Error sensitivity analysis and precision distribution for multi-operation machining processes based on error propagation model

Abstract

The error control and distribution of multi-operational machining processes is an active and important research topic in manufacturing. Most of the recent studies focus on statistical methods and the robustness of the evaluating process. However, these studies mainly serve to provide a change prediction tool rather than a method to identify and control root causes of machining errors. In this paper, in order to effectively control and distribute products of high-quality precision, a method of integrating a stream of variations (SoV) and multi-objective optimization is proposed. First, a machining process decomposition method is introduced to identify the sources of error. The multi-operation machining process is divided into three levels: the operation level, the station level, and the key characteristics level. Second, the sensitivities of the machining operation are evaluated level by level based on the SoV model; results of this evaluation will be used to determine the maximum error sources affecting the quality of products. Third, a distribution technique for each quality precision is achieved by solving a multi-objective optimization problem to minimize the cost and error associated with the sensitivities. Finally, a machining instance containing four operations is presented to demonstrate the effectiveness of the methodology.