论产品拆解与绿色设计方法问题

基于产品设计资料,引入产品结构树型图、产品可拆解性和能源回收指数等概念,评估了产品的可拆解性和能源回收性;构建了合并材料和整合产品功能单元2种绿色优化设计方法。以四川绵阳某企业B型超声仪器为例,通过优化设计前后产品零部件数量、拆解步数、拆解时间和能源回收指数的对比,验证了该方法的有效性。     

在Pro/E中自动生成零件拆卸优先约束矩阵

拆卸优先约束矩阵为建立产品的拆卸层次信息图模型提供了基础信息,保证了拆卸序列规划结果的正确性和有效性.在Pro/E中用C语言完成了零件拆卸优先约束矩阵自动生成的二次开发,包括模型调入和预处理、简单拆卸路径生成和包容盒逐级分解的干涉检验等3个模块.解决了自动判别节点可拆卸性的关键问题,为机电产品基于拆卸层次信息图建模的自动化提供了有力的支持.     

考虑不确定性条件的退役产品拆解柔性调度

由于回收的退役产品存在来源、类型、结构和性能残值等方面的不确定性差异，致其梯次或资源化再利用前的拆解逆向生产调度的平稳性受来料品类、拆解序列和拆解方式等不确定性扰动因素影响。本文以采用柔性工装夹具工作站的退役产品拆解生产线为研究对象，考虑不确定的来料品类、拆解序列和拆解方式造成的扰动因素，构建以最短完工时长为目标的AND/OR节点网络调度策略，及其混合整数规划调度模型，并选用改进模拟退火单亲遗传算法求解。实例证明，本文提出的动态调度策略及模型与传统手工经验调度相比较，可减少不确定扰动因素对生产调度的波动影响，有效均衡并提升柔性拆解线设备的利用率，提高退役产品拆解效率。     

基于模块化设计的混合图拆卸建模研究

拆卸建模是拆卸序列规划的基础,也是绿色设计的关键。在传统的拆卸序列规划过程中,随着产品零件数目的增加会造成“组合爆炸”问题。为解决该问题,提出了一种基于模块化设计思想的拆卸建模方法。首先,运用图论中有向图和无向图的概念分别表示零、部件之间的约束关系,并将有向图和无向图结合成混合图,建立产品混合图拆卸模型;其次,利用模块化设计中的模块划分原则生成子装配体,通过将模块化设计方法整合入混合图模型中,得到模块化设计的混合图拆卸模型,利用该模型可以有效地解决图论模型中边与顶点产生“组合爆炸”的问题;最后,以模块化设计的计算机主机箱的混合图拆卸建模为例来验证所提出的方法。     

层次化UML状态机在拆装过程仿真中的应用

针对目前飞机维修培训中拆装流程复杂,系统模型繁多的问题,采用层次化分析法和 UML 状态机相结合的建模方法,建立飞机组件的拆装过程模型。运用 UML状态机建立拆卸组件的状态、迁移和约束模型,规范拆卸零部件模型的统一性表达,提高建模的效率。利用层次化方法对零部件进行层次规划,实现拆卸目标组件的有序逻辑表述,实时监测拆卸零部件的状态,从而建立仿真程度高的训练模型。最后,以维修培训平台中飞机某组件的拆装为例,验证层次化UML状态机拆卸过程仿真方法的有效性。     

基于改进社会工程算法的拆解线平衡多目标优化设计

目的 为了提高拆卸效率,减少拆卸成本和拆卸能耗,提出一种基于社会工程算法的优化方法。方法 首先根据社会工程算法的原理设计了编码和解码方式,然后引入交换子和交换序列的概念,对算法中的训练和再训练、发现攻击和响应攻击等步骤进行设计,最后选取一个高速电子套结机作为实验对象进行了验证。结果 与其他多目标优化算法相比,具有良好的寻优能力。结论 提出的算法有效地解决了拆解线平衡问题,与其他算法相比具有更好的性能。     

基于OBDD的拆卸序列表示模型的优化

拆卸序列的紧凑表示是拆卸序列的评价与优化的基础,AND-OR图是拆卸序列表示的一种典型方法,但是拆卸序列的AND-OR图表示模型存在冗余信息。通过对AND-OR图模型作等价变换,消除AND-OR图表示模型中的冗余信息。设计了拆卸序列的优化表示模型的生成算法,建立了优化的基于OBDD的拆卸序列表示模型,用来表示复杂装配体的拆卸序列。并论证了优化模型的拆卸序列表示可以节省存储空间,最后的实验表明,基于OBDD的拆卸序列优化表示模型的存储空间远小于AND-OR图的存储空间。     

基于可信性理论的闭环供应链生产计划

针对生产、库存和拆卸能力有限情况下,考虑可回收旧产品数量、分销商需求量、生产成本、外包成本、单位旧产品拆卸时间、拆卸成本和单位产品生产时间为模糊不确定数,以供应链总成本最小化为目标,采用期望值规划和机会约束规划相结合的形式,建立不确定环境下供应链生产计划模型。基于可信性规划方法,将不确定模型转化为清晰确定形式。最后,设计算例,通过求解给出在供应链总成本最小下,企业各个计划期内的最优生产量、零部件采购量以及制造商和回收中心对物料的运输计划;并分析了可信性水平、再制造率和回收率变动对供应链总成本的影响,为企业制定生产计划提供参考依据。     

液压打包机油缸建模仿真及动态分析

建立了液压打包机油缸的数学模型,对液压打包机油缸的动态性能进行了仿真,并对主要性能参数进行分析.为液压打包机油缸主要参数的选择、液压系统的智能设计提供理论依据.     

浅析机械装备的再制造拆解工艺与技术

近几年,由于国家政策倡导和经济利益的驱动,再制造技术越来越快的发展了起来。废旧产品的再制造拆解是再制造过程中的重要工序：科学酌再制造拆解工艺能够有效保证再制造的质量性能、几何精度,并显著减少在制造周期和费用,提高再制造质量。这里作者将就再制造工艺流程中的拆解工艺与技术以废旧发动机的拆解流程为例进行解析与阐述。     

拆卸序列规划中子装配体的识别与生成

子装配体识别是解决大规模拆卸序列规划"组合爆炸"问题的有效方法之一.为了准确有效地识别与生成子装配体,在装配体零部件间接触关系、联接关系和向位妨碍关系及其相应图模型、矩阵的基础上,提出了一种基于图模型和判断矩阵的拆卸序列规划子装配体的识别算法.该算法利用图模型对子装配体集合做加法,利用判断矩阵对子装配体集合做减法,首先依据子装配体识别准则对图模型检索生成潜在子装配体集合,然后依据矩阵判断公式从集合中排除不符合连续性原则、稳定性原则和可行性原则的子装配体,并筛选理想个数的符合重量标准、同质标准和价值标准的最终子装配体集合.以减速器实例验证方法的可行性和有效性.     

Generating complete disassembly sequences by utilising two-dimensional views

This research work proposes a novel method to generate the complete disassembly sequences for mechanical products by utilising the part interference matrix which contains the removal directions of the parts and the part connection graph which indicates the contact among the parts in the assembly. Contrary to the earlier methods, the proposed method considers the two-dimensional views generated from the computer-aided design assembly model for automatically identifying the part removal directions and for generating the part connection graph. Rules are formulated in the proposed method to identify the part removal directions effectively and also to reduce the size of part connection graph, since the method of identifying the part removal directions and the size of the formulated graph plays a vital role in the generation of disassembly sequence. Finally, a heuristic method is developed to generate the best feasible disassembly sequences. The effectiveness of the approach is illustrated with three examples.     

Applying data mining technique to disassembly sequence planning: a method to assess effective disassembly time of industrial products

Design for end-of-life and design for disassembly are enabling design strategies for the implementation of business models based on the circular economy paradigm. The paper presents a method for calculating the effective disassembly sequence and time for industrial products. Five steps support designers in defining liaisons and related properties and precedence among components with the aim to calculate the best disassembly sequence and time. The effective disassembly time is computed considering the actual conditions of a product and its components (e.g. deformation, rust and wear) using corrective factors. This aspect represents the main contribution to the state of the art in the field of design for disassembly. The corrective factors are derived from a specific data mining process, based on the observation of real de-manufacturing activities. The proposed approach has been used for calculating the disassembly times of target components in a washing machine and in a coffee machine. The case studies highlight the method reliability of both: definition of time-effective disassembly sequences and assessment of effective disassembly times. In particular, a comparison of experimental tests shows a maximum deviation of ?6% for the electric motor of the washing machine and ?3% for the water pump of the coffee machine.     

Interactive AR-assisted product disassembly sequence planning (ARDIS)

This paper presents a proof-of-concept novel near real-time interactive AR-assisted product disassembly sequence planning system (ARDIS) based on product information, such as interference matrix and 3D models. The system is developed using Unity and consists of three modules, including an intelligent disassembly sequence planning module, an automatic content authoring module and an intuitive augmented reality (AR) user interface (UI) with various features, such as a virtual panel for customisation and an option panel for sequence regeneration. Given the retrieval targets specified by a user, optimised disassembly sequences are computed using an evolutionary computing algorithm. For the sequences computed, the respective AR disassembly instruction sequences, such as 2D text instructions and animated 3D models, are generated dynamically based on a taxonomy that links each disassembly step in a sequence with the corresponding Unity templates that have been created beforehand. Hence, the need for manual authoring to provide AR disassembly guidance is reduced. If necessary, the user can request for alternative disassembly sequences which can be re-computed in near real-time. Several case studies have been carried out to demonstrate and evaluate the performance of the system within the laboratory environment.     

Disassembly process planning algorithms for end-of-life product recovery and environmentally conscious disposal

Disassembly process planning is an act of preparing detailed operation instructions for disassembling used or an end-of-life (EOL) product to recover or dispose of its constituent parts or subassemblies. The main decisions are: (a) disassembly level; (b) disassembly sequence; and (c) EOL options such as reuse, remanufacturing, recycling, incineration, landfill, etc. This study deals with the three decision variables simultaneously in the parallel disassembly environment for the objective of maximising the profit. Unlike previous studies, we consider practical constraints, i.e., reuse probability and environmental impacts of parts or subassemblies, sequence-dependent setup costs, regulation on recovery rate, and incineration capacity. To represent and solve the problem, we develop an extended AND/OR graph, and then suggest a two-phase algorithm. To show the effectiveness of the proposed algorithm, two case studies have been carried out on an automatic pencil and a telephone. Also, test results on other general product structures are reported.     

Integrated assembly and disassembly sequence planning using a GA approach

In a product life cycle, an assembly sequence is required to produce a new product at the start, whereas a disassembly sequence is needed at the end. In typical assembly and disassembly sequence planning approaches, the two are performed as two independent tasks. In this way, a good assembly sequence may contradict the cost considerations in the disassembly sequence, and vice versa. In this research, an integrated assembly and disassembly sequence planning model is presented. First, an assembly precedence graph (APG) and a disassembly precedence graph (DPG) are modelled. The two graphs are transformed into an assembly precedence matrix (APM) and a disassembly precedence matrix (DPM). Second, a two-loop genetic algorithm (GA) method is applied to generate and evaluate the solutions. The outer loop of the GA method performs assembly sequence planning. In the inner loop, the reverse order of the assembly sequence solution is used as the initial solution for disassembly sequence planning. A cost objective by integrating the assembly costs and disassembly costs is formulated as the fitness function. The test results show that the developed method using the GA approach is suitable and efficient for the integrated assembly and disassembly sequence planning. Example products are demonstrated and discussed.     

Dynamic disassembly planning for remanufacturing of multiple types of products

With the increased need for remanufacturing of end-of-life products, achieving economic efficiency in remanufacturing is urgently needed. The purpose of this study was to devise a cost-minimisation plan for disassembly and remanufacturing of end-of-life products returned by consumers. A returned end-of-life product is disassembled into remanufacturable parts, which are supposed to be used for new products after being remanufactured. Each end-of-life product is disassembled into parts at variable levels and through variable sequences as needed, taking into account not only disassembly but also manufacturing, remanufacturing, and holding inventory of remanufacturable parts. This study proposes a mixed integer linear programming (MILP) model for derivation of the optimal disassembly plan for each returned product, under deterministically known demand and return flows. For the purposes of an illustrative example, the proposed model was applied to the formulation of an optimal disassembly and remanufacturing plan of ‘fuser assembly’ of laser printers. The solution reveals that variable-level disassembly of products saves a significant remanufacturing cost compared with full disassembly.     

Partial disassembly sequencing considering acquired end-of-life product age distributions

Uncertainty management is a priority in remanufacturing operations due to uncertain end-of-life (EoL) product quality, quantity and return timing. Ignoring EoL product uncertainty can result in inefficient remanufacturing operations. In this work, an approach is developed that addresses the impact of EoL product quality uncertainty on partial disassembly sequences. Disassembly is performed on nearly all EoL products, yet it is vulnerable to uncertain EoL product quality, defined in this work as the remaining value of an EoL product compared to original equipment manufacturer standards. The developed approach converges to an optimal or near-optimal partial disassembly sequence provided that information regarding acquired EoL product age distributions is known and correlates to EoL product quality. A mathematical framework is introduced to evaluate disassembly sequences based on profit standard deviation and profit probability as well as the traditionally used expected profit. The approach is tested on an example case study to investigate the impact of uncertain quality on the optimal or near-optimal disassembly sequence, expected profit, profit standard deviation and profit probability.     

An optimal algorithm for selective disassembly sequencing with sequence-dependent set-ups in parallel disassembly environment

This study considers selective disassembly sequencing in parallel disassembly environment in which two or more components can be removed by a single disassembly operation. The problem is to determine the sequence of disassembly operations to extract multiple target components while satisfying the precedence relations among disassembly operations. The objective is to minimise the sum of sequence-dependent set-up and operation costs. An integer programming model is developed after representing all possible disassembly sequences using an extended process graph, and then an optimal branch and bound algorithm is proposed that incorporates the methods to obtain the lower and upper bounds as well as a dominance property to reduce the search space. To show the performance of the algorithm, computational experiments are done on various random instances, and the results are reported. In particular, it is shown from the test results that the optimal algorithm requires much shorter computation times than a competitive commercial software package. Finally, a case is reported to illustrate the extended process graph and the solution algorithm.