Condition based maintenance (CBM) is becoming more and more popular in equipment main-tenance. A prerequisite to widespread deployment of CBM technology and practice in industry is effective diagnostics and prognostic...Condition based maintenance (CBM) is becoming more and more popular in equipment main-tenance. A prerequisite to widespread deployment of CBM technology and practice in industry is effective diagnostics and prognostics. A dynamic Bayesian network (DBN) based prognosis method was investigated to predict the remaining useful life (RUL) for an equipment. First, a DBN based prognosis framework and specific steps for building a DBN based prognosis model were presented. Then, the corresponding inference algorithms for DBN based prognosis were provided. Finally, a prognosis procedure based on particle filtering algorithms was used to predict the RUL of drill-bits of a vertical drilling machine, which is commonly used in industrial process. Preliminary experimental results are promising.展开更多
This article describes experimental evaluations of the authors＇ previous studies on the knowledge-based system （KBS） aimed at capturing and managing CNC （Computer Numerical Control） operator knowledge. The propos...This article describes experimental evaluations of the authors＇ previous studies on the knowledge-based system （KBS） aimed at capturing and managing CNC （Computer Numerical Control） operator knowledge. The proposed KBS follow thinking steps of CNC operators when they assess machining parameters described in the CAM （Computer Aided Manufacturing） file before proceeding to CNC machining processes. Also, the decision support system equipped with expert system （ES） has been proposed to realize efficient knowledge capturing system and effective usability of captured knowledge, and to recommend actions and decisions. From the viewpoint of providing useful information, the KBS should be aware of context or constraints in which the user has to deal with. In this study, the usefulness of DSS （Decision Support System） and ES is experimentally evaluated using real cases. Comparing the results of the testing participants with and without the DSS and ES, the effectiveness and usefulness were demonstrated. In addition, it was shown that the proposed system is also useful to narrow the discrepancies between CAM and CNC operators, focusing on CNC milling operations.展开更多
Traditional five-axis tool path planning methods mostly focus on differential geometric characteristics between the cutter and the workpiece surface to increase the material removal rate(i.e.,by minimizing path length...Traditional five-axis tool path planning methods mostly focus on differential geometric characteristics between the cutter and the workpiece surface to increase the material removal rate(i.e.,by minimizing path length,improving curvature matching,maximizing local cutting width,etc.) . However,material removal rate is not only related to geometric conditions such as the local cutting width,but also constrained by feeding speed as well as the motion capacity of the five-axis machine. This research integrates machine tool kinematics and cutter-workpiece contact kinematics to present a general kinematical model for five-axis machining process. Major steps of the proposed method include:(1) to establish the forward kinematical relationship between the motion of the machine tool axes and the cutter contact point;(2) to establish a tool path optimization model for high material removal rate based on both differential geometrical property and the contact kinematics between the cutter and workpiece;(3) to convert cutter orientation and cutting direction optimization problem into a concave quadratic planning(QP) model. Tool path will finally be generated from the underlying optimal cutting direction field. Through solving the time-optimal trajectory generation problem and machining experiment,we demonstrate the validity and effectiveness of the proposed method.展开更多
文摘Condition based maintenance (CBM) is becoming more and more popular in equipment main-tenance. A prerequisite to widespread deployment of CBM technology and practice in industry is effective diagnostics and prognostics. A dynamic Bayesian network (DBN) based prognosis method was investigated to predict the remaining useful life (RUL) for an equipment. First, a DBN based prognosis framework and specific steps for building a DBN based prognosis model were presented. Then, the corresponding inference algorithms for DBN based prognosis were provided. Finally, a prognosis procedure based on particle filtering algorithms was used to predict the RUL of drill-bits of a vertical drilling machine, which is commonly used in industrial process. Preliminary experimental results are promising.
文摘This article describes experimental evaluations of the authors＇ previous studies on the knowledge-based system （KBS） aimed at capturing and managing CNC （Computer Numerical Control） operator knowledge. The proposed KBS follow thinking steps of CNC operators when they assess machining parameters described in the CAM （Computer Aided Manufacturing） file before proceeding to CNC machining processes. Also, the decision support system equipped with expert system （ES） has been proposed to realize efficient knowledge capturing system and effective usability of captured knowledge, and to recommend actions and decisions. From the viewpoint of providing useful information, the KBS should be aware of context or constraints in which the user has to deal with. In this study, the usefulness of DSS （Decision Support System） and ES is experimentally evaluated using real cases. Comparing the results of the testing participants with and without the DSS and ES, the effectiveness and usefulness were demonstrated. In addition, it was shown that the proposed system is also useful to narrow the discrepancies between CAM and CNC operators, focusing on CNC milling operations.
基金supported by the National Basic Research Program of China ("973" Program) (Grant No. 2011CB706800)the National Natural Science Foundation of China (Grant No. 50835004)the National Funds for Distinguished Young Scientists of China (Grant No. 51025518)
文摘Traditional five-axis tool path planning methods mostly focus on differential geometric characteristics between the cutter and the workpiece surface to increase the material removal rate(i.e.,by minimizing path length,improving curvature matching,maximizing local cutting width,etc.) . However,material removal rate is not only related to geometric conditions such as the local cutting width,but also constrained by feeding speed as well as the motion capacity of the five-axis machine. This research integrates machine tool kinematics and cutter-workpiece contact kinematics to present a general kinematical model for five-axis machining process. Major steps of the proposed method include:(1) to establish the forward kinematical relationship between the motion of the machine tool axes and the cutter contact point;(2) to establish a tool path optimization model for high material removal rate based on both differential geometrical property and the contact kinematics between the cutter and workpiece;(3) to convert cutter orientation and cutting direction optimization problem into a concave quadratic planning(QP) model. Tool path will finally be generated from the underlying optimal cutting direction field. Through solving the time-optimal trajectory generation problem and machining experiment,we demonstrate the validity and effectiveness of the proposed method.
