Stream-of-variation modeling and analysis of multi-operational machining processes.

摘要

In multi-operational machining processes, part dimensional variation can be attributed to a variety of error sources, and the variations are propagated from upstream to downstream operations in a “Stream of Variation”. One of the major challenges in the machining process control is to understand, model, analyze, and control the process variation.; The limitations of current variation reduction techniques in product and process development are: (1) a lack of system-level models and mathematical tools to understand and to model variation propagation; and (2) the current focus on manufacturing process monitoring, as opposed to balanced studies on process monitoring and root cause identification. As a result, a large number of iterative design changes and human interventions are required due to a poor system response to uncertainty.; The “Stream of Variation” approach is a unified, systematic, and generic methodology developed for variation management and reduction in multi-operational machining processes. A state space modeling approach has been developed to describe variation propagation in machining processes. An analogy is established between a multi-operational machining process and a large-scale dynamic system, where the operation index is considered a time index. Product information and process information are integrated in the system matrices of this state space model. The advantage of this approach is that optimal control theory and advanced statistical methods can be integrated to address manufacturing problems. In order to effectively reduce ramp-up time during production, a responsive in-process diagnostic methodology is developed for identifying root causes of fabrication uncertainty. From the developed state space model, a methodology is also developed for simultaneous tolerance synthesis, process selection, and process design improvement.