A1 Journal article (refereed), original research

An adaptive fuzzy control system to maximize rough turning productivity and avoid the onset of instability


Publication Details
Authors: Ratava Juho, Rikkonen Mikko, Ryynänen Ville, Leppänen Johanna, Lindh Tuomo, Varis Juha, Sihvo Inga
Publication year: 2011
Language: English
Related Journal or Series Information: International Journal of Advanced Manufacturing Technology
Volume number: 53
Issue number: 1-4
ISSN: 0268-3768
JUFO-Level of this publication: 1
Open Access: Not an Open Access publication

Abstract
This paper presents a new method to improve cutting efficiency for steel rough turning. To date, most efforts aimed at improving productivity during cutting operations have concentrated on optimizing material handling to and from the machinery. Here, the focus is on improving the efficiency of the turning operation itself. The approach is to control feed rate to raise machine power to a maximum safe level while avoiding the onset of cutting instability. The measure of machine power comes directly from the spindle motor and is held below the cutting machine's power capacity. Detecting the onset of instability relies on interpreting data that come from installed instrumentation. A fuzzy inference system processes the inputs and makes the final control decisions. The prototype system was tuned using data collected in a variety of cutting situations. Subsequent testing of the tuned control system showed that it was capable of successfully maximizing power usage while still avoiding the onset of instability.

Last updated on 2017-22-03 at 14:43