A knowledge-based intelligent decision system for production planning - Ecole Centrale de Nantes
Article Dans Une Revue International Journal of Advanced Manufacturing Technology Année : 2017

A knowledge-based intelligent decision system for production planning

Résumé

This paper presents a Knowledge-Based Intelligent Decision system (KIDs) that takes information from a vision sensor within the manufacturing process and generates automatic planning/path-planning decisions in for collision avoidance in virtual CAM production. In this paper, the integration of KIDs approach is presented in the context of conventional multi-axis machining. The proposed system would be implemented in the conventional machining processes and, in this paper, its future implementation in the context of STEP-NC-based CAM systems is also discussed. This contribution provides secure solutions that can detect and avoid collisions using multiple solutions including tool diversion strategy, but also offers many other opportunities such as process change, sequence change, plan change, etc. A bi-turret machining scenario is used as a test case, where two tools working together possess a synchronization issue. Multi-tool synchronization cycles during preparation should take into account the management of materials left on the work part. The proposed solutions allow multiple opportunities where the machining units (blank groove) can be enriched with new associated data such as uncut material (identified visually) that may cause collisions during production. It is not limited however and therefore could be integrated into the STEP-NC in CAM simulation environment where the system is gaining acceptance from industry.
Fichier principal
Vignette du fichier
Ahmad2017.pdf (442.08 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02042551 , version 1 (06-01-2025)

Identifiants

Citer

Rafiq Ahmad, Stephane Tichadou, Jean-Yves Hascoët. A knowledge-based intelligent decision system for production planning. International Journal of Advanced Manufacturing Technology, 2017, 89 (5-8), pp.1717-1729. ⟨10.1007/s00170-016-9214-z⟩. ⟨hal-02042551⟩
31 Consultations
0 Téléchargements

Altmetric

Partager

More