【正文】 ，而不是衍生工具或其他輔助知識。傳統(tǒng)的技術(shù)是沒有效率的時候，實際的搜索空間過大。數(shù)學(xué)模型常用的是代表： 而 Y是加工回應(yīng)， ?是響應(yīng)函數(shù)和 S， f，α ， R的銑削變數(shù)和∈是錯誤，通常是發(fā)給約觀測響應(yīng) y為零的意思。 喬恩和賈殷 [ 8 ]用神經(jīng)網(wǎng)絡(luò)建模和優(yōu)化加工條件。 艾爾艾丁等人 [ 6 ]開發(fā)出一種表面粗糙度模型，用丹參，為端銑 190BHN鋼。 拜佑密等人 [ 4 ]研究過工具對旋轉(zhuǎn)角度，進給速度和切削速度在機械工藝參數(shù)（壓力，摩擦參數(shù)）的影響，為端銑操作常用三種商用工件材料， 11L17易切削鋼， 62353易切削黃銅和鋁 2024年使用單一槽高速鋼立銑刀。為了開發(fā)和優(yōu)化表面粗糙度模型，有必要了解目前在這方面的工作的狀況。在材料去除過程中，不當?shù)倪x擇切削條件造成的表面粗糙度高和尺寸誤差 ，它甚至可能發(fā)生動力現(xiàn)象：由于自動興奮的震動，可以設(shè)定在 [ 2 ] 。在這個過程中建模有助于更好的理解。通過嘗試也取得了優(yōu)化表面粗糙度預(yù)測模型，采用遺傳算法（ GA ） 。1 Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling Abstract : Influence of tool geometry on the quality of surface produced is well known and hence any attempt to assess the performance of end milling should include the tool geometry. In the present work, experimental studies have been conducted to see the effect of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the machining performance during end milling of medium carbon steel. The first and second order mathematical models, in terms of machining parameters, were developed for surface roughness prediction using response surface methodology (RSM) on the basis of experimental results. The model selected for optimization has been validated with the Chi square test. The significance of these parameters on surface roughness has been established with analysis of variance. An attempt has also been made to optimize the surface roughness prediction model using geic algorithms (GA). The GA program gives minimum values of surface roughness and their respective optimal conditions. Introduction End milling is one of the most monly used metal removal operations in industry because of its ability to remove material faster giving reasonably good surface quality. It is used in a variety of manufacturing industries including aerospace and automotive sectors, where quality is an important factor in the production of slots, pockets, precision and dies. Greater attention is given to dimensional accuracy and surface roughness of products by the industry these days. Moreover, surface finish influences mechanical properties such as fatigue behaviour, wear, corrosion, lubrication and electrical conductivity. Thus, measuring and characterizing surface finish can be considered for predicting machining performance. Surface finish resulting from turning operations has traditionally received considerable research attention, where as that of machining processes using cutters, requires attention by researchers. As these processes involve large number of parameters, it would be difficult to correlate surface finish with other parameters just by conducting experiments. Modeling helps to understand this kind of process better. Though some amount of work has been carried out to develop surface finish prediction models in the past, the effect of tool geometry has received little attention. However, the radial rake angle has a major affect on the power consumption apart from tangential and radial forces. It also influences chip curling and modifies chip flow direction. In addition to this, researchers [1] have also observed that the nose radius plays a significant role 2 in affecting the surface finish. Therefore the development of a good model should involve the radial rake angle and nose radius along with other relevant factors. Establishment of efficient machining parameters has been a problem that has confronted manufacturing industries for nearly a century, and is still the subject of many studies. Obtaining optimum machining parameters is of great concern in manufacturing industries, where the economy of machining operation plays a key role in the petitive market. In material removal processes, an improper selection of cutting conditions cause surfaces with high roughness and dimensional errors, and it is even possible that dynamic phenomena due to auto excited vibrations may set in [2]. In view of the significant role that the milling operation plays in today?s manufacturing world, there is a need to optimize the machining parameters for this operation. So, an effort has been made in this paper to see the influence of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the surface finish produced during end milling of medium carbon steel. The experimental results of this work will be used to relate cutting speed, feed rate, radial rake angle and nose radius with the machining response . surface roughness by modeling. The mathematical models thus developed are further utilized to find the optimum process parameters using geic algorithms. 2 、 Review Process modeling and optimization are two important issues in manufacturing. The manufacturing processes are characterized by a multiplicity of dynamically interacting process variables. Surface finish has been an important factor of machining in predicting performance of any machining operation. In order to develop and optimize a surface roughness model, it is essential to understand the current status of work in this area. Davis et al. [3] have investigated the cutting performance of five end mills having various helix angles. Cutting tests were performed on alloy L 65 for three milling processes (face, slot and side), in which cutting force, surface roughness and concavity of a machined plane surface were measured. The central posite design was used to decide on the number of experiments to be conducted. The cutting performance of the end mills was assessed using variance analysis. The affects of spindle speed, depth of cut and feed rate on the cutting force and surface roughness were studied. The investigation showed that end mills with left hand helix angles are generally less cost effective than those with right hand helix angles. There