基于綠色特征的方案設計與評價
發(fā)布時間：2018-11-16 15:35
【摘要】：在人類物質文明飛速發(fā)展的同時,對資源、能源的過度消耗和對環(huán)境的無償利用已經(jīng)造成資源短缺、環(huán)境污染等一系列問題。對于產品來說,要從根本上解決環(huán)境問題,必須實施源頭控制,將污染消除在生產過程之初,即方案設計階段。因此,在產品方案設計的早期階段,如何對環(huán)境有重要影響的綠色信息進行有效集成,對產品生命周期資源、能源、碳排放等環(huán)境屬性做出正確評價,進而獲得綠色設計方案,是提高產品環(huán)境性能的關鍵。 常規(guī)的產品方案設計主要是從用戶需求出發(fā),利用QFD方法將用戶需求轉化為方案設計參數(shù)以及技術特征,對產品方案進行約束,主要關注產品零部件的低層幾何信息和拓撲信息、原理信息、功能信息、基本的裝配信息及可制造信息等,而沒有詳細的形狀、尺寸、精度、制造和裝配信息,信息量少且不確定程度很高,難以利用已有的信息完成產品的環(huán)境影響評價,進而優(yōu)化產品方案。并且,由于方案設計師環(huán)境知識的匱乏,難以從嚴重不完整且不確定的設計參數(shù)中提取出綠色信息,并對其進行有效集成,進而完成產品生命周期評價。針對這些難題,本文提出了基于綠色特征的產品方案設計模型來支持產品在方案設計早期階段的綠色設計與評價。 (1)針對方案設計階段信息嚴重匱乏,難以提取完整的設計參數(shù)信息來支持生命周期評價過程的現(xiàn)狀,本文建立了產品全生命周期模塊化設計模型。首先,將產品按照功能性、綠色性等進行模塊化設計；然后,根據(jù)需要,運用實例推理、約束、描述邏輯等模塊選擇方式,選取匹配模塊,重組成符合要求的產品,生成產品模塊化設計方案,從而獲得綠色設計參數(shù)信息。 (2)建立了設計參數(shù)信息與綠色特征之間的雙向信息映射模型和映射關系模型,將設計參數(shù)信息轉換為對環(huán)境有重要影響的屬性信息——綠色特征。針對映射關系中的關鍵技術進行了重點研究,并以某推土機變速箱行星架為例進行了驗證。 (3)在課題組前期工作的基礎上,進一步研究了基于綠色特征的快速生命周期評價(RLCA)及優(yōu)化方法。分析了綠色特征中存在的不確定性信息,對其中的定量信息和定性信息分別采用蒙特卡羅法和模糊集理論進行處理,在此基礎上完成了產品方案的快速生命周期評價；運用基于數(shù)理統(tǒng)計和基于神經(jīng)網(wǎng)絡的敏感性分析方法對評價結果進行敏感性分析,找出其中對評價結果影響比較大的因素,回溯到產品的設計參數(shù)信息,對方案進行優(yōu)化。
[Abstract]:With the rapid development of human material civilization, the excessive consumption of resources and energy and the free use of the environment have caused a series of problems, such as the shortage of resources and environmental pollution. For the product, to solve the environmental problem fundamentally, it is necessary to carry out the source control and eliminate the pollution at the beginning of the production process, that is, the project design stage. Therefore, in the early stage of product design, how to integrate the green information which has important impact on the environment, and make a correct evaluation of the environmental attributes such as product life cycle resources, energy, carbon emissions, etc., and then obtain the green design scheme. It is the key to improve the environmental performance of products. The conventional product scheme design is mainly based on the user's requirements, and the QFD method is used to transform the user's requirements into the design parameters and technical features, which constrains the product scheme. Focusing on the lower level geometry and topology information, principle information, function information, basic assembly information and manufacturable information, etc., without detailed shape, size, precision, manufacture and assembly information, etc. Because of the small amount of information and the high degree of uncertainty, it is difficult to make use of the existing information to complete the environmental impact assessment of the product, and then optimize the product scheme. Moreover, due to the lack of environmental knowledge, it is difficult to extract green information from the seriously incomplete and uncertain design parameters, and integrate it effectively to complete the product life cycle evaluation. In order to solve these problems, a green feature based product design model is proposed to support the green design and evaluation in the early stage of the project design. (1) in view of the serious lack of information in the project design phase, it is difficult to extract complete design parameter information to support the life cycle evaluation process. In this paper, a product lifecycle modular design model is established. First of all, the product according to the functionality, green and other modular design; Then, according to the need, we select the matching module by using case-based reasoning, constraint, description logic and other module selection methods, reorganize into the product that meets the requirements, and generate the product modular design scheme, so as to obtain the green design parameter information. (2) the bidirectional information mapping model and the mapping relation model between the design parameter information and the green feature are established, and the design parameter information is transformed into the green feature, which has an important impact on the environment. The key technologies of mapping relation are studied and verified by an example of a bulldozer gearbox planetary frame. (3) based on the previous work of the research group, the fast life cycle evaluation (RLCA) and its optimization method based on green feature are further studied. The uncertain information in green feature is analyzed, and the quantitative and qualitative information are processed by Monte Carlo method and fuzzy set theory respectively. On this basis, the rapid life cycle evaluation of product scheme is completed. The sensitivity analysis method based on mathematical statistics and neural network is used to analyze the sensitivity of the evaluation results. The factors which have a great influence on the evaluation results are found out, and the design parameters are traced back to the design parameters of the products, and the scheme is optimized.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TB472
本文編號：2335904
[Abstract]:With the rapid development of human material civilization, the excessive consumption of resources and energy and the free use of the environment have caused a series of problems, such as the shortage of resources and environmental pollution. For the product, to solve the environmental problem fundamentally, it is necessary to carry out the source control and eliminate the pollution at the beginning of the production process, that is, the project design stage. Therefore, in the early stage of product design, how to integrate the green information which has important impact on the environment, and make a correct evaluation of the environmental attributes such as product life cycle resources, energy, carbon emissions, etc., and then obtain the green design scheme. It is the key to improve the environmental performance of products. The conventional product scheme design is mainly based on the user's requirements, and the QFD method is used to transform the user's requirements into the design parameters and technical features, which constrains the product scheme. Focusing on the lower level geometry and topology information, principle information, function information, basic assembly information and manufacturable information, etc., without detailed shape, size, precision, manufacture and assembly information, etc. Because of the small amount of information and the high degree of uncertainty, it is difficult to make use of the existing information to complete the environmental impact assessment of the product, and then optimize the product scheme. Moreover, due to the lack of environmental knowledge, it is difficult to extract green information from the seriously incomplete and uncertain design parameters, and integrate it effectively to complete the product life cycle evaluation. In order to solve these problems, a green feature based product design model is proposed to support the green design and evaluation in the early stage of the project design. (1) in view of the serious lack of information in the project design phase, it is difficult to extract complete design parameter information to support the life cycle evaluation process. In this paper, a product lifecycle modular design model is established. First of all, the product according to the functionality, green and other modular design; Then, according to the need, we select the matching module by using case-based reasoning, constraint, description logic and other module selection methods, reorganize into the product that meets the requirements, and generate the product modular design scheme, so as to obtain the green design parameter information. (2) the bidirectional information mapping model and the mapping relation model between the design parameter information and the green feature are established, and the design parameter information is transformed into the green feature, which has an important impact on the environment. The key technologies of mapping relation are studied and verified by an example of a bulldozer gearbox planetary frame. (3) based on the previous work of the research group, the fast life cycle evaluation (RLCA) and its optimization method based on green feature are further studied. The uncertain information in green feature is analyzed, and the quantitative and qualitative information are processed by Monte Carlo method and fuzzy set theory respectively. On this basis, the rapid life cycle evaluation of product scheme is completed. The sensitivity analysis method based on mathematical statistics and neural network is used to analyze the sensitivity of the evaluation results. The factors which have a great influence on the evaluation results are found out, and the design parameters are traced back to the design parameters of the products, and the scheme is optimized.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TB472
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