Selection of cutting tools and conditions of machining operations using an expert system

Arezoo, Behrooz; Ridgway, Keith; Al-Ahmari, Abdulrahman

doi:10.1016/s0166-3615(99)00051-2

Cited by 117 publications

(49 citation statements)

References 10 publications

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“…Arezoo, Ridgway and AlAhmari [8] developed a knowledge based system for selection of cutting tools and conditions of turning operations. It contains an inference engine, a user interface and explanation facility, a knowledge base and an optimization module for machining conditions.…”

Section: T R a N S A C T I O N S O N M A C H I N E L E A R N I N G A mentioning

confidence: 99%

Automatic Tool Selection System based on STEP_NC and ISO13399 Standards

Zarkti¹,

Rechia²,

Mesbahi³

2017

TMLAI

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Computer Aided Process Planning (CAPP) is considered as an essential component of Computer Integrated manufacturing (CIM) environment and it is an important interface between Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM). The purpose of the CAPP is to determine automatically the use of available resources, including machines, cutting inserts, holders, appropriate machining parameters such as cutting speed, feed rate, depth of cut, and generates automatic sequences of operations and instructions to convert a raw material into a required product, with good surface finish.The contribution of this work in CAPP field is the development of an automatic tool selection system based on STEP_NC and ISO 13399 standards for turning and milling processes. The paper presents the result of study and analysis of principal system functionalities to be considered. The system consist of four principal modules: a Tool database, feature recognition module, cutting tool selection module and a process optimization module. Finally, based on functional analysis results, the paper present the development of tool database and data tool extraction module from ISO 13399 File using oriented object programing.

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Section: T R a N S A C T I O N S O N M A C H I N E L E A R N I N G A mentioning

confidence: 99%

Automatic Tool Selection System based on STEP_NC and ISO13399 Standards

Zarkti¹,

Rechia²,

Mesbahi³

2017

TMLAI

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“…The intelligent systems such as EXTOOL and EXCATS were developed for selection of cutting tools for turning and milling [8,9]. EXTOOL does not consider any optimization procedures while EXCATS was developed using Prolog and optimization of parameters was done using dynamic programming.…”

Section: Review Of Literaturementioning

confidence: 99%

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

Saranya

Jegaraj

Kumar

et al. 2016

J. Inst. Eng. India Ser. C

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With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledgebased selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

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“…Arezoo performed a study determining the tool selection and cutting condition for machining works that utilized expert systems [5]. The developed system recommends using operators and optimal tool and cutting conditions in conjunction with a knowledge base containing tool data such as tool holders, inserts, and cutting conditions like feed, speed, and depth of cut.…”

Section: Cutting Conditions On Cutting Processesmentioning

confidence: 99%

Rule-based cutting condition recommendation system for intelligent machine tools

Lee

2009

J Mech Sci Technol

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This study relates to a rule-based cutting condition recommendation system for the implementation of intelligent machine tools. For cutting processes, information on the configuration and material of the work-piece, machine tools, and other related tools are essential, similarly as machine tools operators determine appropriate cutting conditions using their own experience along with such details. The development of computer technology has enhanced the intelligence of machine tools, allowing them to automatically calculate and determine relevant cutting data. In this study, a rulebased cutting condition recommendation system is implemented and installed on an open controller for intelligent machine tools. The cutting conditions utilized were provided by tool-makers. The conditions were recommended by classification into high-speed and common speed machining. Efficiency and accuracy has been improved by the implemented system, which is expected to be a key technology for the development of intelligent machine tools.

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Selection of cutting tools and conditions of machining operations using an expert system

Cited by 117 publications

References 10 publications

Automatic Tool Selection System based on STEP_NC and ISO13399 Standards

Automatic Tool Selection System based on STEP_NC and ISO13399 Standards

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

Rule-based cutting condition recommendation system for intelligent machine tools

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