fuzzy interference of classified chip shapes in chip breaking charts to predict the chip volume ratio is presented. Chip volume ratios, specific cutting pressures, cutting powers and resultant cutting forces are considered as performance characteristics and converted into single indices using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), VIKOR method and Utility Analysis (UA). An expert system based on fuzzy rule modelling approach is then adopted to combine the computed indices into a single Universal Characteristics Index (UCI). Results showed that converting the output of different Multiple Attribute Decision Making (MADM) methods into a single UCI index is a simple and efficient technique in determining an optimal combination of the cutting parameters. Constrained simulated annealing optimization procedure is then employed to evaluate the optimal process parameters thereby satisfying conflicting requirements of each of performance factors. First ranking UCI values are analyzed and compared with the output of multi-objective optimization techniques (MOO) using Weighted Sum Method. A remarkable improve in reduction of cutting power consumption, specific cutting pressure, resultant cutting forces are reported when first rank UCI value is directly reported as optimum point instead of performing conventional optimization. In the second phase, cutting force and machine current consumption signals are adopted as indirect cutting tool wear monitoring techniques to graph the tool wear progression. Results showed that the tool life strongly affected by cutting speed and workpiece material.]]> Mon, 16 Jun 2014 06:33:20 GMT /slideshow/machining-of-duplexstainlesssteelsacomparativestudy/35916776 112525@slideshare.net(112525) Machining of duplex stainless steels: a comparative study 112525 This paper investigates the machining of super duplex EN 1.4410, standard duplex EN 1.4462 and austenitic EN 1.4404 stainless steels through a two-phase experimental study. In the first phase, a new methodology based on Mamdani fuzzy interference of classified chip shapes in chip breaking charts to predict the chip volume ratio is presented. Chip volume ratios, specific cutting pressures, cutting powers and resultant cutting forces are considered as performance characteristics and converted into single indices using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), VIKOR method and Utility Analysis (UA). An expert system based on fuzzy rule modelling approach is then adopted to combine the computed indices into a single Universal Characteristics Index (UCI). Results showed that converting the output of different Multiple Attribute Decision Making (MADM) methods into a single UCI index is a simple and efficient technique in determining an optimal combination of the cutting parameters. Constrained simulated annealing optimization procedure is then employed to evaluate the optimal process parameters thereby satisfying conflicting requirements of each of performance factors. First ranking UCI values are analyzed and compared with the output of multi-objective optimization techniques (MOO) using Weighted Sum Method. A remarkable improve in reduction of cutting power consumption, specific cutting pressure, resultant cutting forces are reported when first rank UCI value is directly reported as optimum point instead of performing conventional optimization. In the second phase, cutting force and machine current consumption signals are adopted as indirect cutting tool wear monitoring techniques to graph the tool wear progression. Results showed that the tool life strongly affected by cutting speed and workpiece material. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/machiningofduplexstainlesssteelsacomparativestudy-140616063320-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This paper investigates the machining of super duplex EN 1.4410, standard duplex EN 1.4462 and austenitic EN 1.4404 stainless steels through a two-phase experimental study. In the first phase, a new methodology based on Mamdani fuzzy interference of classified chip shapes in chip breaking charts to predict the chip volume ratio is presented. Chip volume ratios, specific cutting pressures, cutting powers and resultant cutting forces are considered as performance characteristics and converted into single indices using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA), VIKOR method and Utility Analysis (UA). An expert system based on fuzzy rule modelling approach is then adopted to combine the computed indices into a single Universal Characteristics Index (UCI). Results showed that converting the output of different Multiple Attribute Decision Making (MADM) methods into a single UCI index is a simple and efficient technique in determining an optimal combination of the cutting parameters. Constrained simulated annealing optimization procedure is then employed to evaluate the optimal process parameters thereby satisfying conflicting requirements of each of performance factors. First ranking UCI values are analyzed and compared with the output of multi-objective optimization techniques (MOO) using Weighted Sum Method. A remarkable improve in reduction of cutting power consumption, specific cutting pressure, resultant cutting forces are reported when first rank UCI value is directly reported as optimum point instead of performing conventional optimization. In the second phase, cutting force and machine current consumption signals are adopted as indirect cutting tool wear monitoring techniques to graph the tool wear progression. Results showed that the tool life strongly affected by cutting speed and workpiece material.
Machining of duplex stainless steels: a comparative study from Rasper Dellshad
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