Application of rough sets theory in knowledge acquisition for the cold extrusion process

Cold extrusion is a process based on intensive knowledge and experience. Many knowledge based processing technologies have been used in this area. In this paper, we have attempted to apply rough sets theory to acquire and analyse the manufacturing knowledge in the cold extrusion process. An over view of the rough sets theory was given, and several reduction algorithms based on information theory and rough sets theory were presented. After defining the cost as decision attribute, some key condition attributes that influence the cost are studied in the cold extrusion process. The detailed procedures that utilise rough sets theory for knowledge acquisitions were introduced, including data preparation, core attributes calculation, attribute reduction, core values calculation and decision rules induction. The implementation of cold extrusion knowledge acquisition using rough sets theory was presented in this paper. The advantages and disadvantages of this method were also discussed in this paper.