| It is well recognized that geometrical accuracy and dimensional variation are two of the most important quality and productivity factors in many manufacturing processes. Thus, the lack of a comprehensive technology for product/process performance prediction and control in dimensional/geometric variation is a major barrier to further progress in new product and process development.; The methodology for Stream-of-Variation (SOYA) is a systematic approach for modeling, analysis, diagnosis and control of product variation in assembly systems. The general framework of the developed methodology includes: (1) Statistical modal analysis (SMA) methodology, which established a generic math model to represent arbitrary form variability of a geometrical feature and provides the basis for the statistical geometric tolerancing (G/ST). (2) Composing rule, which determines the interaction of the SMA model and the tolerance zone assigned. This rule will be used for generating random samples in G/ST conforming to the tolerance zone with given in-specs probabilities. (3) Mechanistic model for stream of variation propagation analysis of compliant assembly (SOVA-CA), which integrates component error (SMA) and product/process information, and provides a compatible and explicit model, whereby, the current FEM-Monte Carlo simulation can be avoided in G/ST. (4) SOVA model for rigid assembly (SOVA-RA) that expands the current 2D SOVA model to more general 3D assembly and provides the fundamental building block for multiple station 3D SOVA model. SOVA-RA provides a simplified, economic alternative for SOVA-CA. (5) Computational efficient algorithm based on Number Theoretical approach (NT-net), this is desirable for overcoming the computational difficulty of Monte Carlo-based statistical tolerancing for complex assembly models. Validation of the methodology is illustrated by case studies.; The SOVA methodology can be potentially applied to many multistage manufacturing industries such as automotive, aerospace, shipbuilding, etc. It will provide substantial benefits to the field of manufacturing. It is our goal that this tool will enable the domestic manufacturer to continue the improvement in quality and productivity and reduce the overall cost. |
