Lu et al., 2017 - Google Patents
A modified analytical cutting force prediction model under the tool flank wear effect in micro-milling nickel-based superalloyLu et al., 2017
View PDF- Document ID
- 8222895316452379874
- Author
- Lu X
- Wang F
- Jia Z
- Si L
- Zhang C
- Liang S
- Publication year
- Publication venue
- The International Journal of Advanced Manufacturing Technology
External Links
Snippet
This study attempts to develop a micro-milling force model under cutting conditions considering tool flank wear effect during micro-milling of nickel-based superalloy with coated carbide micro-milling tools based on our three-dimensional dynamic cutting force prediction …
- 238000003801 milling 0 title abstract description 76
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/4097—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by using design data to control NC machines, e.g. CAD/CAM
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/49—Nc machine tool, till multiple
- G05B2219/49085—CMP end point analysis, measure parameters on points to detect end of polishing process
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Lu et al. | A modified analytical cutting force prediction model under the tool flank wear effect in micro-milling nickel-based superalloy | |
Tlhabadira et al. | Modelling and optimization of surface roughness during AISI P20 milling process using Taguchi method | |
Zhanqiang et al. | Definition and determination of the minimum uncut chip thickness of microcutting | |
Yang et al. | Tool edge radius effect on cutting temperature in micro-end-milling process | |
Madariaga et al. | Reduction of distortions in large aluminium parts by controlling machining-induced residual stresses | |
Afazov et al. | Prediction and experimental validation of micro-milling cutting forces of AISI H13 steel at hardness between 35 and 60 HRC | |
Agmell et al. | The influence of tool micro-geometry on stress distribution in turning operations of AISI 4140 by FE analysis | |
Isbilir et al. | Finite element analysis of drilling of titanium alloy | |
Daniyan et al. | Design and optimization of machining parameters for effective AISI P20 removal rate during milling operation | |
Yang et al. | Tool wear prediction of machining hydrogenated titanium alloy Ti6Al4V with uncoated carbide tools | |
Jiang et al. | An approach for analyzing and controlling residual stress generation during high-speed circular milling | |
Aydın et al. | Identification and modeling of cutting forces in ball-end milling based on two different finite element models with Arbitrary Lagrangian Eulerian technique | |
Jing et al. | Modelling the cutting forces in micro-end-milling using a hybrid approach | |
Abdelhafeez et al. | A coupled Eulerian Lagrangian finite element model of drilling titanium and aluminium alloys | |
Zhou et al. | A novel instantaneous uncut chip thickness model for mechanistic cutting force model in micro-end-milling | |
Manso et al. | Tool wear modelling using micro tool diameter reduction for micro-end-milling of tool steel H13 | |
Nespor et al. | Surface topography after re-contouring of welded Ti-6Al-4V parts by means of 5-axis ball nose end milling | |
Cui et al. | Evaluation of specific cutting energy considering effects of cutting tool geometry during micro-machining process | |
Han et al. | Cutting deflection control of the blade based on real-time feedrate scheduling in open modular architecture CNC system | |
Yue et al. | Modeling machining errors for thin-walled parts according to chip thickness | |
Jia et al. | A new cutting force prediction method in ball-end milling based on material properties for difficult-to-machine materials | |
Lu et al. | Predicting the surface hardness of micro-milled nickel-base superalloy Inconel 718 | |
Astakhov et al. | The principle of minimum strain energy to fracture of the work material and its application in modern cutting technologies | |
Wang et al. | An integrated optimization of cutting parameters and tool path generation in ultraprecision raster milling | |
Jackson et al. | Predicting chip and non-chip formation when micromachining Ti-6Al-4V titanium alloy |