Dynamic model of computer aided process planning (CAPP) for rotational components

Abstract

Though Computer Aided Process Planning (CAPP) is the key to mlegrate design and manufacturing systems, CAPP ha, not kept pace with (he development of CW and CAM syslel11~_Still a major part orihe proces,> plans l~ created manually due (0 the lock of a standard una generali/ed sy,lem to lrwl',fonTI de8ign infornlalion completely into manufacturing inii)rmalion. In this work. geol1letri~ mi'Jl111alion of a rolallOll~1 part 1, translated into manuJac!uring iniormalLon llmlligh a Data Imerch,mge FOTTllal(DXF). A feature recognition algorithm is used to recognize dirfcrcnt fcalures 0(- the par! fr0111lIS DXF file, Then each feature of the part is rccognircd using the data extracted from DXF file, O]Jlirnlz~tion of parameters is the vital stage of process planning since the economy of machmmg operation plays thc most important role in incrt'a~ing productivity and compelitl\'eness. In this work, process planning parameters for machining rotational components are also optlmi7,ed by a 'Genetic Algorithm' in Matlah environment. Here machining time is considered as the obj ecti\'e function and constraints arc machine capacity, limits 0 ('i"eedrate. depth of cut, culling speed etc. Machining timc is minimized throllgh a sent'S or gt'neTations while some genetic operators arc applied at each generation. The resuH of the work amply demonstnlles the quick eonvergi ng ahi1ity oi"genetic algorithm.