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.     

拆卸与或图生成及其权重不定问题研究

为了高效地规划装配体的拆卸序列,首先利用生成完备可行子装配体的算法构造所有可行的拆卸操作,并以与或图的形式将所有可行的拆卸操作加以表达,对该与或图进行简约,从而构建能够表达所有可行拆卸序列的拆卸与或图;为了基于该拆卸与或图规划拆卸序列,利用广义权重解决了拆卸与或图中有向边上权重不确定的问题,并给出了广义权重的计算方法;最后,通过实例验证了这种拆卸与或图表达拆卸序列的高效性和用于拆卸序列规划的可行性和有效性.结果表明拆卸与或图是一种可用于拆卸序列规划的高效模型.     

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.     

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.     

基于灰关联和模糊规划的产品设计改进方法

考虑质量屋模型中顾客需求与产品工程特性之间相关关系具有“少数据”、“贫信息”特点,将灰关联分析引入到质量屋模型中求解产品工程特性重要度。为了在产品设计过程中考虑产品开发成本、技术实现困难、产品市场竞争需求以及实际情况中产品开发成本约束存在的模糊性对产品最优设计的影响,构建一种模糊混合整数规划模型,实现产品工程特性最优设计水平。通过一个智能手机产品改进的案列来验证所构建模型的有效性和实用性。     

基于可靠性框图的可靠性建模研究

针对传统可靠性仿真模型建模繁琐、编程困难的问题,以可靠性框图为基础,设计了基于ExtendSim的可靠性建模流程,以两单元并联可修系统为例,建立了基于“致命修复”和“即坏即修”策略的仿真模型,并与解析模型进行了对比验证.仿真结果表明建立的可靠性模型是可信的,且此建模方法易于工程技术人员掌握,具有一定的推广价值．     

产品制造过程质量波动源解释结构模型与应用

基于对产品制造过程波动传递和累积模式、波动影响因素之间关系的分析,运用图论方法将制造过程影响关系拓扑结构简化为有向图和邻接矩阵,提出制造过程波动源解释结构模型的建模步骤;给出基于因果图建立邻接矩阵,基于布尔代数方法编程计算可达矩阵,建立质量波动源解释结构模型,提出改进优先次序和技术建议的工程应用案例。     

含有柔性电缆的复杂系统装配仿真

将装配单元划分为“刚性组件”和“柔性电缆”,从装配对象建模、装配工艺规划和装配过程模拟三个方面对复杂系统的装配仿真方法进行系统的研究。首先,根据刚性组件和柔性电缆的不同特点,给出相应的建模方法,即针对刚性组件的CAD三维建模方法和针对柔性电缆的虚拟布线方法;然后,将装配过程视为拆卸过程的逆过程,提出含有柔性电缆的复杂系统的装配工艺规划方法,其中考虑了电缆形变过程及相应的模拟方法;最后,以装配工艺为基础对仿真对象进行装配仿真。实例表明,所提出的方法可以用于含有柔性电缆的复杂系统装配仿真。     

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。     

复杂机电产品线缆信息本体表达与存储分析

针对复杂机电产品中线缆工程语义信息统一表达难、线缆复杂拓扑结构难以表示和存储的问题,提出基于本体和无向图的复杂线缆信息表达与存储分析方法。首先建立了基于布线设计、装配工艺规划和仿真分析3个维度的线缆信息集成模型;然后利用本体技术对模型信息进行了本体建模,增强了线缆语义信息的表达;最后利用一种水平分割算法将线缆零件划分成一个无向图,在此基础上建立邻接表,实现了线缆零件无向图在计算机中的存储和表达。通过将该方法应用到某线缆零件的实际分析中,验证了文中方法的可行性。     

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.     

Selective disassembly sequencing with random operation times in parallel disassembly environment

Selective disassembly sequencing is the problem of determining the sequence of disassembly operations to extract one or more target components of a product. This study considers the problem with random operation times in the parallel disassembly environment in which one or more components can be removed at the same time by a single disassembly operation. After representing all possible disassembly sequences using the extended process graph, a stochastic integer programming model is developed for the objective of minimising the sum of disassembly and penalty costs, where the disassembly costs consist of sequence-dependent set-up and operation costs and the penalty cost is the expectation of the costs incurred when the total disassembly time exceeds a threshold value. A sample average approximation-based solution algorithm is proposed that incorporates an optimal algorithm to solve the sample average approximating problem under a given set of scenarios for disassembly operation times. The algorithm is illustrated with a hand-light case and a large-sized random instance, and the results are reported.     

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.     

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.     

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.     

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.     

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.