基于快速成型系统的集成制造系统研究

通过简要介绍快速成型技术在国内外发展的现状 ,针对国内在此领域发展的不足 ,提出一种基于快速成型系统的集成制造系统体系 ,并详细阐述了快速成型与反求工程、快速模具制造的集成技术。该系统综合了快速成型、快速反求技术、快速模具制造、虚拟制造、网络等配套技术 ,可大大提高产品的开发速度 ,增强企业的竞争能力。     

改进基本矩阵计算和优化的多摄像机并行标定算法

多摄像机系统具有摄像机数目多、空间位置分布复杂特点,导致多摄像机标定效率低。基本矩阵计算和非线性优化是摄像机标定算法的关键步骤。针对标定物空间位置相互独立性,改进随机抽样一致性(RANSAC)的基本矩阵计算和简化非线性优化的增量方程,提出多摄像机系统的并行标定算法。该算法挖掘多摄像机标定过程的内在并行化,从而提高了标定的时间效率。相比于传统的多摄像机标定算法,并行算法的时间复杂度从O(n3)降为O(n)。实验结果表明：使用多摄像机系统并行标定算法在不损失精度的同时能够减少标定时间,实现多摄像机系统的快速标定。     

可重构制造系统的多Agent模型

论文在介绍可重构制造系统重构方法的基础上,给出了可重构制造系统多Agent模型的结构,并详细描述了基于该模型的可重构车间加工系统的重构算法,最后对重构算法进行仿真验证了该算法的可行性。     

基于低秩矩阵恢复的目标快速检测方法研究

为了实现快速运动目标检测,利用低秩矩阵恢复原理进行视频前景检测,主要针对低秩矩阵恢复算法存在的耗费大部分运算时间且运算较为复杂的奇异值分解问题,应用统一计算结构装置(CUDA)第三方库实现加速计算奇异值分解的低秩矩阵恢复算法优化,得到快速且高效的前景检测方法。基于开源视频序列实验,与原有的低秩矩阵恢复算法进行各项参数的比较,其中加速倍数达一倍以上。实验结果证明,经过优化的算法运算时间变短,具有更高效率。     

基于可辨识矩阵的快速粗糙集属性约简算法

Karno Bozi提出的Core Searching算法在向约简中插入候选属性的时候,根据属性出现次数需要循环查找可辨识矩阵中的所有剩余项,直至矩阵为空,导致计算量较大和结果中冗余属性存在的可能.基于Core Searching算法提出通过给属性设立计数器的基于可辨识矩阵的快速属性约简算法,实例分析表明,该算法与Core Searching算法相比,在计算量减少和循环次数减少的同时能得到更简约的结果,是一种快速、高效的属性约简算法.     

可重构计算系统的研究与应用

可重构计算系统既具有在制造后的可编程性．又能提供较高的计算性能和计算密度。对可重构计算系统的基本概念以及系统构成概要介绍的基础上,通过一个实例给出了可重构计算系统的一种快速实现方法,与具有相同功能的其他系统相比．这种系统更灵活和高效。     

线性定常系统仿真的广义增广矩阵法

对于线性定常系统的数字仿真,增广矩阵法是一种高精度快速算法。本文给出了增广矩阵法的改进算法,由此建立了基于增广矩阵法的一般仿真模型。文中针对输入函数的不同情况给出了几种仿真计算模型。容易推证,原有的增广矩阵法乃是以本文算法给出的仿真计算模型之一的一种特例。     

快速r循环分块Jacket变换

由中心权重哈达玛变换发展而来的Jacket变换,因其正交性、求逆简单和拥有快速算法等特点逐渐受到关注。Jacket变换可应用于信号与图像处理、数字移动通信、量子编码、大数据处理等领域。为了进一步丰富Jacket变换理论,提出了一种通用的循环分块Jacket变换(r-circulant block Jacket transform,r-CBJT)。同时基于基本的r循环分块矩阵的性质,给出了任意阶r循环分块Jacket变换矩阵的构造方法。随后进一步推导了任意阶r循环分块Jacket变换矩阵的快速构造与分解算法,该快速算法可表示为单位矩阵与低阶Jacket矩阵连续克罗内克积的迭代形式。相比直接计算算法,该快速算法拥有更高的计算效率,且该快速算法也可应用于具有类似结构的其他类型的r循环分块Jacket变换。     

非圆信号与圆信号共存下的快速方位估计算法*

针对非圆信号和圆信号共存时,信号的波达方向估计算法运算量较大的问题,提出了一种可同时估计非圆信号和圆信号DOA的快速算法。首先,利用观测数据及其复共轭构造中心复共轭对称矩阵,通过双映射定理可将该矩阵转换为实矩阵;然后,利用多级维纳滤波,无需计算阵列协方差矩阵及对其进行特征分解,仅通过对接收的实数据矩阵递推可快速求出观测数据的信号子空间;最后,利用酉ESPRIT算法的实值性,不必谱峰搜索,在保证DOA估计精度的同时可大大降低算法的计算复杂度。仿真结果验证了算法的有效性。     

N皇后问题的快速搜索算法

回溯算法是解决N皇后问题的经典算法,最坏情况下,它的搜索时间和皇后维数N成指数关系,无法满足基于Q_矩阵的LDPC码这种编码方案对码长的要求.介绍了一种解决皇后问题的快速搜索算法,它是使碰撞数最小化的本地搜索算法,这种算法的性能和回溯算法相比有极大的提高,搜索时间和皇后维数N基本成线性关系,并且有较强的灵活性,因而对于Q-矩阵LDPC码这种编码方案而言,快速搜索算法更为合适.     

机床产品制造系统能效的最优控制

本文结合机床产品制造系统的能量流特性,研究机床产品制造系统能效的最优控制.首先,利用无线传感器网络,构建制造系统能效感知网络,并设计了网络能量高效的通信协议,实时获取制造系统的能效数据.进而,利用能效感知数据,分别从单机设备局部优化与综合资源全局优化两方面,设计能效优化控制算法.根据单机设备任意两工步间空载能耗特性,给出单机设备空载能效最优控制模型.同时,建立以缩短生产周期、减少机器空转时间、提高产品合格率为优化目标的综合生产资源能效多目标优化方案.考虑到所论综合资源能效优化问题是离散组合优化问题,本文提出了文化基因支配排序粒子群算法进行求解,并采用层次分析(analysis hierarchy process,AHP)决策方法从Pareto解集中选取最优综合能效的优化策略.最后,利用实例与仿真相结合的方法,验证了文中所提方法的有效性.     

柔性制造单元的一种调度算法

本文提出了一种新的柔性制造单元的调度算法,它在离散周期控制的基础上加上事件中断以适应系统状态的随机干扰,在流控制中,我们不仅决定产品类型的混合比,同时决定每种工件在各加工路径的比。文中给出了一个制造单元的仿真结果,它表明了算法的有效性。     

粒子群遗传算法在离散制造业排产中的研究

在离散制造业中,排产方法的优劣直接影响生产的效率.为了使算法更好的应用到排产当中,首先分析离散制造业的生产特点.同时,为了提高算法的搜索性能,分析遗传算法与粒子群优化算法的优缺点,提出了一种粒子群遗传混合算法(PSO_GA).该算法中,在遗传算法的基础上引入参数,从而动态控制每次迭代交叉变异比,进而提高群体多样性.同时为了克服遗传算法自身收敛速度慢的缺点,在适当的迭代周期内引入粒子群优化算法,从而提高算法的搜索速度和精度.最后,针对排产模型进行仿真实验,结果表明该算法具有很好的搜索性能.     

Data-driven dynamic bottleneck detection in complex manufacturing systems

Production (throughput) bottlenecks are the critical stations defining and constraining the overall productivity of a system. Effective and timely identification of bottlenecks provide manufacturers essential decision input to allocate limited maintenance and financial resources for throughput improvement. However, identifying throughput bottleneck in industry is not a trivial task. Bottlenecks are usually non-static (shifting) among stations during production, which requires dynamic bottleneck detection methods. An effective methodology requires proper handling of real-time production data and integration of factory physics knowledge. Traditional data-driven bottleneck detection methods only focus on serial production lines, while most production lines are complex. With careful revision and examination, those methods can hardly meet practical industrial needs. Therefore, this paper proposes a systematic approach for bottleneck detection for complex manufacturing systems with non-serial configurations. It extends a well-recognized bottleneck detection algorithm, “the Turning Point Method”, to complex manufacturing systems by evaluating and proposing appropriate heuristic rules. Several common industrial scenarios are evaluated and addressed in this paper, including closed loop structures, parallel line structures, and rework loop structures. The proposed methodology is demonstrated with a one-year pilot study at an automotive powertrain assembly line with complex manufacturing layouts. The result has shown a successful implementation that greatly improved the bottleneck detection capabilities for this manufacturing system and led to an over 30% gain in Overall Equipment Effectiveness (OEE).     

Agile Manufacturing and Management of Variability

In this study, the relationship between agile manufacturing and management of variability is discussed. First, the key concepts of agility and agile manufacturing are introduced. These key concepts are then related to the management of variability. Previous studies on the modeling of variability of manufacturing systems are reviewed. Then the effects of variability of the structure of the production system, and also the processing time variability on the performance of a manufacturing system are studied by utilizing a simple model of a synchronous production line with identical stations and random processing times. Numerical results that examine the effects of the coefficient of variation of service time and the number of stations on the variability of the cycle time are also given.     

制造系统的递阶滚动优化调度模型

研究的对象是只有一台不可靠（failure-prone)机器的非完全柔性制造系统，该系统能生产多种产品，但在同一时刻只能生产一种产品，并且当机器由生产一种产品向生产另一种产品切换时，需要考虑setup时间及其成本，待决策变量是setup序列及产品生产率，本文基于非完全柔性制造系统的特点，引入递阶层控的思想，采用新的递阶结构框架和阈值控制策略，对问题进行分解，建立了考虑setup时间及成本的递阶流率控制最优化调度模型，并给出了递阶的滚动优化算法，仿真结果表明，这种调度策略更易于工程实现。     

Application of genetic algorithm to computer-aided process planning in distributed manufacturing environments

In a distributed manufacturing environment, factories possessing various machines and tools at different geographical locations are often combined to achieve the highest production efficiency. When jobs requiring several operations are received, feasible process plans are produced by those factories available. These process plans may vary due to different resource constraints. Therefore, obtaining an optimal or near-optimal process plan becomes important. This paper presents a genetic algorithm (GA), which, according to prescribed criteria such as minimizing processing time, could swiftly search for the optimal process plan for a single manufacturing system as well as distributed manufacturing systems. By applying the GA, the computer-aided process planning (CAPP) system can generate optimal or near-optimal process plans based on the criterion chosen. Case studies are included to demonstrate the feasibility and robustness of the approach. The main contribution of this work lies with the application of GA to CAPP in both a single and distributed manufacturing system. It is shown from the case study that the approach is comparative or better than the conventional single-factory CAPP.     

Clustering algorithm for solving group technology problem with multiple process routings

Cell formation is an important problem in the design of a cellular manufacturing system. Most of the cell formation methods in the literature assume that each part has a single process plan. However, there may be many alternative process plans for making a specific part, specially when the part is complex. Considering part multiple process routings in the formation of machine-part families in addition to other production data is more realistic and can produce more independent manufacturing cells with less intercellular moves between them. A new comprehensive similarity coefficient that incorporates multiple process routings in addition to operations sequence, production volumes, duplicate machines, and machines capacity is developed. Also, a clustering algorithm for machine cell formation is proposed. The algorithm uses the developed similarity coefficient to calculate the similarity between machine groups. The developed similarity coefficient showed more sensitivity to the intercellular moves and produced better machine grouping.     

具有固定生产周期的制造系统的控制策略及其实现

考虑一台机器组成的制造系统,其中加工时间是一个常数,而机器的维护时间是一随机变量,文献（５）证明了这类制造系统生产率的最优控制策略为切换曲线策略,该策略由一个参数完全确定,但在一般情况下该参数很难求解。并给出用扰动分析方法求解该策略的算法。     

基于制造流程和制造特征的零件工时估算

为了解决以往相似零件工时估算方法的精度和效率之间的矛盾,提出一种精度高且易于编程实现进而提高效率的工时估算方法。研究加工工艺对制造特征工时的影响机理,提出制造特征组合的概念,并在此基础上实现生产准备、上下料、换刀、粗加工、精加工五个工时数据库的开发。提出制造流程图的概念并描述其绘制方法。通过对历史零件制造流程图的修改及工时数据库中数据的调取计算实现对相似零件的工时估算。以某企业生产的一个零件族中相似零件的工时估算为例,验证所提出的估算方法的有效性。