Automatic feature recognition and tool path strategies for enhancing accuracy in double sided incremental forming

R, Lingam and O, Prakash and Belk, J H and Reddy, N Venkata (2016) Automatic feature recognition and tool path strategies for enhancing accuracy in double sided incremental forming. International Journal of Advanced Manufacturing Technology. pp. 1-17. ISSN 0268-3768

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Incremental sheet forming (ISF) has demonstrated significant potential to form complex three-dimensional parts without using component-specific tools and is suitable for economically fabricating low-volume functional sheet metal parts. Single-point incremental forming (SPIF) uses only one tool to form components and requires additional setup to form complex geometries. Double-sided incremental forming (DSIF), using two tools (one on either side of the sheet), can form features from top and bottom of sheet in single setup. While forming components with multiple features, the accuracy of component depends on the tool path strategy used for each feature and sequence in which features are formed. Methodologies are developed to recognise features from free-form components modeled using single and/or multiple surfaces. Recognised features are sliced using horizontal, inclined or offset strategies (developed during the present work) based on the geometrical characteristics of a given feature. Selection of best-forming sequence is automated based on the relation between features and process mechanics. Results presented in this paper show that complex free-form geometries can be formed with good accuracy using proposed methodologies. Maximum deviation between the measured and ideal profiles is less than 400 μm, while using right sequence and appropriate tool path strategy.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Article
Uncontrolled Keywords: Double-sided incremental sheet forming, Feature recognition, Tool path strategies, Accuracy
Subjects: Others > Mechanics
Divisions: Department of Mechanical & Aerospace Engineering
Depositing User: Library Staff
Date Deposited: 24 May 2016 08:43
Last Modified: 16 Jan 2019 07:16
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