An intelligent process planning system for prismatic parts using STEP features

A multi-perspective dynamic feature concept in adaptive NC machining of complex freeform surfaces

“…Computer Aided Design (CAD) and integrated Numerical Control (NC) technologies have been developed for tool path optimisation [1] and machining planning with capabilities of distributed planning [2], intelligent planning [3], reconfigurable planning [4] and integration with production scheduling [5]. However, product data in existing CAD systems do not support adaptive machining planning and optimisation, where main concerns are the changes in component geometry, machining methods, parameters, resources due to various requirements and constraints in real manufacturing operations.…”

Automated process planning and cost estimation under material quality uncertainty

“…Those works evolved around feature recognition [12][13][14][15][16][17][18], knowledge representation [19][20][21][22][23][24][25] and inference engine [26,27], and integration of process planning, and upstream or downstream processes [28,29]. Some researchers applied different methods/technologies such as OPPS-PRI 2.0 system [30], genetic algorithms (GA) [31][32][33][34][35][36], imperialist competitive algorithm [37], energy-efficient oriented method [38], neural network-based system [39][40][41], fuzzy set theory/fuzzy logic method [39,42,43], agent-based methodology [44,45], Internet-based technology [46,47], functional blocks [48,49], Petri net model [50] and STEP-compliant method [51][52][53][54], just to name a few, for process planning optimization. In 2014, [55]…”

A novel methodology for cross-technology interoperability in CNC machining

“…Kumar et al introduced an intelligent and self-learning framework that could get feedback from measurement errors within the STEP-NC framework to close the manufacturing loop [21]. In 2007, Amaitik and Kilic created a STEP compliant feature based process planning system entitled ST-FeatCAPP that supported prismatic parts [22]. This was followed by the research carried out by Liu et al on prismatic parts to realise a complex feature recognition process that produces the corresponding machining operations [23].…”