scholarly journals Real-time tool condition monitoring using wavelet transforms and fuzzy techniques

2000 ◽  
Vol 30 (3) ◽  
pp. 352-357 ◽  
Author(s):  
Jun Wang ◽  
Shiu Kit Tso ◽  
Xiaoli Li
Keyword(s):  
Real Time ◽  
Condition Monitoring ◽  
Wavelet Transforms ◽  
Tool Condition Monitoring ◽  
Tool Condition ◽  
Fuzzy Techniques

Open Platform for the Integration of Monitoring Applications

2002 ◽  
Author(s):  
Andreas Kahmen ◽  
Manfred Weck
Keyword(s):  
Control System ◽  
Machine Tool ◽  
Real Time ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Integration Platform ◽  
Open Platform ◽  
Tool Condition ◽  
Monitoring Applications ◽  
Monitoring Software

Process and machine tool condition monitoring are the keys to an increasing degree of automation and consequently to an increasing productivity in manufacturing. The realisation of monitoring functionality demands an extension of the control system. The prerequisite for these extensions are open interfaces in the NC-kernel. Nowadays controls with open NC-kernel interfaces are available on the market. However these interfaces are vendor specific solutions that do not allow the reuse of monitoring software in different controls. To overcome these limitations a platform with vendor neutral open real-time interface for the integration of monitoring functionality into the NC-kernel is presented in this paper. Additionally two realisations of the integration platform for different target systems are described.

scholarly journals Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

2012 ◽  
Vol 364 ◽  
pp. 012091 ◽  
Author(s):  
S Sztendel ◽  
C Pislaru ◽  
A P Longstaff ◽  
S Fletcher ◽  
A Myers
Keyword(s):  
Machine Tool ◽  
Real Time ◽  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Time System ◽  
Real Time System ◽  
Tool Condition ◽  
Five Axis

scholarly journals INTELLIGENT MACHINING: REAL-TIME TOOL CONDITION MONITORING AND INTELLIGENT ADAPTIVE CONTROL SYSTEMS

2018 ◽  
Vol Vol.18 (No.1) ◽  
pp. 5-18 ◽  
Author(s):  
M. HASSAN ◽  
A. SADEK ◽  
M.H. ATTIA ◽  
V. THOMSON
Keyword(s):  
Adaptive Control ◽  
Real Time ◽  
Condition Monitoring ◽  
High Speed ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Tool Condition Monitoring ◽  
Cnc Machine ◽  
Machining Processes ◽  
Tool Condition

Unmanned manufacturing systems has recently gained great interest due to the ever increasing requirements of optimized machining for the realization of the fourth industrial revolution in manufacturing ‘Industry 4.0’. Real-time tool condition monitoring (TCM) and adaptive control (AC) machining system are essential technologies to achieve the required industrial competitive advantage, in terms of reducing cost, increasing productivity, improving quality, and preventing damage to the machined part. New AC systems aim at controlling the process parameters, based on estimating the effects of the sensed real-time machining load on the tool and part integrity. Such an aspect cannot be directly monitored during the machining operation in an industrial environment, which necessitates developing new intelligent model-based process controllers. The new generations of TCM systems target accurate detection of systematic tool wear growth, as well as the prediction of sudden tool failure before damage to the part takes place. This requires applying advanced signal processing techniques to multi-sensor feedback signals, in addition to using ultra-high speed controllers to facilitate robust online decision making within the very short time span (in the order of 10 ms) for high speed machining processes. The development of new generations of Intelligent AC and TCM systems involves developing robust and swift communication of such systems with the CNC machine controller. However, further research is needed to develop the industrial internet of things (IIOT) readiness of such systems, which provides a tremendous potential for increased process reliability, efficiency and sustainability.

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