Methods for reducing process variation based on deterministic and probabilistic models_Henry QiaoSpeaker: Qiao Heng , Head of Six Sigma Promotion and Master Black Belt of Ningde New Energy Technology Co., Ltd. (ATL)
Topic: Methods for reducing process variation based on deterministic and probabilistic models
summary:
In the process of process optimization, it is not only necessary to obtain the optimal setting of the mean, but also to reduce process variation, such as reducing the process standard deviation or coefficient of variation, which is often more critical. Process variation not only directly affects process capability, but is also an important input parameter in the product design process, and is of vital importance to the design of high-quality products. However, many engineers and technicians do not understand how to establish a statistical model of process variation and its optimization method. This article introduces two methods to reduce process variation to help engineers and technicians model and optimize process variation: 1) Establish a deterministic model of process variation based on the experimental design method of internal and external surfaces; 2) Establish a probabilistic model of process variation based on error propagation and Monte Carlo simulation methods.
