Intelligent feature based process planning for five-axis mill-turn parts

This paper proposes a new process planning system for five-axis mill-turn parts. This system focuses on parts including both prismatic and rotational features newly defined as Prisronal parts . The three main parts of the new system are as follows: (a) a novel machining features classification based...

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Bibliographic Details
Published in:Computers in industry 2009-06, Vol.60 (5), p.296-316
Main Authors: Waiyagan, Kriangkrai, Bohez, E.L.J.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Control theory. Systems
Exact sciences and technology
Five-axis lathe
Intelligent process planning
Machining feature definition
Machining features classification
Prisronal part
Process control. Computer integrated manufacturing
Process planning
Software
Software engineering
Studies
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Summary:This paper proposes a new process planning system for five-axis mill-turn parts. This system focuses on parts including both prismatic and rotational features newly defined as Prisronal parts . The three main parts of the new system are as follows: (a) a novel machining features classification based on machining processes and number of simultaneously controlled axes of five-axis lathe; a new group code system is proposed. (b) Machining feature definition with representation; this model not only includes geometric and manufacturing data in the open layer but also includes machining processes and machining knowledge viewed as production rules of expert systems. (c) Process plan generation model; a process plan is generated based on machining features and rules. A user interactively identifies geometric entities to machining features provided as templates by the system. Machining processes and particular machining rules are designed and built-in each machining feature in the hidden layer. Auxiliary rules are provided for setup selection, precedence relation, and tool selection. Benefits of the system are fast and accurate process plan generation.
ISSN:0166-3615
1872-6194
DOI:10.1016/j.compind.2008.09.009