scholarly journals Using Fuzzy Control for Feed Rate Scheduling of Computer Numerical Control Machine Tools

2021 ◽  
Vol 11 (10) ◽  
pp. 4701
Author(s):  
Cheng-Jian Lin ◽  
Chun-Hui Lin ◽  
Shyh-Hau Wang

In industrial processing, workpiece quality and processing time have recently become important issues. To improve the machining accuracy and reduce the cutting time, the cutting feed rate will have a significant impact. Therefore, how to plan a dynamic cutting feed rate is very important. In this study, a fuzzy control system for feed rate scheduling based on the curvature and curvature variation is proposed. The proposed system is implemented in actual cutting, and to verify the data an optical three-dimensional scanner is used to measure the cutting trajectory of the workpiece. Experimental results prove that the proposed fuzzy control system for dynamic cutting feed rate scheduling increases the cutting accuracy by 41.8% under the same cutting time; moreover, it decreases the cutting time by 50.8% under approximately the same cutting accuracy.

2021 ◽  
Author(s):  
Cheng-Jian Lin ◽  
Chun-Hui Lin ◽  
Shyh-Hau Wang

Abstract In industrial processing, workpiece quality and processing time have become important issues lately. Fortunately, dynamic cutting feedrate scheduling has been proposed to improve machining accuracy and decrease cutting time. Studies have shown that the curvature and cutting feedrate significantly influence the machining accuracy. Therefore, the present study proposes a fuzzy control system for feedrate scheduling based on the curvature and curvature variation. The proposed system is implemented in actual cutting, and an optical three-dimensional scanner is performed as a verification to measure the cutting trajectory of the workpiece. Experimental results prove that the proposed fuzzy control system for dynamic cutting feedrate scheduling increases the cutting accuracy by 43% under the same cutting time; moreover, it decreases the cutting time by 49% under the same cutting accuracy.


Author(s):  
Rodolfo E. Haber-Guerra ◽  
Rodolfo Haber-Haber ◽  
Diego Martín Andrés ◽  
Angel Alique Palomar

The high-performance drilling (HPD) process has a significant impact on production in many industries, such as the automotive, die/mold and aerospace industries. However, cutting conditions for drilling are generally chosen from a machining-data handbook, requiring operator experience and skill. In order to improve drilling efficiency while preserving tool life, the current study focuses on the design and implementation of a simple, optimal fuzzy-control system for drilling force. The main topic of this study is the design and implementation of a networked fuzzy controller. The control system consists of a two-input (force error and change of error), single-output (feed-rate increment) fuzzy controller with nine control rules, the sup-product compositional operator for the compositional rule of inference, and the center of area as the defuzzification method. The control algorithm is connected to the process through a multipoint interface (MPI) bus, a proprietary programming, and communication interface for peer-to-peer networking that resembles the PROFIBUS protocol. The output (i.e., feed-rate) signal is transmitted through the MPI; therefore, network-induced delay is unavoidable. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) criterion. The goal is to obtain the optimal tuning parameters for the input scaling factors while minimizing the ITAE performance index. In this study, a step in the force reference signal is considered a disturbance, and the goal is to assess how well the system follows set-point changes using the ITAE criterion. The optimization is performed using the Nelder–Mead simplex (direct search) method. The main advantage of the approach presented herein is the design of a simple fuzzy controller using a known maximum allowable delay to deal with uncertainties and nonlinearities in the drilling process and delays in the network-based application. The results demonstrate that the proposed control strategy provides an excellent transient response without overshoot and a slightly higher drilling time than the CNC working alone (uncontrolled). A major issue in high performance drilling is the increase in cutting force and torque that occurs as the drill depth increases. Therefore, the fuzzy-control system reduces the influence of these factors, thus eliminating the risk of rapid drill wear and catastrophic drill breakage.


Author(s):  
Rodolfo E. Haber ◽  
Rodolfo Haber-Haber ◽  
Angel Escribano ◽  
Javier Escribano

In order to improve drilling efficiency while preserving tool life, the current study focuses on the design and implementation of a simple, optimal fuzzy-control system for drilling force. The main topic of this study is the design and implementation of a networked fuzzy controller. The control system consists of a two-input (force error and change of error), single-output (feed-rate increment) fuzzy controller. The control algorithm is connected to the process through a multipoint interface (MPI) bus. The output (i.e., feed-rate) signal is transmitted through the MPI; therefore, network-induced delay is unavoidable. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) criterion. The main advantage of the approach presented herein is the design of a simple fuzzy controller using a known maximum allowable delay to deal with uncertainties and nonlinearities in the drilling process and delays in the network-based application. The results demonstrate that the proposed control strategy provides an excellent transient response without overshoot and a slightly higher drilling time than the CNC working alone (uncontrolled). Therefore, the fuzzy-control system reduces the influence of the increase in cutting force and torque that occurs as the drill depth increases, thus eliminating the risk of rapid drill wear and catastrophic drill breakage.


2014 ◽  
Vol 1039 ◽  
pp. 403-408
Author(s):  
Shu Zhen Yang ◽  
Wei Jin ◽  
Yu Jie Bai

In this paper, a control system based on the prediction of processing flow in Abrasive flow machining is designed. In this system,flow is predicted by an improved GM(1,1) model in conformation of background value. Combined with fuzzy control system, it can adapt the pressure to meet the processing requirement automatically. Experiments proved that the improved GM(1,1) model can predict the processing flow accuratly, and the fuzzy control system based on grey prediction can improve the machining accuracy of micro-hole AFM effectively.


2021 ◽  
Vol 57 (1) ◽  
pp. 528-536
Author(s):  
Ghunter Paulo Viajante ◽  
Eric Nery Chaves ◽  
Luis Carlos Miranda ◽  
Marcos Antonio A. de Freitas ◽  
Carlos Antunes de Queiroz ◽  
...  

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Zhi LIU ◽  
Ardashir Mohammadzadeh ◽  
Hamza Turabieh ◽  
Majdi Mafarja ◽  
Shahab S. Band ◽  
...  

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