关键词: 数字制造, 尺寸关联, 多工序制造, 质量分析与预测, 偏最小二乘回归

Abstract: To meet with the needs of multistage quality control in digital manufacturing, a process association matrix based on the dimension chain was put forward on the basis of analyzing machining features and datum. Part process information was stored by feature-based description method. Based on this, a process association searching algorithms was designed to extract association between processes. An analysis and forecasting model for multistage manufacturing quality was constructed based on partial least square regression. Some principal components which were major influencing factors on multistage manufacturing quality were extracted by partial least square regression. Then, the multi-collinearity among processes could be solved and the forecasting precision of multistage manufacturing quality model could be improved greatly. Finally, a case study on bush machining was given to demonstrate the above-mentioned ideas.

Key words: digital manufacturing, dimension association, multistage manufacturing, quality analyzing and forecasting, partial least square regression