A knowledge-based auto-reasoning methodology in hole-machining process planning

2006 ◽  
Vol 57 (4) ◽  
pp. 297-304 ◽  
Author(s):  
Hao Yongtao ◽  
Ma Jingying
Keyword(s):  
Process Planning ◽  
Machining Process ◽  
Knowledge Based ◽  
Machining Process Planning ◽  
Hole Machining

A hole-machining process planning system for marine engines

2013 ◽  
Vol 32 (1) ◽  
pp. 114-123 ◽  
Author(s):  
Cheol-Soo Lee ◽  
Jae-Hyun Lee ◽  
Dong-Soo Kim ◽  
Eun-Young Heo ◽  
Dong-Won Kim
Keyword(s):  
Process Planning ◽  
Machining Process ◽  
Planning System ◽  
Process Planning System ◽  
Marine Engines ◽  
Machining Process Planning ◽  
Hole Machining

scholarly journals Decision-making for multi-criteria optimization of process planning

2019 ◽  
Vol 20 (8) ◽  
pp. 806 ◽  
Author(s):  
Laurent Delolme ◽  
Anne-Lise Antomarchi ◽  
Séverine Durieux ◽  
Emmanuel Duc
Keyword(s):  
Decision Making ◽  
Process Planning ◽  
Choice Theory ◽  
Social Choice Theory ◽  
Automatic Generation ◽  
Machining Process ◽  
Performance Criteria ◽  
Machining Time ◽  
Machining Process Planning ◽  
Productivity And Competitiveness

The objective of this work is to develop a methodology for the automatic generation of optimised and innovative machining process planning that enable aeronautical subcontractors to face current productivity and competitiveness issues. A four-step methodology is proposed, allowing the user to obtain optimised machining ranges that respect his know-how and experience and introduce innovation. This methodology is based on a representation of the decisional behaviour of the user in a given situation as well as in the face of the risk of industrialisation and broadens the formalisation of the performance of a process by taking into account other performance criteria other than machining time or overall cost. A genetic algorithm is used to generate optimized process planning. An AHP method is used to represent the decision-making process. The methodology presents the best processes generated and the use of social choice theory enables it to target the most efficient ranges to be implemented, by integrating a risk criterion to the industrialization.

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