绿色制造风险的群层次模糊综合评判

分析了绿色制造中综合风险的层次结构模型；建立了群层次模糊综合评判的数学模型：建立了综合风险层次模型，给出了群层次模糊综合评判的方法。实例研究表明，该方法是有效的，层次模型和群层次模糊综合评判反映了实施绿色制造中的风险特点，实际应用是可行的。     

基于模糊AHP的机电产品绿色再制造综合评价方法及应用

提出一种基于模糊层次分析法(Fuzzy AHP)的机电产品绿色再制造综合评价方法,借鉴绿色制造TQCRE五大决策属性,从废旧机电产品再制造的环境、资源、能源、经济和技术等五个方面进行分析,构建评价模型。建立了机电产品绿色再制造综合评价指标体系及流程,通过定性和定量相结合的模糊层次分析评价方法对再制造度进行评价,最后通过一个实例验证了该方法的可行性和实用性。     

多级模糊评价在绿色产品评价中的应用

绿色产品的“绿色程度”的评价是涉及多个方面和层次的多级评价问题。根据影响产品“绿色程度”评价项目的属性 ,将其分成不同的评价方面、要素及因素 ,形成不同的评价层次。采用多级模糊评价方法解决了综合考虑产品在全生命周期或多生命周期内从设计、制造、使用及回收利用等方面众多因素的影响下的评价问题。通过权重系数突出重要的评价项目 ,评价过程不仅考虑了所有因素的影响 ,而且保留了各级评价的全部信息。评价结果客观、直观地反映了实际情况 ,且便于评价和比较 ,并通过实例说明了评价过程     

模糊综合评判法在绿色工艺方案决策中的应用研究

综合考虑制造过程中的环境影响和资源消耗，对绿色制造中的绿色工艺方案决策进行分析。运用模糊综合评判法建立绿色工艺方案决策的评判模型。决策实例的应用验证了所建模型与所用方法的正确性和适用性，并对进行绿色工艺方案决策的研究具有实际意义。     

模糊AHP方法在产品绿色模块化设计中的应用

绿色设计和绿色制造是制造业实施可持续发展的关键技术。在绿色产品设计开发过程中采用模块化技术,易于增加产品的材料相容性、可维护性、可拆卸及可回收性等。总结了模块化方法在产品绿色设计中的应用特点,考虑环境问题应引起的模块,产品实施模块化中应注意考虑的环境目标等;提出了一种应用于离散型机电产品多目标模块化分析的初步框架,对利用模糊图论和ＡＨＰ方法解决机电产品绿色设计决策的多目标、多特征和不确定性做了重点     

基于模糊层次分析法的机电产品绿色度综合评价

为了评价机电产品的绿色性能,根据绿色产品的特征,提出应用面向产品全生命周期的模糊层次分析法对机电产品进行绿色度综合评价。统筹考虑机电产品整个生命周期中的绿色属性,根据产品及其评价指标的层次特性,应用层次分析方法建立递阶层次结构模型,结合模糊评判法对产品的“绿色”特性进行评价。并以此作为产品的方案比较或进行绿色设计和绿色制造的决策依据。实例证明．采用模糊层次分析法对机电产品进行绿色度综合评价是合理可行的。     

基于模糊层次分析法的刀具优化选择

针对刀具选择决策的不确定、模糊性等问题,提出了基于模糊层次分析法的多属性约束决策模型。从质量属性、成本属性和效率属性三方面,采用层次分析法建立刀具选择的递阶层次结构模型,根据准则层权重和因素层权重得出候选方案的权重值。由方案权重大小得出刀具最优选择,并通过实例验证了此方法的可行性。     

基于模糊积分的绿色工艺规划综合评判

实施绿色制造的基础是确定绿色工艺规律。文中运用模糊积分建立了绿色工艺规划综合评判模型,采用两级评判方法解决了工艺规划中多影响因素的评判及工艺规划方案选择问题,并以实例说明了其可行性。     

绿色产品制造工艺方案的研究

通过对影响绿色产品制造工艺决策的因素进行定性和定量相结合的分析。从资源利用属性、能源利用属性、环境负担和经济性等几个方面建立了绿色制造工艺评价体系的层次结构图,并应用层次分析法确定绿色制造工艺决策的权重和应用有限方案多目标决策逼近理想解法对决策工艺方案进行排序。在此基础上应用实例求绿色产品多个制造工艺方案的最优解,并通过验证是可行的。     

企业绿色制造实施过程及绩效评价研究

根据企业实施绿色制造的系统性和复杂性,基于生命周期主线从系统的角度综合考虑绿色制造目标、过程、特征和支撑技术,提出了一个四层结构的技术框架模型。针对基于该模型实施绿色制造的成果检验的需要建立了绿色制造绩效评价模型,提出将可拓层次分析与模糊综合评价相结合的评价方法。该评价方法利用可拓层次分析法计算出准确的各因素的相对权重,结合模糊综合评价法进行逐级评价,最终得出综合评分。本模型可为企业实施绿色制造提供一种技术体系参考模型和评价工具。     

基于消费者行为的绿色制造服务决策方法

为了满足制造与服务融合过程中的绿色化需求,构建了绿色制造服务决策方法,该方法以绿色制造中的消费者行为分析为基础,将消费者购买行为映射为绿色制造服务决策主题,通过决策支持工业互联网环境中绿色制造服务的智能化运作。提出了绿色制造服务决策模型,该模型以绿色设计服务决策、绿色生产服务决策、绿色产品服务决策刻画绿色制造服务运作过程中的决策活动。结合消费者问题识别、消费者购买过程、消费者满意度等行为对绿色制造服务问题制定了决策方案,并建立了基于灰色关联分析的绿色产品服务决策算法,最后通过企业绿色产品服务决策的算例分析,验证了该算法的可行性,以及消费者行为驱动绿色制造服务决策的有效性。     

Environmentally conscious design by using fuzzy multi-attribute decision-making

Products affect the environment at many points in their life cycles. Once a product moves from the drawing board into the production line, its environmental attributes are largely fixed. Many researchers have focused on developing intelligent systems to provide a variety of design and manufacturing information to help designers make environmentally conscious decisions. However, in the early design stage, not all the information available is precise. A large amount of information, especially those that are based on designer experience, is fuzzy in nature. This paper presents an innovative method, namely green fuzzy design analysis (GFDA), which involves simple and efficient procedures to evaluate product design alternatives based on environmental consideration using fuzzy logic. The hierarchical structure of environmentally conscious design indices was constructed using the analytical hierarchy process (AHP), which include five aspects: (1) energy, (2) recycling, (3) toxicity, (4) cost, and (5) material. After weighting factors for the environmental attributes are determined, the most desirable design alternative can be selected based on the fuzzy multi-attribute decision-making (FMADM) technique. The benefit of using such a technique is to effectively solve the design problem by capturing human expertise.     

Environmentally conscious design by using fuzzy multi-attribute decision-making

Products affect the environment at many points in their life cycles. Once a product moves from the drawing board into the production line, its environmental attributes are largely fixed. Many researchers have focused on developing intelligent systems to provide a variety of design and manufacturing information to help designers make environmentally conscious decisions. However, in the early design stage, not all the information available is precise. A large amount of information, especially those that are based on designer experience, is fuzzy in nature. This paper presents an innovative method, namely green fuzzy design analysis (GFDA), which involves simple and efficient procedures to evaluate product design alternatives based on environmental consideration using fuzzy logic. The hierarchical structure of environmentally conscious design indices was constructed using the analytical hierarchy process (AHP), which include five aspects: (1) energy, (2) recycling, (3) toxicity, (4) cost, and (5) material. After weighting factors for the environmental attributes are determined, the most desirable design alternative can be selected based on the fuzzy multi-attribute decision-making (FMADM) technique. The benefit of using such a technique is to effectively solve the design problem by capturing human expertise.     

Environmentally conscious design by using fuzzy multi-attribute decision-making

Products affect the environment at many points in their life cycles. Once a product moves from the drawing board into the production line, its environmental attributes are largely fixed. Many researchers focus on developing intelligent systems to provide a variety of design and manufacturing information to help designers make environmentally conscious decisions. However, in the early design stage, not all the information available is precise. A large amount of information, especially that which is based on designer experience, is fuzzy in nature. This paper presents an innovative method, namely, green fuzzy design analysis (GFDA), which involves simple and efficient procedures, to evaluate product design alternatives based on environmental consideration using fuzzy logic. The hierarchical structure of environmentally conscious design indices was constructed using the analytical hierarchy process (AHP), which includes five aspects: (1) energy, (2) recycling, (3) toxicity, (4) cost, and (5) material. After weighting factors for the environmental attributes are determined, the most desirable design alternative can be selected based on the fuzzy multi-attribute decision-making (FMADM) technique. The benefit of using such a technique is to effectively solve the design problem by capturing human expertise .     

绿色工艺规划的决策模型及应用案例研究

绿色工艺规划是绿色制造的重要组成部分,绿色工艺规划问题实质上是一个决策问题。在绿色制造决策框架模型研究的基础上,从绿色工艺规划的目标体系模型、绿色工艺规划问题的决策变量描述出发,建立了绿色工艺规划的决策模型,并在一个生产实际的工艺规划问题成功地进行了应用。     

基于数字孪生的制造资源动态优选决策

针对面向服务的智能制造环境下决策数据的准确性和实时性不足,以及协同和动态决策机制欠缺等问题,提出一种基于数字孪生的制造资源动态优选决策方法。设计了基于数字孪生的制造资源动态优选决策架构,并提出设备数字孪生(云/边数字孪生)和产品数字孪生,为决策者提供准确、实时的评价数据;构建基于实时Multi-Agent的资源优选决策多方协同机制,采用层次赋时有色Petri网仿真分析复杂制造任务中的瓶颈设备资源;采用序关系分析法计算评价指标权重,引入参考理想法对候选制造资源进行综合评估。将该方法应用于某航空发动机叶片制造企业设备资源优选中,验证了所提方法的可行性和有效性。     

绿色制造的决策框架模型及其应用

分析了绿色制造过程中决策问题的决策目标,提出了包含T（时间）、Q（质量）、C（成本）、E（环境影响）和R（资源消耗）等5大决策目标变量的决策目标体系,并由此建立了绿色制造的决策框架模型,最后用一个制造过程中的决策问题实例,说明了绿色制造的决策框架模型的应用。     

面向绿色制造的生产过程的夹具选择决策模型

分析了国内外当前机床夹具的研究前沿,提出了夹具的绿色化程度对整个制造过程的绿色化水平有着极为重要的影响.建立了面向绿色制造的生产过程的夹具选择决策模型,采用层次分析法和模糊综合评判法相结合的方法对决策模型进行求解,并说明了所建立的决策模型的应用.     

基于区间数的机械加工工艺方案多目标稳健决策

绿色制造中的工艺方案选择是一个复杂的多目标决策问题。由于机械加工过程存在不确定性,目标值往往不是一个确定的数,而是一个变化区间,所以用区间数表示更加符合实际。为此,提出一种基于区间数的机械加工工艺方案多目标稳健决策方法,首先建立了多目标稳健决策体系;然后结合区间数理论,建立了多目标稳健决策模型;最后以阀体机加工过程的4个不同工艺方案为例,验证了该模型的可行性和实用性。     

Aggregate production planning with multiple fuzzy goals

This work presents a novel interactive multiple fuzzy objective linear programming (MFOLP) model for solving the aggregate production planning (APP) decision problem in a fuzzy environment. The proposed model minimizes total production costs, carrying and backordering costs, and costs of changes in labor levels, while considering inventory levels, labor levels, machine capacity, warehouse space, and the time value of money. An industrial case demonstrates the feasibility of applying the proposed model to the APP problem. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple fuzzy goal values. Furthermore, the proposed model provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the fuzzy data and related model parameters until a satisfactory solution is obtained. Several significant characteristics that differentiate the proposed model from other APP models are presented .