The paper investigates in-process signal usage in turning for indirect surface roughness measurement. Based on theoretical surface roughness value and in-process signal, a model is proposed for surface roughness evaluation. Time surface roughness and in-process signal surface roughness correlation based analysis is performed to characterize tool wear component behavior among others. Influencing parameters are grouped based on their behavior in time. Moreover, Digital Object Memory based solution and algorithm is proposed to automate indirect surface roughness measurement process.