Modeling of Additive Manufacturing Process Relevant Feature in Layer Based Manufacturing Process Planning

doi:10.1007/s12204-012-1260-6

Abstract

Abstract: Compared with general machining processes, additive manufacturing (AM) process has stabler planning route and limited process variables and this makes it to be more easily designed and planned with knowledge based systems and computer aided techniques. Case based reasoning approach is applied to the process planning of additive manufacturing in this paper. The concept of “AM process relevant design features” is proposed after the analysis of the characteristics of AM processes. The concept is used as the basis of the knowledge representation, and AM relevant feature graph is used as the case representation schema. The case retrieval method is discussed based on this graph. The case representation of a machine arm is given to illustrate the brief process of the proposed approach.

Key words:

additive manufacturing (AM)| case based reasoning| process planning| design feature

摘要： Compared with general machining processes, additive manufacturing (AM) process has stabler planning route and limited process variables and this makes it to be more easily designed and planned with knowledge based systems and computer aided techniques. Case based reasoning approach is applied to the process planning of additive manufacturing in this paper. The concept of “AM process relevant design features” is proposed after the analysis of the characteristics of AM processes. The concept is used as the basis of the knowledge representation, and AM relevant feature graph is used as the case representation schema. The case retrieval method is discussed based on this graph. The case representation of a machine arm is given to illustrate the brief process of the proposed approach.

关键词:

additive manufacturing (AM)| case based reasoning| process planning| design feature

CLC Number:

TH 162

LIU Xi-juan (刘溪涓). Modeling of Additive Manufacturing Process Relevant Feature in Layer Based Manufacturing Process Planning[J]. Journal of shanghai Jiaotong University (Science), 2012, 17(2): 241-244.

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