Intelligent feature based resource selection and process planning

Samira Sadeghi (1) , Mohsen Sadeghi (2) , Ali Siadat (1) , Patrick Martin (1) , William Ziz (2)

1 LCFC - Laboratoire de Conception Fabrication Commande
2 Procton Labs

This paper presents an intelligent knowledge-based integrated manufacturing system using the STEP feature-based modeling and rule based intelligent techniques to generate suitable process plans for prismatic parts. The system carries out several stages of process planning, such as identification of the pairs of feature/tool that satisfy the required conditions, generation of the possible process plans from identified tools/machine pairs, and selection of the most interesting process plans considering the economical or timing indicators. The suitable processes plans are selected according to the acceptable range of quality, time and cost factors. Each process plan is represented in the tree format by the information items corresponding to their CNC Machine, required tools characteristics, times (machining, setup, preparatory) and the required machining sequences. The process simulation module is provided to demonstrate the different sequences of machining. After selection of suitable process plan, the G-code language used by CNC machines is generated automatically. This approach is validated through a case.

Mots clés: Process planning; STEP; Knowledge based; Integrated design; Manufacturing

Domaines: Génie mécanique [physics.class-ph]; Génie mécanique [physics.class-ph]

Samira Sadeghi, Mohsen Sadeghi, Ali Siadat, Patrick Martin, William Ziz. Intelligent feature based resource selection and process planning. Proceedings of the International Conference on PLM '10, 2012, Chapter 3: Process Development, pp.133-145. ⟨hal-00999539⟩