Tool Life Analysis and Forecasting: 2. Forecasting Tool Life Using Neural Networks

1993 ◽  
Author(s):  
Jack P. Manata
Keyword(s):  
Neural Networks ◽  
Tool Life ◽  
Life Analysis

Development of a System for Monitoring Tool Wear Using Artificial Intelligence Techniques

2001 ◽  
Author(s):  
Rui. G. Silva ◽  
Steven J. Wilcox ◽  
Robert L. Reuben
Keyword(s):  
Neural Networks ◽  
Expert System ◽  
Tool Wear ◽  
Knowledge Base ◽  
Tool Life ◽  
Intelligent System ◽  
Process Data ◽  
Line System ◽  
Life Model ◽  
The Neural Networks

Abstract The main objective of the work reported here was to develop an intelligent condition monitoring system able to detect when a cutting tool was worn out. To accomplish this objective the use of a hybrid intelligent system, based on an expert system and two neural networks was investigated. The neural networks were employed to process data from sensors and the classifications made by the neural networks were combined with information from the knowledge base to obtain an estimate of the wear state of the tool by the expert system. The novelty of this work is mainly associated with the configuration of the developed system. The combination of sensor-based information and inference rules, results in an on-line system that can learn from experience and update the knowledge base pertaining to information associated with different cutting conditions. The neural networks resolved the problem of interpreting the complex sensor inputs while the expert system, by keeping track of previous success, estimated which of the two neural networks was more reliable. Mis-classifications were filtered out through the use of a rough but approximate estimator, Taylor’s tool life model. The system’s modular structure would make it easy to update as required for different machines and/or processes. The use of Taylor’s tool life model, although weak as a tool life estimator, proved to be crucial in achieving higher performance levels. The application of the Self Organizing Map to tool wear monitoring proved to be slightly more reliable then the Adaptive Resonance Theory neural network although overall the system made reliable, accurate estimates of the tool wear.

Predicting tool life in turning operations using neural networks and image processing

2018 ◽  
Vol 104 ◽  
pp. 503-513 ◽  
Author(s):  
T. Mikołajczyk ◽  
K. Nowicki ◽  
A. Bustillo ◽  
D. Yu Pimenov
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Tool Life ◽  
Turning Operations

Fatigue in cold-forging dies: tool life analysis

1999 ◽  
Vol 95 (1-3) ◽  
pp. 40-48 ◽  
Author(s):  
Peder Skov-Hansen ◽  
Niels Bay ◽  
Jens Grønbæk ◽  
Povl Brøndsted
Keyword(s):  
Tool Life ◽  
Cold Forging ◽  
Life Analysis

Cutting Tool Life Analysis in Heat-Pipe Assisted Drilling Operations

2015 ◽  
Vol 137 (1) ◽  
Author(s):  
Lin Zhu ◽  
Tien-Chien Jen ◽  
Yong-Bing Liu ◽  
Jie-Wen Zhao ◽  
Wei-Lai Liu ◽  
...  
Keyword(s):  
Heat Pipe ◽  
Thermal Management ◽  
Tool Life ◽  
Manufacturing Industry ◽  
Drilling Fluid ◽  
Life Extension ◽  
Cooling Conditions ◽  
Drilling Operations ◽  
Life Analysis ◽  
Fluid Cooling

This paper further focuses on the feasibility and effectiveness of heat-pipe cooling in drilling operations based on our previously related work. To achieve this, the authors used a combination of numerical analyses and experimental measurements for drilling in three different cooling conditions, i.e., dry drilling, fluid cooling, and heat-pipe cooling. The evidences obtained from the experimental study and finite element analyses were compared. The results strongly demonstrate that heat-pipe assisted cooling in drilling processes can effectively perform thermal management comparable to the fluid cooling used pervasively in the manufacturing industry, consequently offering the tool life extension.

Dynamic speed control of a machine tool with stochastic tool life: analysis and simulation

2013 ◽  
Vol 25 (5) ◽  
pp. 1153-1166 ◽  
Author(s):  
Bernard F. Lamond ◽  
Manbir S. Sodhi ◽  
Martin Noël ◽  
Ousman A. Assani
Keyword(s):  
Machine Tool ◽  
Tool Life ◽  
Speed Control ◽  
Life Analysis
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