Automatic tool selection for milling operations Part 1: Cutting data generation

Author:

Carpenter I D1,Maropoulos P G1

Affiliation:

1. University of Durham School of Engineering UK

Abstract

The selection of tools and cutting data is a central activity in process planning and is often liable to an element of subjectivity. It is further complicated by the wide range of choice presented by the various operation types and the huge portfolio of cutters and inserts available from many different tool manufacturers. This paper describes a procedure to select consistently and efficiently tools for rough and finish milling operations performed on a computer numerical controlled (CNC) machining centre. A wide range of milling operations is considered, including faces, square shoulders, slots, T-slots, pockets, holes and profiles. An initial set of feasible tools is generated that satisfy the constraints of the tool type, the operation geometry, the insert geometry and carbide grade, the workpiece material and the machine tool capacity. Each tool consists of a holder and one or more indexable carbide inserts. Aggressive cutting data are generated for each feasible tool using a rapid search procedure in the permissible depth/width/feed space for good chip control. The cutting data are further refined by a set of technological constraints, which include tool life, surface finish, machine power and available spindle speeds and feeds. The overall cutting data optimization criterion is selected by the user from minimum cost, maximum production rate or predefined tool life. A new optimization criterion, called ‘harshness’, allows the user to influence the chip thickness that is achieved for any given cutter. Any feasible tools that fail to satisfy all the constraints and optimization criteria are discarded.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A knowledge-based system for end mill selection;Advances in Production Engineering & Management;2016-02-07

2. Metaheuristic approaches to tool selection optimisation;Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference - GECCO '12;2012

3. Cost-effective supervisory control system in peripheral milling using HSM;Annual Reviews in Control;2010-04

4. Object Oriented Approach in Computer Aided Process Planning;ICT Innovations 2009;2010

5. Milling Strategy Prediction with SOM Neural Network;IFAC Proceedings Volumes;2008

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3