Automatic tool selection for rough turning operations

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.

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Design of the CNC Milling Tool Selection System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.148-149.153 ◽

2011 ◽

Vol 148-149 ◽

pp. 153-157

Author(s):

Xiu Lin Sui ◽

Na Hu ◽

Chun Hong Zhang

Keyword(s):

Selection Process ◽

Complex Surface ◽

Forward Direction ◽

Computer Applications ◽

Cnc Milling ◽

Tool Selection ◽

Milling Tool ◽

Selection For ◽

Inference Strategy ◽

Reasoning Mechanism

Knowledge base of milling feature machining based on relational database is proposed, using knowledge representation of production rules, according to the characteristics of feature machining knowledge. Tool selected reasoning mechanism and reasoning processes is presented basing the installed CNC milling tool database , and further reasoning is based on knowledge, milling tool selection method is implemented based on feature machining knowledge using the forward direction inference strategy .In the paper, a complete system of the selecting milling cutter is established. The system connects not only the theoretical knowledge but the expert’s experiences with the computer applications in order to provide a base of realizing the automatic mechanical processing. By the example of machining tool selection for complex surface, the selection process is described, and the system can select the tools to meet the processing requirements within a shot time, and has good versatility.

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Multi-constraint optimization and cutting conditions selection in process planning turning operations with modern chip breaker tools

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1243/095440503762502288 ◽

2003 ◽

Vol 217 (1) ◽

pp. 57-71 ◽

Cited By ~ 3

Author(s):

E J A Armarego ◽

D Ostafiev

Keyword(s):

Process Planning ◽

Economic Benefits ◽

Numerical Control ◽

Cutting Conditions ◽

Complex Nature ◽

Constraint Optimization ◽

Turning Operations ◽

Chip Breaker ◽

Machining Operations ◽

Rough Turning

It has long been recognized that the selection of cutting conditions in process planning should optimize the economic performance of machining operations although it appears that common practice favours the use of ‘recommended’ cutting conditions which are known to be non-optimal. This practice seems to be partly due to the difficulties in establishing equations for the many technological machining performance measures and partly due to the complex nature and slow progress made in developing reliable multi-constraint optimization analyses. This paper presents multi-constraint optimization analyses and computer aided strategies for selecting the ‘optimal’ feeds and speeds in single-pass rough turning operations. The optimization, based on criteria typified by the minimum time and cost per component and suitable for the newer coated lathe tools with in-built chip breaker groove designs, incorporates chip breaking constraints for turning on computer numerical control (CNC) lathes. Despite the complexity of the analyses, clearly denned strategies that guarantee the global optimal solutions have been developed. Extensive simulation studies have highlighted the considerable economic benefits of using ‘optimal’ rather than ‘recommended’ cutting conditions, the potential for increased benefits from improved chip control and tool magazine designs and the need for technological performance equations as well as optimization analyses for the wide spectrum of machining operations for use in modern process planning.

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