Open AccessApplication of Stochastic Regression for the Configuration of Microrotary Swaging Processes
Author(s) -
Daniel Rippel,
Eric Moumi,
Michael Lütjen,
Bernd ScholzReiter,
Bernd Kuhfuß
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/360862
Subject(s) - swaging , miniaturization , process (computing) , context (archaeology) , quality (philosophy) , engineering , regression , computer science , manufacturing engineering , reliability engineering , mechanical engineering , process engineering , industrial engineering , mathematics , statistics , paleontology , philosophy , electrical engineering , epistemology , biology , operating system
In micromanufacturing, a precise adjustment of manufacturing, handling, and quality control processes constitutes an essential factor for success. The continuing miniaturization of workpieces and production devices results in ever decreasing tolerances, whereas machines and processes become increasingly more specialized. Thereby, the so-called size effects render the direct application of knowledge from the area of macromanufacturing impossible. In this context, this paper describes the application of the μ-ProPlAn method for the configuration of an infeed rotary swaging process for microcomponents. At this, the cause-effect relationships between relevant process parameters are analyzed using stochastic regression models, in order to determine cost-efficient process configurations for the manufacturing of bulk and tubular microcomponents
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