2002
DOI: 10.1088/0960-1317/12/6/311
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Development of micromachine tool prototypes for microfactories

Abstract: At present, many areas of industry have strong tendencies towards miniaturization of products. Mechanical components of these products as a rule are manufactured using conventional large-scale equipment or micromechanical equipment based on microelectronic technology (MEMS). The first method has some drawbacks because conventional large-scale equipment consumes much energy, space and material. The second method seems to be more advanced but has some limitations, for example, two-dimensional (2D) or 2.5-dimensi… Show more

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Cited by 94 publications
(45 citation statements)
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“…Many academic institutions, mainly in Europe and Asia, have been directing efforts toward the development and commercialization of smaller, even desktop-sized micro-cutting machines. These efforts have resulted in a number of compact, three to five-axis, mainly micromilling machines [7][8][9][10][11][12][13][14][15][16][17].…”
Section: Machinery For Micromillingmentioning
confidence: 99%
“…Many academic institutions, mainly in Europe and Asia, have been directing efforts toward the development and commercialization of smaller, even desktop-sized micro-cutting machines. These efforts have resulted in a number of compact, three to five-axis, mainly micromilling machines [7][8][9][10][11][12][13][14][15][16][17].…”
Section: Machinery For Micromillingmentioning
confidence: 99%
“…To manufacture this micro channel recuperator it is possible to use Micro Equipment Technology [14][15][16].…”
Section: Microchannel Recuperatormentioning
confidence: 99%
“…This paper continues the series of works on automation of micro assembly processes [3,4]. The LIRA neural classifier is proposed for texture recognition of mechanically treated metal surfaces.…”
Section: Resultsmentioning
confidence: 89%
“…The task of metal surface texture recognition is important to automate the assembly processes in micromechanics [3]. To assembly a device it is necessary to recognize the position and orientation of the work pieces to be assembled [4].…”
Section: Metal Surface Texture Recognitionmentioning
confidence: 99%
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