Process decision in magnetorheological finishing guided by optical system performance indicators

Magnetorheological finishing (MRF) is often employed as the final manufacturing step for many precision components. Traditional process decision-making methods primarily rely on surface accuracy metrics, which do not directly establish a connection with system-level optical performance. Therefore, this study proposes a decision-making method driven by optical performance. The characteristic tool marks generated by MRF serve as a bridge between process parameters and optical performance, enabling the construction of a full-link simulation that integrates process parameters, tool marks, component characteristics, and optical system performance. Subsequently, for a typical Ritchey-Chrétien system, a statistical model of process parameters and optical performance is established. For large-scale data, the various response mechanisms are clarified through cluster analysis; the coupling among processing parameters is clarified using principal component analysis; and the random forest method is employed to demarcate the range of process parameters based on the response mechanisms. Then, the range of process parameters is determined by reverse searching based on the distance to the ideal value, enabling optimal process parameter decision. This method converts performance requirements into process parameters and enables quantitative decision-making, thereby providing a performance-oriented decision basis for process planning in high-precision optical manufacturing.