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.     

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。     

基于改进遗传算法的异步并行拆卸序列规划

针对考虑优先关系约束和机器工作区域冲突约束的异步并行拆卸序列规划问题,提出加入路径重连策略的遗传算法。通过定义零部件之间的与或优先关系,对拆卸方向进行简化。且根据工作区域冲突约束,避免零部件拆卸过程中产生工作区域冲突。在此基础上,对种群进行编码解码,并加入路径重连算子,将遗传算法迭代得到的精英解进行路径重连以增强算法的局部搜索能力。最后通过多个实际案例证明算法的有效性。     

基于自动拆卸过程的装配序列生成方法研究

装配序列生成是装配工艺规划的基本任务,设计了一个基于自动拆卸过程的装配序列生成算法。首先,进行自动拆卸仿真,通过过程中的干涉检查生成可行的装配序列集。然后,定义了三类装配序列优先约束规则,对可行序列集进行过滤选择,得到可用于最终评价的少量装配序列。该算法在SolidWorks平台上得到了实现,给出了实例验证。     

基于模糊推理的舰炮故障检测方法研究

基于模糊推理知识和模糊神经网络的理论，根据舰炮运转时发出的声音信号，提出了舰炮系统的故障检测诊断方案，详细介绍了信号提取的方法和故障分析的算法。     

基于模糊推理的数据手套传感器建模方法

分析了应用于数据手套CA SGlove上的传感器的性能和特点，提出了一种基于模糊推理的传感器建模方法：首先利用模糊推理建立传感器的模型，然后利用采样数据进行离线学习确定模型中的参数。实验证明该方法在只获取传感器最小和最大两个标定值的情况下，能够取得和分段线性插值相近似的结果。     

结构选型中基于模糊推理的评判系统

本文在基于自组织竞争神经网络检索机制与模糊逻辑评判的实例推理系统基础上，讨论了该系统用于结构选型过程中的模糊推理过程；建立了高层建筑结构高度适应性的模糊评价标准；并将其应用于模糊推理系统中；以剪力墙结构高度适应性评价为例展示了推理过程。证明采用模糊推理系统作为设计型结构选型决策支持系统的评价模块是理想的解决方案。     

基于Mamdani模糊推理的核动力装置技术状态评估

分析了传统二元逻辑应用于核动力装置部分失效技术状态评估时的局限性，概述了Mamdani模糊推理的基本技术；结合状态评估实例，提出了基于Mamdani模糊推理的核动力装置系统级的技术状态评估方法，为系统部分失效的技术状态评估提供了一种新的技术途径。     

复杂环境下基于目标指引的RRT*路径规划算法

机器人路径规划算法需应对运动过程中遇到的各种复杂环境。针对快速扩展随机树(RRT)算法规划时间长、产生新节点随机性大、盲目性强的缺点,提出基于目标指引的RRT*路径规划算法。该算法在障碍物和目标点处分别产生虚拟势场,引入引力函数和斥力函数使得生成的随机点具有目标性,随机点朝向目标点方向产生,降低盲目性和随机性;回归策略和动态自适应步长策略减少规划时间和产生冗余点的数量。当环境复杂时,提出带有预测机制的模糊推理策略,以解决机器人在U型陷阱下易产生的局部死锁现象。在动态环境下,提出重规划策略使机器人拥有动态避障能力。最后,在树莓派智能小车上进行了实验测试,结果验证了该算法的有效性。     

喷油器拆卸工具的研制

柴油发动机的维修涉及修理的各个方面,其中发动机喷油器的维修保养,有时因为使用时间长造成喷油器在拆卸过程中存在一定的难度,同时也没有一种比较专业的工具进行使用,研制一种专业工具使用在现场维修中,对于提高劳动实效,降低劳动轻度都有很大的益处。     

维修拆装工艺规划系统的研究

结合装备维修活动中的拆卸与装配问题,明确了研发面向维修的拆装工艺规划系统的必要性.提出了一个拆装工艺规划系统的构架,论述了系统的主要功能模块、工作流程以及所采用的关键技术.实现了装配建模、拆装序列规划、拆装序列评估与优化,以及拆装作业仿真等关键功能.实践表明该原型系统的设计切实可行,具有良好的应用前景.     

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。     

基于实例的模糊工艺推理技术研究

介绍了智能型CAPP系统的体系结构,研究了工艺实例分类索引树机制和基于模糊推理的工艺实例匹配算法,解决了具有复杂特征属性的工艺实例相似检索问题,实现了基于实例模糊推理的智能CAPP系统.     

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.     

Disassembly line balancing using linear physical programming

Disassembly is the separation of a product into its constituent parts in a systematic way. It has gained importance recently due to its vital importance in product recovery. Cost-effective implementation of disassembly operation has a direct impact on the profitability of product recovery activities (recycling, remanufacturing etc.). Although it is possible to carry out disassembly operations in a disassembly station or in a disassembly cell, the highest productivity is achieved in a disassembly line. The output of a disassembly line can be maximised only if the line is balanced. A linear physical programming-based disassembly line balancing method is proposed in this study. This method was used to balance a mixed-model disassembly line and the effectiveness of the method was illustrated by analysing the results.     

基于可信性理论的模糊环境下再制造生产计划

针对再制造系统生产计划问题,分析了再制造系统的特点。以一般再制造系统为原型,在可回收产品数量、单位产品拆卸时间、单位零部件再制造加工时间以及客户需求不确定情况下,考虑回收、拆卸、再制造加工、重新装配的能力限制,以总成本最小化为目标,构建了模糊再制造系统混合整数规划模型。利用可信性理论给出了模糊模型的清晰等价形式。最后,通过算例分析了不同置信水平选取对再制造成本的影响,验证了模型对再制造企业生产计划制定的适用性。     

Disassembly line design with multi-manned workstations: a novel heuristic optimisation approach

As the first and the most time consuming step of product recovery, disassembly is described as the systematic separation of constituent parts from end-of-life products through a series of operations. In this context, designing and balancing disassembly lines are critical in terms of the efficiency of product recovery. Recent research on disassembly line balancing (DLB) has focused on classical stations where only one worker is allocated. However, such a line results in larger space requirement and longer disassembly lead time. In this paper, disassembly line balancing problem (DLBP) with multi-manned stations is introduced to the relevant literature as a solution to overcome these disadvantages. A mixed integer linear programming (MILP) model and two novel framework heuristic algorithms are developed to minimise the number of workers and workstations. MILP model has been applied to a dishwasher disassembly system. The application results indicate the superiority of establishing multi-manned stations over classical disassembly system design with single-worker stations with shorter disassembly lead time (80.9%) and line length (60.2%). Moreover, the proposed heuristics have been compared on newly generated test problems (instances) for DLBP. The results validate that the heuristics provide acceptable solutions in a reasonable amount of time even for large-sized problems.     

Robotic disassembly sequence planning using enhanced discrete bees algorithm in remanufacturing

Increasing attention is being paid to remanufacturing due to environmental protection and resource saving. Disassembly, as an essential step of remanufacturing, is always manually finished which is time-consuming while robotic disassembly can improve disassembly efficiency. Before the execution of disassembly, generating optimal disassembly sequence plays a vital role in improving disassembly efficiency. In this paper, to minimise the total disassembly time, an enhanced discrete Bees algorithm (EDBA) is proposed to solve robotic disassembly sequence planning (RDSP) problem. Firstly, the modified feasible solution generation (MFSG) method is used to build the disassembly model. After that, the evaluation criterions for RDSP are proposed to describe the total disassembly time of a disassembly sequence. Then, with the help of mutation operator, EDBA is proposed to determine the optimal disassembly sequence of RDSP. Finally, case studies based on two gear pumps are used to verify the effectiveness of the proposed method. The performance of EDBA is analysed under different parameters and compared with existing optimisation algorithms used in disassembly sequence planning (DSP). The result shows the proposed method is more suitable for robotic disassembly than the traditional method and EDBA generates better quality of solutions compared with the other optimisation algorithms.     

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.     

工程液压油缸的拆解能量分析

拆解能量是产品可拆卸性评价的关键指标,对产品的可拆卸性设计和再制造回收决策具有重要意义.基于图论思想,构建油缸的拆解约束图并生成油缸的拆卸序列;定义零部件拆解能量的组成模型和传送带移出零部件的能量消耗模型;讨论油缸零部件间典型连接方式与约束解除所消耗能量的数学关系.以某型号工程液压油缸为例,对其零部件的不同拆卸序列进行总的拆解能量分析计算与评估,为油缸的拆卸序列规划、专用拆卸设备设计和液压油缸的可拆卸性设计提供参考.