Digital Simulation and Analysis of Assembly-Deviation Prediction Based on Measurement Data

Abstract

For various power equipment items such as aircraft engines and gas turbines with numerous components demanding requirements on processing accuracy and high structural complexity, processing errors tend to cause such problems as assembly rework, forced assembly and prolonged research and development cycle. In this paper, the core machine of micro gas turbine is taken as the research object to construct a simulation model of assembly-deviation prediction based on the design tolerance and actual measurement data. Then, an analysis is conducted on the assemblability of the design model and the key factors causing the deviation of the assembly. After conducting deviation calculations and simulation analysis, it was determined that the current mounting position is deemed to be suboptimal. In light of this finding, an optimized solution is proposed, which involves advancing the mounting phase by 0.47 mm. This adjustment effectively resolves the interference issue resulting from the design error. Moreover, the geometry, shape and three-dimensional contour of the key components are measured with high accuracy and precision to identify the key characteristic parameters affecting the outcome of the assembly. With an assembly-deviation-prediction and -analysis model established on the basis of actual measurement data, the results of the assembly-deviation analysis are compared with the outcome of the assembly, showing high consistency. The assembly-deviation-prediction method proposed in this paper on the basis of design tolerance and actual measurement data is applicable to the manufacture of aviation and combustion engines.

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“…La eficiencia de estos componentes básicos en la construcción, incluso en situaciones urgentes, garantiza un rendimiento óptimo, por su tecnología de fabricación disponible, junto con la accesibilidad para probar sus propiedades físicas y químicas (como las propiedades mecánicas, aislamiento acústico y térmico, respuesta a las condiciones climáticas, o resistencia al fuego, y para realizar pruebas de fuego, agua, resistencia a parásitos, etc.). Todo ello es muestra de su mejor desempeño en la realidad, y no sólo como simulaciones computacionales, que siempre sufren imprecisiones y márgenes de desviación desde el diseño hasta la producción real (Jiang et al, 2021;Zhang et al, 2023;Segovia y García-Alfaro, 2022). Además, estos componentes básicos, probados con su correspondiente tecnología de fabricación disponible, sientan bases más sólidas para su reproductibilidad y estandarización (Wang et al, 2021;Boafo, Kim y Kim, 2016;Gunawardena y Mendis, 2022).…”