Intelligent Cutting Tool Selection for Milling Based on STEP-NC Machining Features

2014 ◽  
Vol 635-637 ◽  
pp. 589-593 ◽  
Author(s):  
Hua Bing Ouyang
Keyword(s):  
Cutting Tool ◽  
Cutting Tools ◽  
Nc Machining ◽  
Prototype System ◽  
Selection System ◽  
Tool Selection ◽  
Machining Features ◽  
Selection For ◽  
Base Module ◽  
Selection Of

A framework of an intelligent tool selection system for milling based on STEP-NC machining features is proposed. The main objective of the research is to develop a procedure for the selection of cutting tools. This will help the planners to select the optimal cutting tools. The proposed system consists of the knowledge base module, the inference engine, the user interface and the database. The implementation of the presented system is developed in Solidworks. An example is given to demonstrate the feasibility and efficiency of the prototype system. As a result, this research shows a high potential to aid the development of tool selection and process planning milling system.

Machining Feature Classification and Description for Intelligent Tool Selection

2013 ◽  
Vol 589-590 ◽  
pp. 643-647
Author(s):  
Hong Long Ma ◽  
Zhan Qiang Liu ◽  
Hong Tao Ye
Keyword(s):  
Cutting Tool ◽  
Cutting Tools ◽  
Object Oriented ◽  
Tool Selection ◽  
Machining Features ◽  
Rule Based ◽  
Processing Information ◽  
Efficient Processing ◽  
Object Oriented Approach ◽  
The Cost

In manufacturing process, reasonable tool selection can greatly improve the efficiency and reduce the cost of machining. In order to obtain optimized tool solutions, object-oriented approach to the classification and description of the machining features are presented in this paper. Machining features by means of object-oriented classes, attributes and methods are described. Efficient processing information for tool selection is extracted. Tool selection model based on the machining features is established. Cutting tool intelligent selection is implemented through rule-based reasoning. This work will help the process planners to select more reasonable cutting tools.

Deep learning enabled cutting tool selection for special-shaped machining features of complex products

2019 ◽  
Vol 133 ◽  
pp. 1-11 ◽  
Author(s):  
Guanghui Zhou ◽  
Xiongjun Yang ◽  
Chao Zhang ◽  
Zhi Li ◽  
Zhongdong Xiao
Keyword(s):  
Deep Learning ◽  
Cutting Tool ◽  
Tool Selection ◽  
Machining Features ◽  
Complex Products ◽  
Selection For

Research on Intelligent Tool Selection System Based on Optimization Model

2016 ◽  
Vol 693 ◽  
pp. 1765-1771
Author(s):  
Rui Wang ◽  
Wu Zhao ◽  
Chun Jing Luo ◽  
Zhi Yong Wang ◽  
Tao Luo
Keyword(s):  
Cutting Tool ◽  
Intelligent System ◽  
Cutting Tools ◽  
Optimization Methods ◽  
Database System ◽  
Prototype System ◽  
Tool Selection ◽  
Cutting Parameter ◽  
System A ◽  
Machine Shops

Over the last few decades, the range of engineering materials encountered in machine shops has increased greatly, as has the variety of cutting tools that are capable of machining these materials. The tasks of tool selection and cutting parameter recommendation for performing the operations are complex and require development of intelligent system. A cutting tool database system model is proposed in this paper. And base on the model, this paper presents a cutting tool database system for selection of cutting tools and conditions of turning operations. The model incorporates intelligent tool selection technology, optimization methods of tool selection and cutting parameter. An application example of the system was performed to demonstrate the practicability and validity of the prototype system.

Ct-SELECTOR: A Web Application for Cutting-Tool Selection in a CNC Machining Workshop

2014 ◽  
Vol 889-890 ◽  
pp. 1170-1173
Author(s):  
Pei Lu Sun ◽  
Ping Yu Jiang ◽  
Bao Quan Chen ◽  
Lei Zhang
Keyword(s):  
Tool Life ◽  
Web Application ◽  
Metal Cutting ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Parameters ◽  
Cnc Machining ◽  
Tool Selection ◽  
Selection Of

Recently in most Chinese CNC machining enterprises, the selection of cutting tools still depends on the experience of individual workers, which is hard to be inherited by others. Faced with this situation, we developed a web application for selecting proper cutting tools in CNC machining workshop, named ct-SELECTOR for short. This article introduces the main functions of the ct-SELECTOR and analyzed the three key enable technologies for realizing each function: (1) the automatic cutting-tool selection and match, (2) the optimal recommendation and management of metal cutting parameters and (3) the management and off-line prediction of tool-life. Finally, the developing architecture of the ct-SELECTOR is demonstrated, and a running example is illustrated to verify the validity and practicability of this system.

A DECISION-MAKING FRAMEWORK MODEL OF CUTTING TOOL SELECTION FOR GREEN MANUFACTURING AND ITS APPLICATION

2008 ◽  
Vol 07 (02) ◽  
pp. 257-260 ◽  
Author(s):  
XIANCHUN TAN ◽  
DACHENG LIU ◽  
CONGBO LI
Keyword(s):  
Decision Making ◽  
Cutting Tool ◽  
Main Idea ◽  
Green Manufacturing ◽  
Tool Selection ◽  
Environment Impact ◽  
Framework Model ◽  
Important Approach ◽  
Selection For ◽  
Decision Making Framework

Green manufacturing (GM in short) is beneficial to the alleviation of environment burdens. The optimization selection of tool is an important approach to improving environmental performance of cutting machining. The objective factors of decision-making problems for traditional tool selection are time, quality and cost. Based on the main idea of environmental consciousness, a decision-making framework model of GM is proposed; a multi-objective decision-making model for cutting tool selection is put forward. The objectives include Time (T), Quality (Q), Cost (C), Resources (R) and Environmental impact (E), where T aims to minimize the produce time, Q means to maximize the quality, C means to minimize the cost, R means to minimize the resource consumption and E means to minimize the environment impact respectively. Each objective is analyzed in detail and application of the Fuzzy Analysis Algorithm in the decision-making is discussed. A case study in which a practical decision-making problem of cutting tool selection for GM is analyzed and successful application of the above model shows that the model is practical.

scholarly journals Selection Of Cutting Inserts For Aluminum Alloys Machining By Using MCDM Method

2015 ◽  
Vol 66 (1) ◽  
pp. 98-101 ◽  
Author(s):  
Miloš Madić ◽  
Miroslav Radovanović ◽  
Dušan Petković ◽  
Bogdan Nedić
Keyword(s):  
Decision Making ◽  
Aluminum Alloys ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Multi Criteria Decision Making ◽  
Complex Task ◽  
Cutting Inserts ◽  
Mcdm Method ◽  
Product Assessment ◽  
Selection Of

Abstract Machining of aluminum and its alloys requires the use of cutting tools with special geometry and material. Since there exists a number of cutting tools for aluminum machining, each with unique characteristics, selection of the most appropriate cutting tool for a given application is very complex task which can be viewed as a multi-criteria decision making (MCDM) problem. This paper is focused on multi-criteria analysis of VCGT cutting inserts for aluminum alloys turning by applying recently developed MCDM method, i.e. weighted aggregated sum product assessment (WASPAS) method. The MCDM model was defined using the available catalogue data from cutting tool manufacturers.

scholarly journals Modularized Cutting Tool Selection Expert System

2014 ◽  
Vol 8 (1) ◽  
pp. 892-898
Author(s):  
Chen Wang ◽  
Wu Zhao ◽  
Ling Chen ◽  
Kai Zhang ◽  
Xin Guo
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Feature Recognition ◽  
Cutting Tool ◽  
Tool Material ◽  
Tool Selection ◽  
Type Calculation ◽  
Rule Bases ◽  
Cutting Problem ◽  
Selection Of

This paper is to present a rule-based cutting tool selecting expert system which has knowledge modules and rule bases. Besides, according to different process targets, the selection progress will apply corresponding constraints and rule modules. The logic of tool selection follows a decision-making procedure as an experienced engineers. The strategy of system is to guide the user through several standard steps: information input; feature recognition; selection of machining method; selection of tool material and type; calculation of process parameter and solving cutting problem. This system also has a modularized structure which allows adding new functions and new modules to expand knowledge base and data base. Modules involves in this system are composed of the user interface, knowledge acquisition facility, explanation facility, the knowledge base module, the inference engine and the database module.

Study on Supplier Selecting System Oriented Networked Manufacturing

2010 ◽  
Vol 44-47 ◽  
pp. 960-964
Author(s):  
Zi Xu Lui ◽  
Tian Biao Yu ◽  
Jing Qiang Zhang ◽  
Wan Shan Wang
Keyword(s):  
Theoretical Study ◽  
Selection Function ◽  
Prototype System ◽  
Supplier Evaluation ◽  
Main Function ◽  
Networked Manufacturing ◽  
Selection System ◽  
Manufacturing Environment ◽  
Function Modules ◽  
Selection Of

This paper analyzes the characteristics of supplier selection base on network manufacturing environment. The requirements of supplier evaluation and selection function of the system were analyzed too. Supplier evaluation and selection of system architecture and workflow was studied oriented networked manufacturing environment. Base on the theoretical study a prototype system was developed and the main function modules were introduced. This paper provides a theoretical and technical reference to develop efficient and practical supplier evaluation and selection system to meet the requirements of networked manufacturing.

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