Beruvides et al., 2014 - Google Patents
Correlation of the holes quality with the force signals in a microdrilling process of a sintered tungsten-copper alloyBeruvides et al., 2014
View PDF- Document ID
- 14635145622894117928
- Author
- Beruvides G
- Quiza R
- del Toro R
- Castaño F
- Haber R
- Publication year
- Publication venue
- International Journal of Precision Engineering and Manufacturing
External Links
Snippet
Holes quality errors are an undesired but unavoidable consequence in drilling operations. Due to the small dimensions involved in the microdrilling processes, quality measurement and control must be carried out offline, by using microscopy or other high precision …
- 238000000034 method 0 title abstract description 21
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Beruvides et al. | Correlation of the holes quality with the force signals in a microdrilling process of a sintered tungsten-copper alloy | |
| Binali et al. | Advance monitoring of hole machining operations via intelligent measurement systems: A critical review and future trends | |
| Klaic et al. | Tool wear classification using decision treesin stone drilling applications: A preliminary study | |
| Duo et al. | The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process | |
| Leksycki et al. | Evaluation of tribological interactions and machinability of Ti6Al4V alloy during finish turning under different cooling conditions | |
| Natarajan et al. | Modeling and multiresponse optimization of quality characteristics for the micro-EDM drilling process | |
| Shi et al. | Evaluation of surface roughness based on sampling array for rotary ultrasonic machining of carbon fiber reinforced polymer composites | |
| Tangjitsitcharoen et al. | Intelligent monitoring and identification of cutting states of chips and chatter on CNC turning machine | |
| Shahabi et al. | Prediction of surface roughness and dimensional deviation of workpiece in turning: a machine vision approach | |
| Shilpa et al. | Surface roughness estimation techniques for drilled Surfaces: A review | |
| Chethan et al. | Parametric optimization in drilling EN-8 tool steel and drill wear monitoring using machine vision applied with Taguchi method | |
| Sung et al. | SIMULATION APPROACH FOR SURFACE ROUGHNESS INTERVAL PREDICTION IN FINISH TURNING. | |
| Kant et al. | Parametric modeling in drilling of die steels using Taguchi method based response surface analysis | |
| Toledo et al. | Performance of wiper geometry carbide tools in face milling of AISI 1045 steel | |
| Amin et al. | The effect of preheating of work material on chatter during end milling of medium carbon steel performed on a vertical machining center (VMC) | |
| Lee et al. | Detection of fracture in ceramic cutting tools from workpiece profile signature using image processing and fast Fourier transform | |
| Tangjitsitcharoen et al. | Hybrid monitoring of chip formation and straightness in CNC turning by utilizing daubechies wavelet transform | |
| Das et al. | Surface roughness analysis of hardened steel using TiN coated ceramic inserts | |
| Tangjitsitcharoen | Advance in detection system to improve the stability and capability of CNC turning process | |
| Sung et al. | Effect of wedge angle on surface roughness in finish turning: analytical and experimental study | |
| Cerce et al. | Novel spatial cutting tool-wear measurement system development and its evaluation | |
| Jouini et al. | Relevance of roughness parameters of surface finish in precision hard turning | |
| Khaisar et al. | Prediction of tool wear during turning of EN9 work material against coated carbide insert using vibration signal processing | |
| Cheng et al. | A new approach for predicting wear overlap geometry in ball end finish milling | |
| Krolczyk et al. | Influence of technological cutting parameters on surface texture of austenitic stainless steel |