Micro-milling represents a versatile and fast manufacturing process suitable for production of fully 3D micro-components. Such components are demanded for a vast number of industrial applications including safety systems, environmental sensors, personalized medical devices or micro-lenses and mirrors. The ability of micro-milling to process a wide range of materials makes it one of the best candidates to take a leading position in micromanufacturing. However, so far it does not seem to happen. By discussion with various industrialists, low predictability of micro-milling process was identified as the major limiting factor. This is mainly because of strong effects of the tool tolerances and process uncertainties on machining performance. Although, these issues are well known, they are not reflected by the current modelling methods used in micro-milling. Therefore, the research presented in this thesis mainly concentrates on development of a method allowing a prediction of the tool life in manner of tool breakage probability. Another important criterion which must be fulfilled is the method applicability to industrial applications. This means that the method must give sufficiently accurate prediction in reasonable time with minimum effort and interactions with day-to-day manufacturing process. The criteria listed above led to development of a new method based on analytically/numerical modelling techniques combined with an analysis of real tool variations and process uncertainty. Although, the method is presented in a relatively basic form, without considering some of the important factors, it shows high potential for industrial applications. Possibility of further implementation of additional factors is also discussed in this thesis. Additionally, some of the modelling techniques presented in this thesis are assumed to be suitable for application during designing of micro end-mills. Therefore, in the last part of this thesis is presented a systematic methodology for designing of micro end-mills. This method is based on knowledge and experience gained during this research.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:566042 |
| Date | January 2012 |
| Creators | Zdebski, Daniel |
| Contributors | Stephenson, David J.; Allen, David |
| Publisher | Cranfield University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://dspace.lib.cranfield.ac.uk/handle/1826/7789 |
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