Intelligent Real-Time Predictive Diagnostics for Cutting Tools and Supervisory Control of Machining Operations

1993 ◽  
Vol 115 (3) ◽  
pp. 268-277 ◽  
Author(s):  
K. Ramamurthi ◽  
C. L. Hough
Keyword(s):  
Real Time ◽  
Metal Cutting ◽  
Failure Modes ◽  
Cutting Tools ◽  
Diagnostic System ◽  
Training Time ◽  
Process Diagnosis ◽  
Modes Of Failure ◽  
On Line ◽  
Cutting Processes

Machining economics may be improved by automating the replacement of cutting tools. In-process diagnosis of the cutting tool using multiple sensors is essential for such automation. In this study, an intelligent real-time diagnostic system is developed and applied towards that objective. A generalized Machining Influence Diagram (MID) is formulated for modeling different modes of failure in conventional metal cutting processes. A faster algorithm for this model is developed to solve the diagnostic problem in real-time applications. A formal methodology is outlined to tune the knowledge base during training with a reduction in training time. Finally, the system is implemented on a drilling machine and evaluated on-line. The on-line response is well within the desired response time of actual production lines. The instance and the accuracy of diagnosis are quite promising. In cases where drill wear is not diagnosed in a timely manner, the system predicts wear induced failure and vice versa. By diagnosing at least one of the two failure modes, the system is able to prevent any abrupt failure of the drill during machining.

Adaptive Control for the Metal Cutting Process

2020 ◽  
Vol 51 ◽  
pp. 1-7
Author(s):  
Viktors Gutakovskis ◽  
Eriks Gerins ◽  
Vytenis Naginevicius ◽  
Vladimirs Gudakovskis ◽  
Esmeralda Styps ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Real Time ◽  
Metal Cutting ◽  
Actual Condition ◽  
Operating Parameters ◽  
Production Environment ◽  
Tool Materials ◽  
On Line ◽  
Cutting Processes

The adaptive control of metal cutting processes is a logical extension of the CNC systems. In CNC systems of metal-cutting processes the machining variables (e.g., the cutting speed and feedrate) are prescribed by the part programmer. The determination of these variables depends on experience and knowledge regarding the workpiece and tool materials, coolant conditions, and other factors.The determination of these operating parameters depends on experience and knowledgeregarding the workpiece and tool materials, coolant conditions, and other factors. By contrast,the main idea in adaptive control is the improvement of the production rate, or the reductionof machining costs, by calculation and setting of the optimal operating parameters duringmachining itself. This calculation is based upon measurements of process variables in real time and is followed by a subsequent on-line adjustment of the machining variables subject to constraints with the objective to optimize the performance of the overall system.The adaptive control is basically a feedback system, in which the operatingparameters automatically adapt themselves to actual condition of the process. AC system formachine tools can be classified into two categories:1.Adaptive control with optimization(ACO);2.Adaptive control with constraints(ACC);ACO refers to systems in which a given performance index (usually an economicfunction) is extremized subject to process and system constraints. With ACC, the machiningparameters are maximized within a prescribed region bounded by process and systemconstraints, such as maximum torque or power. ACC systems, however, do not use aperformance index. In both systems an adaptation strategy is used to vary the operatingparameters in real time cutting progresses. Although there has been considerable research onthe development of ACO systems, few, if any, of these systems are used in practice. The major problems with such systems have been difficulties in defining realistic indexes of performance and the lack of suitable sensors which can reliably measure on-line thenecessary parameters in a production environment. The objective of most AC systems isimprovement in productivity, which is achieved by increasing the metal removal rate (MRR)during rough cutting operations. The increases in productivity range from approximately 20 to 80 percent and clearly depend on the material being machined and the complexity of the part tobe produced.

Method for Evaluating Machining Toolholder-Spindle Unbalance Due to Chips at the Toolholder Interface

2010 ◽  
Author(s):  
John Agapiou
Keyword(s):  
Real Time ◽  
Process Monitoring ◽  
Diagnostic System ◽  
Machining Process ◽  
Monitoring Method ◽  
Spindle System ◽  
On Line

Machining process monitoring method is developed for detecting and diagnosis of the presence of chips at the toolholder-spindle interface. Although toolholders can be simply balanced before they are placed in the spindle, there can be some balancing problems remaining when one or more loose machining chips are attached at the toolholder-spindle interface(s) during a tool change. A method is developed by considering the natural and geometric unbalances of the toolholder-spindle system combined with an analysis of the toolholder tilt due to the presence of loose machining chips around the spindle. The method can be integrated on-line as a real-time expert diagnostic system for toolholder tilt due to the presence of loose machining chips at the spindle nose. The expert diagnostic system makes intelligent decisions on toolholder unbalance and concerns with chips at the interface that result in unwanted tilting and vibrations. The tool unbalance algorithm was able to monitor the toolholder tilting according to the results of this study.

scholarly journals Prediction of Surface Roughness When End MillingTi6Al4VAlloy Using Adaptive Neurofuzzy Inference System

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Salah Al-Zubaidi ◽  
Jaharah A. Ghani ◽  
Che Hassan Che Haron
Keyword(s):  
Surface Roughness ◽  
Metal Cutting ◽  
End Milling ◽  
Cutting Tools ◽  
Computing Methods ◽  
Milling Process ◽  
Dry Cutting ◽  
Inference System ◽  
Cutting Processes ◽  
Adaptive Neurofuzzy Inference System

Surface roughness is considered as the quality index of the machine parts. Many diverse techniques have been applied in modelling metal cutting processes. Previous studies have revealed that artificial intelligence techniques are novel soft computing methods which fit the solution of nonlinear and complex problems like metal cutting processes. The present study used adaptive neurofuzzy inference system for the purpose of predicting the surface roughness when end millingTi6Al4Valloy with coated (PVD) and uncoated cutting tools under dry cutting conditions. Real experimental results have been used for training and testing ofANFISmodels, and the best model was selected based on minimum root mean square error. A generalized bell-shaped function has been adopted as a membership function for the modelling process, and its numbers were changed from 2 to 5. The findings provided evidence of the capability ofANFISin modelling surface roughness in end milling process and obtainment of good matching between experimental and predicted results.

Real Time Monitoring of Cutting Chatter Based on Fuzzy Hidden Markov Models

2006 ◽  
Vol 532-533 ◽  
pp. 1160-1163
Author(s):  
Chun Liang Zhang ◽  
Li Ping Chen
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Real Time ◽  
Metal Cutting ◽  
Hidden Markov ◽  
Cnc Machine ◽  
Real Time Monitoring ◽  
Time Frequency ◽  
Cutting Chatter ◽  
Cutting Processes

The full automation of machine tools has gained substantial importance in manufacturing industries in recent years, as machining technology has progressed from manually operated production machines to highly advanced and sophisticated CNC machine tool. Whereas manufacturing technology has moved to the stage of automation, there is still an unsolved problem in metal cutting processes: cutting chatter. Due to its complexity, thus cutting chatter is still the primary problem in metal cutting processes. According to the characteristic of cutting chatter, a real time monitoring technique of cutting chatter based on fuzzy hidden Markov model (FHMM) was presented. Hidden Markov model (HMM) is a state-of-the-art technique for speech recognition because of its elegant mathematical structure and the availability of computer implementation of these models. In this paper, the fuzzy EM algorithm was used to the Baum-Welch algorithm in the HMM method, and the strategy of time frequency feature extraction to non-stability signal was described. The experimental results show that the proposed method is feasible and effective for the monitoring of cutting chatter in the metal cutting processes.

Heat Conduction Analysis of Coated Cutting Tools with Temperature-Dependent Properties

2009 ◽  
Vol 69-70 ◽  
pp. 389-393 ◽  
Author(s):  
S.J. Zhang ◽  
Zhan Qiang Liu
Keyword(s):  
Heat Conduction ◽  
Metal Cutting ◽  
Cutting Tools ◽  
Cutting Temperature ◽  
Temperature Dependent ◽  
Machined Surface ◽  
Average Temperature ◽  
Coated Tools ◽  
Temperature Dependent Properties ◽  
Cutting Processes

The heat generation during metal cutting processes affects accuracy of the machined surface and strongly influences cutting forces and tool wear. Material property of coated tools is one of the most important factors effecting heat conduction and temperature on the rake face of coated tools. To find the action of thermal properties of coated cutting tools on cutting temperature, the temperature distributions were obtained with temperature-dependent properties and temperature-independent properties of coated tools using numerical method. The results indicated that temperature-dependent properties should be considered when calculating cutting temperature. To simplify calculation, selecting the thermal conductivities at average temperature to substitute for temperature-dependent properties can reduce calculating error. The conclusion provides a methodology for analysis of cutting temperature of coated tools, design of cutting tools and analysis of thermal stress within coated tools in manufacturing industries.

Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring

1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant
Keyword(s):  
Computer Architecture ◽  
Real Time ◽  
Data Abstraction ◽  
Monitoring Strategy ◽  
Intelligent Monitoring ◽  
Patient Status ◽  
On Line ◽  
Main Components ◽  
And Control ◽  
Adaptive Signal

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.

On-line testing as a new method of student knowledge evaluation

2018 ◽  
Vol 22 (2) ◽  
pp. 353-356
Author(s):  
V.P. Kovalchuk ◽  
I.M. Kovalenko ◽  
S.V. Kovalenko ◽  
V.M. Burkot ◽  
V.O. Kovalenko
Keyword(s):  
Information Technologies ◽  
English Language ◽  
Educational Process ◽  
Personality Testing ◽  
Online Testing ◽  
Training Time ◽  
Internet Resources ◽  
New Information ◽  
On Line ◽  
Use Of The Internet

Innovations change the world in all spheres of life, and education is not an exception. Modern requirements of time put us new challenges that require the use of new information technologies at all stages of the educational process in higher education institutions, in particular the use of the Internet. In addition, it has been noted that Internet resources increase motivation and contribute to the formation of a fully developed personality. Testing and evaluating students' knowledge and abilities is an integral part of the credit-module system. One of the forms of evaluation of the initial level of knowledge, consolidation and improvement of assimilation of information is testing. It should be noted that in a number of countries, testing has shifted traditional forms of control — oral and written exams and interviews. However, in Ukraine, educators remain adherents of a combination of testing and classical analysis of material. It allows the most efficient distribution of the training time of a practical class, 100% control of the knowledge and the effectiveness of mastering the material of all the students of the academic group. Technical progress stimulates the search for new variants and possibilities of testing, its various variations. One of the options that can help solve this problem was a smartphone. In order to facilitate the work of the teacher at the Department of Microbiology, an online testing system with the use of smartphones was introduced. Online testing is conducted among students with Ukrainian and English language training. With the Google Forms platform, the teacher creates a form which contains the student's records and tests. Students directly from the teacher get a link to fill out an online form directly at the lesson. For testing, a database containing standard KROK-1 licensed test tasks is used. The form can contain any number of test tasks that are in arbitrary order, as well as a changed order of distractors, which makes it impossible to write off. At the same time, all students are in the same conditions: all write one option. After submitting the form, the student receives a notification that his response is recorded. Re-linking is not possible. In turn, the teacher receives a message on the result of the test in the table — the ratio of correct answers to the total number of questions, as well as options for their answers. First and foremost, questions are displayed on which students gave the largest number of incorrect answers. This allows the topic to be considered in the process of discussion of the most difficult tasks from the students perspective, and in the future it will allow more efficiently to create forms for on-line tests and to focus on these issues.

Sign in / Sign up

Export Citation Format

Share Document