Ontology-based modeling of process selection knowledge for machining feature

One of the major activities in process planning is to decide the most appropriate machining methods for a part to be manufactured. Above all it requires the knowledge on feature, manufacturing capability of machining process and their relationships. As new technologies emerge, the process selection knowledge needs to be updated accordingly. Most of the systems dealing with process knowledge are not flexible enough to accommodate the relevant changes within an acceptable cost. In this paper, ontology based modeling of the process planning knowledge is presented. The core process ontology represents the process planning knowledge for machining operation selection regarding multi-axis machining feature. Firstly the concepts such as features, machining methods and process capability are modeled with relevant properties. Secondly the causal relationships between these concepts are modeled. In addition, the process selection logic is modeled by using rules which describe the match between machining requirements of a feature and process capability of a machining method. An example shows how the process ontology can be used in a reasoning mechanism for operations selection.

[1]  Richard A. Wysk,et al.  An Introduction to Automated Process Planning Systems , 1984 .

[2]  Sankha Deb,et al.  A neural network based methodology for machining operations selection in Computer-Aided Process Planning for rotationally symmetrical parts , 2006, J. Intell. Manuf..

[3]  S. S. Pande,et al.  An intelligent feature-based process planning system for prismatic parts , 2002 .

[4]  S. M. Amaitik *,et al.  STEP-based feature modeller for computer-aided process planning , 2005 .

[5]  Laurent Sabourin,et al.  OMEGA, an expert CAPP system , 1994 .

[6]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[7]  Sang Hwa Lee,et al.  A knowledge-management based process analysis system design through the classification of analysis parameters , 2012 .

[8]  Xun Xu,et al.  Computer-aided process planning – A critical review of recent developments and future trends , 2011, Int. J. Comput. Integr. Manuf..

[9]  A. Nassehi,et al.  The application of multi-agent systems for STEP-NC computer aided process planning of prismatic components , 2006 .

[10]  Masine Md. Tap,et al.  Attribute based feature recognition for machining features , 2007 .

[11]  James Gao,et al.  Product and manufacturing capability modelling in an integrated CAD/process planning environment , 1996 .

[12]  Sara McMains,et al.  CyberCut: An Internet-based CAD/CAM System , 2001, J. Comput. Inf. Sci. Eng..

[13]  Behrokh Khoshnevis,et al.  An integrated process planning system using feature reasoning and space search-based optimization , 1999 .

[14]  Kwangsoo Kim,et al.  A feature-based approach to extracting machining features , 1998, Comput. Aided Des..

[15]  Aydin Nassehi,et al.  A new software platform to support feature-based process planning for interoperable STEP-NC manufacture , 2007, Int. J. Comput. Integr. Manuf..