Abstract
Surface roughness is an important quality index for machining operations. The traditional offline measurement of surface roughness is time consuming and influences the performance of production. To solve this issue, many studies focus on the development of in-process surface roughness prediction system. The force signals are one of the key input factors for the system in milling operations. The purpose of this study is to apply grey relation to determine the significant force signals that would affect surface roughness. 19 force signals were analyzed, and finally the average of absolute difference of peak force in x direction was explored as the most significant factor that would be used in the in-process surface roughness prediction system.