scholarly journals A Neuro-Fuzzy Approach Based Tool Condition Monitoring in AISI H13 Milling

2018 ◽  
Author(s):  
Md. Shafiul Alam ◽  
Maryam Aramesh ◽  
Stephen Veldhuis
Keyword(s):  
Tool Wear ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Manufacturing Industry ◽  
Cutting Tool ◽  
Milling Process ◽  
Tool Condition Monitoring ◽  
Tool Wear Monitoring ◽  
Tool Condition ◽  
Wear Monitoring

In the manufacturing industry, cutting tool failure is a probable fault which causes damage to the cutting tools, workpiece quality and unscheduled downtime. It is very important to develop a reliable and inexpensive intelligent tool wear monitoring system for use in cutting processes. A successful monitoring system can effectively maintain machine tools, cutting tool and workpiece. In the present study, the tool condition monitoring system has been developed for Die steel (H13) milling process. Effective design of experiment and robust data acquisition system ensured the machining forces impact in the milling operation. Also, ANFIS based model has been developed based on cutting force-tool wear relationship in this research which has been implemented in the tool wear monitoring system. Prediction model shows that the developed system is accurate enough to perform an online tool wear monitoring system in the milling process.

TOOL CONDITION MONITORING SYSTEM IN SERIAL PRODUCTION CONDITIONS

2020 ◽  
Vol 4 (2) ◽  
pp. 161-168
Author(s):  
V.I. GOLOVIN ◽  
S.Yu. RADCHENKO
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Serial Production ◽  
Tool Condition ◽  
Decision Making System ◽  
Software And Hardware ◽  
Condition Monitoring System ◽  
The Cost

One of the most important tasks of serial and mass production is to maintain the continuity of the technological process in order to reduce equipment downtime and, as a result, the cost of production. One of the systems is the tool condition monitoring system. However, the solutions used today are complex software and hardware systems that are not available for most medium and small productions. The article proposes a system based on a comparative analysis of the applied tool with reference instances. The results of the analysis are sent to the decision-making system, which determines the feasibility of further use of the cutting tool for subsequent machining. An example of an experimental study of milling processing is given. The results obtained show the possibility and rationality of using this model to predict the state of the instrument.

Experimental Investigation to Predict Tool Wear and Vibration Displacement in Turning – A Base for Tool Condition Monitoring

2016 ◽  
Vol 16 (2) ◽  
pp. 103-114
Author(s):  
M. Prakash Babu ◽  
Balla Srinivasa Prasad
Keyword(s):  
Mathematical Model ◽  
Tool Wear ◽  
Condition Monitoring ◽  
Cutting Forces ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Depth Of Cut ◽  
Vibration Displacement ◽  
Tool Condition ◽  
Tool Vibrations

AbstractIn the present work investigation primarily focuses on identifying the presence of cutting tool vibrations during face turning process. For this purpose an online non-contact vibration transducer i. e. laser Doppler Vibrometer is used as part of a novel approach. The revisions in the values of cutting forces, vibrations and acoustic optic emission signals with cutting tool wear are recorded and analyzed. This paper presents a mathematical model in an attempt to understand tool lifeunder vibratory cutting conditions. Tool wear and cutting force data are collected in the dry machiningof AISI 1040 steel at different vibrationinduced test conditions. Identifying the correlation among tool wear, cutting forces and displacement due to vibration is a critical task in the present study. These results are used to predict the evolution of displacement and tool wear in the experiment. Specifically, the research tasks include: to provide an appropriate experimental data to prove the mathematical model of tool wear based on the influence of cutting tool vibrations in turning.The modeling is focused on demonstrating the scientific relationship between the process variables such as vibration displacement, vibration amplitude, feedrate, depth of cut and spindle speed while getting into account machine dynamics effect and the effects such as surface roughness and tool wear generated in the operation. Present work also concentrates on the improvement in machinability during vibration assisted turning with different cutting tools. The effect of work piece displacement due to vibration on the tool wear is critically analyzed. Finally, tool wear is established on the basis of the maximum displacement that can be tolerated in a process for an effective tool condition monitoring system.

Intelligent Tool Condition Monitoring System Based on Rough Sets and Mathematical Morphology

2007 ◽  
Vol 10-12 ◽  
pp. 722-726 ◽  
Author(s):  
Li Zhang ◽  
Shi Ming Ji ◽  
Yi Xie ◽  
Qiao Ling Yuan ◽  
Yin Dong Zhang ◽  
...  
Keyword(s):  
Tool Wear ◽  
Mathematical Morphology ◽  
Condition Monitoring ◽  
Rough Sets ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Tool Condition Monitoring ◽  
Online Tool ◽  
Tool Condition ◽  
Condition Monitoring System

The image of cutting tools provides reliable information regarding the extent of tool wear. In this paper, we propose the theory of image processing based on rough sets and mathematical morphology to analyzing the flank faces which are chosen as our monitoring object. First, through plotting the appropriate subset, the rough sets filter is used to enhancement the image of tool wear. Then, the mathematical morphology theory is applied to process the translated binary image. Finally, tool condition monitoring is realized by measuring the area of tool wear. This paper gives the corresponding monitoring principal and proposes a new algorithm to process the cutting tool image. The algorithm is also flexible and fast enough to be implemented in real time for online tool wear or tool condition monitoring.

scholarly journals A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 108
Author(s):  
Mustafa Kuntoğlu ◽  
Abdullah Aslan ◽  
Danil Yurievich Pimenov ◽  
Üsame Ali Usca ◽  
Emin Salur ◽  
...  
Keyword(s):  
Tool Wear ◽  
Condition Monitoring ◽  
Metal Cutting ◽  
Cutting Tool ◽  
Complex Structure ◽  
Tool Condition Monitoring ◽  
Monitoring Systems ◽  
Tool Condition ◽  
Condition Monitoring Systems ◽  
Cutting Zone

The complex structure of turning aggravates obtaining the desired results in terms of tool wear and surface roughness. The existence of high temperature and pressure make difficult to reach and observe the cutting area. In-direct tool condition, monitoring systems provide tracking the condition of cutting tool via several released or converted energy types, namely, heat, acoustic emission, vibration, cutting forces and motor current. Tool wear inevitably progresses during metal cutting and has a relationship with these energy types. Indirect tool condition monitoring systems use sensors situated around the cutting area to state the wear condition of the cutting tool without intervention to cutting zone. In this study, sensors mostly used in indirect tool condition monitoring systems and their correlations between tool wear are reviewed to summarize the literature survey in this field for the last two decades. The reviews about tool condition monitoring systems in turning are very limited, and relationship between measured variables such as tool wear and vibration require a detailed analysis. In this work, the main aim is to discuss the effect of sensorial data on tool wear by considering previous published papers. As a computer aided electronic and mechanical support system, tool condition monitoring paves the way for machining industry and the future and development of Industry 4.0.

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