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Volume :30 Issue : 1 2003      Add To Cart                                                                    Download

An expert system machinability data bank (ESMDB) approach

Auther : EISA A. ALMESHAI* AND SAMY E. ORABY**

Department of Mechanical Production Technology, College of Technological Studies, PAAET, P.O, Box 42325, Shuwaikh 70654, Kuwait

*ema@paaet.edu.kw, Phone: ( + 965) 2520356, Fax: ( + 965) 2523907

 **soraby@paaet.edu.kw, homepage: www.geocities.com/soraby/, Phone: (+965) 9549019

ABSTRACT

The selection of appropriate cutting parameters to ensure efficient and safe machining has long been a technological obstacle, especially to operation programmers and technicians and for those involved in manufacturing processes. Parameters selection is usually based on specialists, past experience or on recommended levels from conventional machinability handbooks. A machinability handbook lists machining operations, cross referenced with a broad list of material types to enable a machinist to find a starting point for speeds and feeds for machining. However, while these suit general or conventional machining and maintenance operations where many production objectives are sacrificed or considered unimportant, this is not the case in modern and advanced machining situations where a continuous in-process monitoring and control is an essential feature essential feature. The major objective of the current approach is to assess the selected cutting parameters considering the specifications of the available resources, production objectives and constraints. This is carried out through advanced detection, or prediction, of the levels of different outputs of the machining process, such as edge wear, cutting force, part surface quality and cutting vibration at any stage of its history. This is to avoid or minimize any possible failure consequences during the in-­process stages that usually lead to the breakage of one or more of the manufacturing elements or which jeopardize the operators safety.

Rather than retrieving and listing information, the proposed approach performs some experience and judgment procedures through pre-specified technically relevant rules and criteria to help the user make the decision whether to accept the proposed preliminary parameters or to modify them. The approach consists of two main features: time-varying mathematical models, and logic algorithm as well as a group of technical advisory rules. The expert system (ES) technique is used as a programming tool to manipulate data, to extract technical information from models according to the inputted data, and to provide users with some technical advisory and judgment information.

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