A Knowledge base for Non-Traditional Machining Process Selection
A growing increase in the newer materials used for machining has resulted development of a number of new manufacturing processes known today as non-traditional machining processes. As machining process selection is often difficult and time consuming, the need for a structured approach for appropriate selection of non-traditional machining processes is important. This paper presents a knowledge base system developed for identifying the most appropriate non-traditional machining process to suit specific circumstances based on the output parameter requirements such as material type, shape applications, process economy and some of the process capabilities such as surface finish, corner radii, width of cut, length to diameter ratio, tolerance etc. This approach has resulted in the selection of the best non-traditional machining process among the competitive non-traditional machining processes that takes into account all the existing restrictive factors. The selection procedure involves identifying the relevant possible alternatives among the non-traditional machining processes and grading them according to their performance. The evaluation of the properties and characteristics are carried out by grading them on the basis of a weighted factor (confidence level), after identification of the possible candidate non-traditional machining processes. The selection procedure proposed in this study is based on the idea that certain characteristics of a part restrict the choice of certain non-traditional machining processes for it to have a relatively small number of alternatives. A wide range of industrial parts has been evaluated in order to demonstrate the performance of the proposed procedure.
Keywords: Non-Traditional Machining Processes Knowledge Base, Depth-First-Search Algorithm
Prof. Edison Chandraseelan.R.
Assistant Professor, Department of Mechanical Engineering, Vellammal Engineering College