Research On Energy-efficient Computer Numerical Control Process Planning Based On STEP-NC

With the development of society,energy is playing more and more important role in the industry,which attracts a lot of researchers to be engaged in energy-efficient machining.Process planning is the bridge connecting design and manufacturing,and some research indicates that appropriate process planning can achieve energy-efficient machining.Energy consumption model is the precondition of energy-efficient process planning.Nowadays,most of energy consumption models aims at the characteristic during machining and manufacturing,but there lacks of the research on establishment of energy consumption model from the perspective of a part to be manufactured,so that optimizing the machining process for energy-efficiency only focuses on one or some Workingsteps.To solve this problem,this paper uses the data structure of Standard for the Exchange of Product model data-Numerical Control(STEP-NC)to build an energyconsumption model for computer numerical control(CNC)machining.This model regards the Workingstep of STEP-NC as the base to describe the machining process,and four states are built,i.e.preparation state,approaching state,leaving state,machining state.The corresponding energy consumption calculation method based on the above states are discussed.Finally,a part involving typical manufacturing features are used to verify the model.The energy consumption model based on STEP-NC is an effective tool to calculate energy demand during machining,but it cannot be used to achieve process planning.A CNC machining process ontology integrated with energy consumption knowledge is bulit to solve that.This process ontology consists of three layers,i.e.framework layer,instance layer and reasoning layer.Besides,the framework layer is divided into energy consumption knowledge sub-ontology(it can indicate the calculation method of energy consumption during machining process),extended manufacturing feature sub-ontology(it adds the geometric tolerance and roughness information based on the original manufacturing data structure),CNC machining operations sub-ontology and machining resources sub-ontology.The instance layer is the instances of the framework layer.For the reasoning layer,it represents the function of the process ontology because the output of candidate machining scheme is achieved by SWRL and SQWRL.The output of the process ontology covers the best machining scheme,which refers to the best Workingstep for manufacturing and sequence of Workingsteps.To find this,ant colony optimization(ACO)is used.The optimized model is built first,which includes optimization objective,optimization variable and constraint condition.And then the key procedure of ACO is shown in this work,where the generations of solution space and machining scheme are discussed intensively.Besides,there exists a drawback when to solve the problem with traditional ACO.The factors contributing to energy consumption have different dimensions,so that the low dimension factor will reach the final value first while the high dimension should cost much time during optimizing.To solve this problem,the idea,i.e.locally multiple iteration is used in ACO,which will generate more than one machining schemes with multiple iterations in the high factor during each iteration.A typical part is selected to test this approach,and the traditional ACO and the improved ACO are compared.The results show that the improved ACO can decrease the time of the optimization.A prototype is developed by UG NX,which can help users to select the manufacturing feature defined in STEP-NC to build a digital model of a part.And then it will output the machining scheme of the part.