This study proposes an automatically customizable micro process planning system that reflects the change of properties of an actual machine tool to generate optimal machining information. The system consists of an updatable machining database and a database-oriented micro process planning algorithm. A machining database is updated based on analyzing NC data that are adaptively generated for an actual machine tool by skilled process planners. From the updated machining database, a database-oriented micro process planning algorithm is generated by a decision tree and a regression tree. Machining strategy and cutting tools are determined using IF-THEN rules that are generated from the database by the decision tree method. Cutting conditions are determined from a feasible regression equation. Regression equations and selection rules of these equations are generated from the database by the regression tree method. An example of micro process planning using the generated algorithm is also shown.

To generate optimal machining information, an automatically customizable micro process planning system that reflects the change of properties of an actual machine tool is proposed. The system consists of an updatable machining database and a database oriented micro process planning algorithm. A machining database is updated based on analyzing NC data that are adaptively generated for an actual machine tool by skilled process planners. From the updated machining database, a database oriented micro process planning algorithm is generated by a decision tree and a regression tree. Machining strategy and cutting tools are determined using IF-THEN rules that are generated from the database by decision tree method. Cutting conditions were determined from a feasible regression equation. Regression equations and selection rules of these equations were generated from the database by regression tree method. The example of micro process planning using the generated algorithm is also shown.

To generate optimal machining information, a machining database and operation planning algorithm have to be customized for an actualmachine tool based on the knowledge of a skilled planner. In this paper, a method to update a machining database from NC data is proposed. The database is updated by adding machining information extracted fromNC data, based on tool path analysis. A method of generating a database-oriented planning algorithm from the machining database based on a decision tree method is also proposed. Machining strategy, cutting tool, and cutting conditions are determined based on the algorithm and k nearest neighbor method.

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Annotations on Geometric Dimensioning and Tolerancing (GD&T), surface roughness, etc. are needed for machining or measuring. However, these annotations are not used for the digital format in the product development process, nor is there any clear, explicit relationship between annotation, machining information, and measuring results. In this research, an integrated information model for design, machining, and measuring based on annotated features is proposed. A model for surface texture is also proposed because surface texture parameters are closely related to machining process parameters. A modeling system for the proposed integrated model is also implemented.