A Primary Robustness Optimization Strategy of Multi-Item and Low-Volume Process
- 1 Department of Industry Engineering, Nankai University, Tianjin, China
Abstract
Multi-item and low-volume process is a production system with multi-input source, interactions between input variables, and frequently changes of system state, etc. Strong interactions between input variables and time-varying of input variables cause poor robustness and large variation range of output quality, which produces high cost, heavy waste and low efficiency of multi-item and low-volume process. Robustness optimization of multi-item and low-volume process is a new, important and need-to-deep research field with multi-item and low-volume production system prevails. It proposed a strategy enhancing robustness of multi-item and low-volume process by Taguchi robust design. Firstly, build and analyze a fitting output response model of multi-item and low-volume process after taking the adjustable variables (or time-varying variables) corresponding to each item and interaction between input variables into fitting output response model of multi-item and low-volume process as input variables uniformly, and treating the parameter value of time-varying variables corresponding to each item as level value of the adjustable variables (or signal factors) of process. Secondly, present robustness evaluation index based on evidential theory, desirability function and dual response surface etc. Finally, choose the proper experiment type and optimize the process. And then the robustness optimization of multi-item and low-volume process can be reached.
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