Abstract
Surface roughness is often considered the main purpose in contemporary computer numerical controlled (CNC) machining industry. Most existing optimization researches for CNC finish turning were either accomplished within certain manufacturing circumstances or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme is deemed to be necessary for the industry. In this paper, the cutting depth, feed rate, speed, and tool nose runoff with low, medium, and high level are considered to optimize the surface roughness for finish turning based onL9(34)orthogonal array. Additionally, nine fuzzy control rules using triangle membership function with respective to five linguistic grades for surface roughness are constructed. Considering four input and twenty output intervals, the defuzzification using center of gravity is then completed. Thus, the optimum general fuzzy linguistic parameters can then be received. The confirmation experiment result showed that the surface roughness from the fuzzy linguistic optimization parameters is significantly advanced compared to that from the benchmark. This paper certainly proposes a general optimization scheme using orthogonal array fuzzy linguistic approach to the surface roughness for CNC turning with profound insight.
Highlights
Machining operations have been the core of the manufacturing industry since the industrial revolution 1
The four turning parameters speed, cutting depth, feed rate, and tool nose runoff with three different levels low, medium, and high Table 7 are experimentally distinguished for the machining operation on the basis of L9 34 orthogonal array
A confirmation experiment of the optimum fuzzy linguistic parameters was conducted to indicate the effectiveness of the proposed optimization method
Summary
Machining operations have been the core of the manufacturing industry since the industrial revolution 1. The existing optimization researches for computer numerical controlled CNC turning were either simulated within particular manufacturing circumstances 2– 5 or achieved through numerous frequent equipment operations 6, 7. These are regarded as computing simulations, and the applicability to real-world industry is still uncertain. A general deduction optimization scheme without equipment operations is deemed to be necessarily developed. The machining process on a CNC lathe is programmed by speed, feed rate, and cutting depth, which are frequently determined based on the job shop experiences. The machine performance and the product characteristics are not guaranteed to be acceptable
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