scholarly journals Expert System Based on Integrated Fuzzy AHP for Automatic Cutting Tool Selection

2019 ◽  
Vol 9 (20) ◽  
pp. 4308 ◽  
Author(s):  
Xuan Lan Phung ◽  
Hoanh Son Truong ◽  
Ngoc Tam Bui
Keyword(s):  
Expert System ◽  
Cutting Tool ◽  
Fuzzy Ahp ◽  
Cutting Tools ◽  
Multicriteria Decision Making ◽  
Uncertain Information ◽  
Tool Selection ◽  
Power Requirement ◽  
High Productivity ◽  
Workpiece Stability

Cutting tool selection plays an important role in achieving reliable quality and high productivity work, and for controlling the total cost of manufacturing. However, it is complicated for process planners to choose the optimal cutting tool when faced with the choice of multiple cutting tools, multiple conflict criteria, and uncertain information. This paper presents an effective method for automatically selecting a cutting tool based on the machining feature characteristics. The optimal cutting tool type is first selected using a proposed multicriteria decision-making method with integrated fuzzy analytical hierarchy process (AHP). The inputs of this process are the feature dimensions, workpiece stability, feature quality, specific machining type, and tool access direction, which determine the cutting tool type priority after evaluating many criteria, such as the material removal capacity, tool cost, power requirement, and flexibility. Expert judgments on the criteria or attributes are collected to determine their weights. The cutting tool types are ranked in ascending order by priority. Then, the rule-based method is applied to determine other specific characteristics of the cutting tool. Cutting tool data are collected from world-leading cutting tool manufacturer, Sandvik, among others. An expert system is established, and an example is given to describe the method and its effectiveness.

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.

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.

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.

Cutting Efficiency by Drilling with Tools from Different Materials

2012 ◽  
Vol 538-541 ◽  
pp. 1327-1331 ◽  
Author(s):  
Ivan Mrkvica ◽  
Miroslav Janoš ◽  
Petr Sysel
Keyword(s):  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Efficiency ◽  
High Productivity

Development of cutting tools is basic condition for rationalization of process cutting because it goes out from need of processing new constructional materials. From view of tool it takes application progressive cutting materials. Cutting tools so relevantly make for accomplishment main demand on methods of cutting; it is provision of high productivity production and attainment of desideration of finish surface. It is known, that cutting property of cutting tool is influence by many factors.

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.

scholarly journals Evaluation of Cutting-Tool Coating on the Surface Roughness and Hole Dimensional Tolerances during Drilling of Al6061-T651 Alloy

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1783
Author(s):  
Hamza A. Al-Tameemi ◽  
Thamir Al-Dulaimi ◽  
Michael Oluwatobiloba Awe ◽  
Shubham Sharma ◽  
Danil Yurievich Pimenov ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Good Practice ◽  
Cutting Tools ◽  
Statistical Design ◽  
Cutting Parameters ◽  
Statistical Design Of Experiments ◽  
Hole Quality ◽  
Coated Tools ◽  
Tool Coating

Aluminum alloys are soft and have low melting temperatures; therefore, machining them often results in cut material fusing to the cutting tool due to heat and friction, and thus lowering the hole quality. A good practice is to use coated cutting tools to overcome such issues and maintain good hole quality. Therefore, the current study investigates the effect of cutting parameters (spindle speed and feed rate) and three types of cutting-tool coating (TiN/TiAlN, TiAlN, and TiN) on the surface finish, form, and dimensional tolerances of holes drilled in Al6061-T651 alloy. The study employed statistical design of experiments and ANOVA (analysis of variance) to evaluate the contribution of each of the input parameters on the measured hole-quality outputs (surface-roughness metrics Ra and Rz, hole size, circularity, perpendicularity, and cylindricity). The highest surface roughness occurred when using TiN-coated tools. All holes in this study were oversized regardless of the tool coating or cutting parameters used. TiN tools, which have a lower coating hardness, gave lower hole circularity at the entry and higher cylindricity, while TiN/TiAlN and TiAlN seemed to be more effective in reducing hole particularity when drilling at higher spindle speeds. Finally, optical microscopes revealed that a built-up edge and adhesions were most likely to form on TiN-coated tools due to TiN’s chemical affinity and low oxidation temperature compared to the TiN/TiAlN and TiAlN coatings.

scholarly journals Remaining Useful Life Prediction of Cutting Tools Using an Inverse Gaussian Process Model

2021 ◽  
Vol 11 (11) ◽  
pp. 5011
Author(s):  
Yuanxing Huang ◽  
Zhiyuan Lu ◽  
Wei Dai ◽  
Weifang Zhang ◽  
Bin Wang
Keyword(s):  
Surface Roughness ◽  
Failure Criterion ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Remaining Useful Life ◽  
Model Parameters ◽  
Inverse Gaussian ◽  
Wear Process ◽  
Useful Life ◽  
Dynamic Wear

In manufacturing, cutting tools gradually wear out during the cutting process and decrease in cutting precision. A cutting tool has to be replaced if its degradation exceeds a certain threshold, which is determined by the required cutting precision. To effectively schedule production and maintenance actions, it is vital to model the wear process of cutting tools and predict their remaining useful life (RUL). However, it is difficult to determine the RUL of cutting tools with cutting precision as a failure criterion, as cutting precision is not directly measurable. This paper proposed a RUL prediction method for a cutting tool, developed based on a degradation model, with the roughness of the cutting surface as a failure criterion. The surface roughness was linked to the wearing process of a cutting tool through a random threshold, and accounts for the impact of the dynamic working environment and variable materials of working pieces. The wear process is modeled using a random-effects inverse Gaussian (IG) process. The degradation rate is assumed to be unit-specific, considering the dynamic wear mechanism and a heterogeneous population. To adaptively update the model parameters for online RUL prediction, an expectation–maximization (EM) algorithm has been developed. The proposed method is illustrated using an example study. The experiments were performed on specimens of 7109 aluminum alloy by milling in the normalized state. The results reveal that the proposed method effectively evaluates the RUL of cutting tools according to the specified surface roughness, therefore improving cutting quality and efficiency.

Cutting Tool Wear and Mechanisms of Chip Formation During High-Speed Machining of Compacted Graphite Iron

2007 ◽  
Author(s):  
Niniza S. P. Dlamini ◽  
Iakovos Sigalas ◽  
Andreas Koursaris
Keyword(s):  
Tool Wear ◽  
Surface Finish ◽  
Failure Criterion ◽  
Cutting Tool ◽  
Flank Wear ◽  
Cutting Tools ◽  
Compacted Graphite Iron ◽  
Crater Wear ◽  
Compacted Graphite ◽  
Cutting Speeds

Cutting tool wear of polycrystalline cubic boron nitride (PcBN) tools was investigated in oblique turning experiments when machining compacted graphite iron at high cutting speeds, with the intention of elucidating the failure mechanisms of the cutting tools and presenting an analysis of the chip formation process. Dry finish turning experiments were conducted in a CNC lathe at cutting speeds in the range of 500–800m/min, at a feed rate of 0.05mm/rev and depth of cut of 0.2mm. Two different tool end-of-life criteria were used: a maximum flank wear scar size of 0.3mm (flank wear failure criterion) or loss of cutting edge due to rapid crater wear to a point where the cutting tool cannot machine with an acceptable surface finish (surface finish criterion). At high cutting speeds, the cutting tools failed prior to reaching the flank wear failure criterion due to rapid crater wear on the rake face of the cutting tools. Chip analysis, using SEM, revealed shear localized chips, with adiabatic shear bands produced in the primary and secondary shear zones.

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