文档介绍：International Journal of Machine Tools & Manufacture 43 (2003) 833–844
Predicting surface roughness in machining: a review
. Benardos, G.-C. Vosniakos ∗
National Technical University of Athens, School of Mechanical Engineering, Manufacturing Technology Division, Iroon Polytexneiou 9,
157 80 Zografou, Athens, Greece
Received 20 December 2002
Abstract
The general manufacturing problem can be described as the achievement of a predefined product quality with given equipment,
cost and time constraints. Unfortunately, for some quality characteristics of a product such as surface roughness it is hard to ensure
that these requirements will be met. This paper aims at presenting the various methodologies and practices that are being employed
for the prediction of surface roughness.
The resulting benefits allow for the manufacturing process to e more productive petitive and at the same time to
reduce any re-processing of the machined workpiece so as to satisfy the technical specifications. Each approach with its advantages
and disadvantages is outlined and the present and future trends are discussed. The approaches are classified into those based on
machining theory, experimental investigation, designed experiments and artificial intelligence (AI).
2003 Elsevier Science Ltd. All rights reserved.
Keywords: Surface roughness; Surface roughness prediction; Machining; Review
1. Introduction puter controlled machine tools, have brought up
new issues to deal with, which further emphasize the
There are two main practical problems that engineers need for more precise predictive models.
face in a manufacturing process. The first is to determine Surface roughness is a widely used index of product
the values of the process’ parameters that will yield the quality and in most cases a technical requirement for
desired product quality (meet technical specifications) mechanical products. Achieving the desired surface
and the second is to maximize manufacturing sy