Intelligent Automated Accessory Tool Selection System

2022 ◽  
pp. 231-238
Author(s):  
I. P. Balabanov ◽  
V. D. Ponomareva ◽  
O. N. Balabanova
Keyword(s):  
Selection System ◽  
Tool Selection

Improving Reliability and Consistency in BHA Configuration Through the Use of an Expert Tool-Selection System

2007 ◽  
Author(s):  
Robert Greenaway ◽  
Rex Burgos ◽  
Lambert Dilling ◽  
Cabe Vreeland ◽  
Stephen Bruce ◽  
...  
Keyword(s):  
Selection System ◽  
Tool Selection

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.

scholarly journals An Intelligent Tool Selection System Based on CRB and RBR

2014 ◽  
Vol 8 (1) ◽  
pp. 795-802 ◽  
Author(s):  
Rui Wang ◽  
Wu Zhao ◽  
Cunjing Luo ◽  
Zhiyong Wang ◽  
Tao Luo
Keyword(s):  
Information Management ◽  
Cutting Parameters ◽  
Database System ◽  
Database Management System ◽  
Manufacturing Industries ◽  
Machining Process ◽  
Basic Information ◽  
Selection System ◽  
Tool Selection ◽  
Manufacturing Enterprises

The manufacturing industries dealing with machining and tools' manufacturing generate a large amount of data concerning the machining process. However, in most cases, this information is not used efficiently as there is no system dedicated for storing and manipulating such data. In order to use these data to improve the efficiency and increase the benefit of machining, the cutting database system is built for these manufacturing enterprises, which can provide rational cutting parameters and tool solutions. JAVA and MYSQL are used as the base of database management system, combining XML and JavaScript technology. The intelligent tool selection model was designed, and the functions of basic information management and query were realized. It was concluded that it can commend reasonable cutting parameters and tool solutions according to machining condition input.

Intelligent Tool Selection for Machining Cylindrical Components: Part 2: Results from the Testing of the Knowledge-Based Module

1995 ◽  
Vol 209 (3) ◽  
pp. 183-192 ◽  
Author(s):  
P G Maropoulos ◽  
B Alamin
Keyword(s):  
Selection System ◽  
Tool Selection ◽  
Main Research ◽  
Knowledge Based ◽  
Testing Programme ◽  
Wide Range ◽  
Selection For ◽  
First Time ◽  
Research Assumptions ◽  
Fine Tune

This paper discusses the experimental results obtained by testing the knowledge-based module of the intelligent tool selection system (ITS_KBS). The main objectives of the testing programme were to check the essential functionality, verify the empirical rules and criteria and fine-tune the system. Although certain functions were tested on the computer, a large number of cutting tests were completed using steel components and the system's performance was assessed over a wide range of component geometries and cutting conditions. The cutting tests were successful since ITS_KBS selected tools and generated safe but efficient cutting data which worked on the machine tool the first time around in the large majority of instances. Overall, the results of the testing programme were very encouraging in that they verified the main research assumptions and fulfilled the expectations regarding functionality.

Study on Intelligent Tool Optimal Selection System in Milling

2009 ◽  
Vol 626-627 ◽  
pp. 605-610 ◽  
Author(s):  
Xi Feng Fang ◽  
T.X. Lan ◽  
Sheng Wen Zhang ◽  
W. Jia ◽  
Tong Yue Wang
Keyword(s):  
Decision Making ◽  
Fuzzy Theory ◽  
Prototype System ◽  
Optimal Selection ◽  
Selection System ◽  
Tool Selection ◽  
Rule Based ◽  
Sql Server 2000 ◽  
Development Tool ◽  
Intelligent Technology

Rule-based reasoning (RBR) and weight decision making have been widely used in a lot of decision support systems. According to the waste phenomenon of manufacturing corporations due to the reasonless use of tools during production process, and considering the characteristics of former tool selection systems, develop a tool optimal selection system with Visual Basic 6.0 as development tool and SQL Server 2000 as database developing platform. The system adopts the rule-based reasoning and weight decision-making theory, combines fuzzy theory, artificial intelligent technology and production conditions of corporations. According to the information of workpiece and processing conditions imported by users, the system can select the reasonable tools for users. The system overcomes the limitation of single theory tool selection system, simplifies reasoning mechanism and structure of knowledge base, makes programmer easy to realize, promotes operation efficiency of system, and raises the accuracy and efficiency of tool selection in actual production. A developed prototype system and an example have verified some presented techniques and the research results are the basis of the future development.

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