CAJ | 학술논문

面向成本的设计(Design For Cost,DFC)是从设计的角度降低全生命周期成本(Life Cycle Cost,LCC)的设计方法.从DFC的角度,通过分析得到家用轿车的设计特征主要有外形尺寸、发动机功率、排量等参数,采用基于特征的神经网络集成方法,通过实例计算表明在概念设计阶段就可以估算其LCC,为降低其LCC奠定了重要基础.在计算BP神经网络权值时分别采用了Levenberg-Marquardt,LM法和遗传算法(Genetic algorithm,GA),对两种方法的计算结果进行了神经网络集成,集成后的结果更好.最后采用类似方法,对家用轿车的部分性能指标(100 km耗油量和车身质量)进行了预测.
면향성본적설계(Design For Cost,DFC)시종설계적각도강저전생명주기성본(Life Cycle Cost,LCC)적설계방법.종DFC적각도,통과분석득도가용교차적설계특정주요유외형척촌、발동궤공솔、배량등삼수,채용기우특정적신경망락집성방법,통과실례계산표명재개념설계계단취가이고산기LCC,위강저기LCC전정료중요기출.재계산BP신경망락권치시분별채용료Levenberg-Marquardt,LM법화유전산법(Genetic algorithm,GA),대량충방법적계산결과진행료신경망락집성,집성후적결과경호.최후채용유사방법,대가용교차적부분성능지표(100 km모유량화차신질량)진행료예측.
The design for cost (DFC) is a designing method for lowering the whole life cycle cost (LCC) from a design point of view.From the angle of design and through analysis, the designing characteristics that mainly contain parameters of outline dimen-sions, power of engine and delivery capacity etc.of family car were obtained.By adopting the characteristics based neural network inte-gration method it has been indicated by means of a living example that its life cycle cost (LCC) could then be estimated during the phase of conceptual design, and thus laid an important foundation for lowering its LCC.The LM (Levenberg- Marquardt) method and genetic algorithm (GA) have been adopted respectively while com-puting the weights of BP neural network.The neural network inte-gration was carried out on the calculation results of these two kinds of algorithms, and found that the result after integration is so much the better.Finally, by adopting the similar method a prediction on partial performance indexes (oil consumption/100 kilometers and car-body mass) of family car was carried out.