Surface Roughness

ABSTRACT
In present scenario, the manufacturing industries are facing lot of problems to improve the product’s quality because of global competency. The major constraints that they face are cost and equipment. Surface roughness gaining more importance as it is predominant factor which determines the quality and cost of the product. There are various methodologies are proposed by many researchers to predict and improve the surface finish of the product in metal cutting process. Most commonly used methods are Designed experiments, Artificial intelligence (AI) and Particle swarm optimization technique. The benefits of the each method and the limitations are evaluated and their current trends are analysed. The main objective of this review work

To achieve the desired quality in the machining process, researchers are proposed various approaches based on the machining parameters and their interactions. The quality of the component is generally defined as, the accuracy in geometrical and dimensional tolerance, optimal design efficiency, material specification, and good surface finish. These factors affect the product’s quality during the manufacturing process. These things are not only affects the surface quality of the product but also influence the tool life. One of the major goals in the area of surface roughness prediction techniques is to develop models that are able to predict the surface finish of a work piece under a variety of machining conditions. Reliable models are not only make manufacturing process planning and control, it also contribute the optimization of the machinability of the

The review work focuses on metal cutting process such as milling and turning process.
2. SURFACE ROUGHNESS In manufacturing of products, Surface roughness is a widely used as key index of product quality and in most cases as a technical requirement. It contributes a major part in quality attribute. Proper selection and setting of cutting parameter before process is crucial in order to obtain a better amount of surface finish. To make a proper function of a part it is mandatory to achieve a good surface quality. Several researchers developed many methods for assessment of the surfaces quality. The basic measuring systems of surface quality includes: (i) Nicolau’s method, (ii) Envelope method (E-system, Von Weingraber), (iii) Peak-to-valley measures, (iv) Mean line measures (M-system) [56].
Ra is the universally recognized standard parameter of surface roughness. It is the arithmetical mean of the departures of the profile from the given mean line. It is shown in Fig