基于智能优化算法的军机后机身的流程优化数据集

基于成熟度驱动的模型协同技术和缩短某教练机“后机身”研制周期的目标，在航空产品研制过程中严格的转阶段控制以及各阶段内工作的可并行性基本要求下，通过对某型号教练机“后机身”整个研制周期中单独阶段内和不同阶段间各个研制任务活动节点之间的串行、并行、耦合、重叠以及约束等关系进行分析，借助离散事件建模方法，设计了三种多目标智能优化方法，能有效减少返工和重复开发，缩短研制周期，降低开发成本。

Targeting the goal of applying maturity-driven model collaboration technology and shortening the development cycle of the "aft fuselage" of a certain type of trainer aircraft, under the basic requirements of strict phase transition control and the parallelizability of intra-phase work during aviation product development, this study analyzed the serial, parallel, coupled, overlapping and constraint relationships among various development task activity nodes within individual phases and across different phases throughout the entire development cycle of the "aft fuselage" of this trainer aircraft. By leveraging discrete event modeling methods, three multi-objective intelligent optimization methods were designed, which can effectively reduce rework and repeated development, shorten the development cycle, and lower development costs.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于某教练机后机身研制流程的优化，通过分析任务节点间的复杂关系，应用离散事件建模和三种多目标智能优化方法。其目标是减少返工与重复开发，从而缩短研制周期并降低开发成本。