作业车间区间型多属性瓶颈识别方法

针对扰动情形下作业车间瓶颈识别时机器的特征属性难以用确定值表示的问题,采用区间形式描述机器特征属性,构建了区间型多属性瓶颈识别模型,提出了区间TOPSIS多属性瓶颈识别方法.考虑瓶颈识别与瓶颈利用的紧密关系,提出了先进行瓶颈利用再进行瓶颈识别的统一框架.其中瓶颈利用层基于Plant-Simulation 仿真平台设置了机器故障等随机扰动,采用遗传算法对扰动情形下的调度问题进行了优化仿真,获得了适应扰动情形的最优调度优化方案;瓶颈识别层基于调度优化方案,综合考虑了瓶颈的多维特征属性,采用区间TOPSIS多属性瓶颈识别方法识别了瓶颈机器.通过与机器利用率、瓶颈出现率和移动瓶颈识别法等进行比较,验证了所提方法的有效性.最后,分析了制造成本和原材料成本两个参数对瓶颈识别的影响.     

基于正交试验的作业车间瓶颈识别方法

针对作业车间现有瓶颈识别方法的不足,提出了一种基于正交试验的瓶颈识别方法.该方法利用正交表和多种分派规则构造试验方案,以生产系统作业目标为衡量指标,快速便捷地实现瓶颈机器的识别.该方法能够在生产任务执行之前,预先给出瓶颈机器所在,以指导生产计划和相关生产准备.通过与移动瓶颈识别法对不同规模的作业车间调度问题标准算例进行仿真对比,证明了该方法的优越性和可靠性.     

权重信息不完全的区间型多属性群决策的一种新方法

针对权晕信息不完全、决策者的偏好信息和决策矩阵元素均为区间数的不确定多属性群决策问题,提出了一种新的群决策方法.引入决策者的心态指标,得到带心态指标的决策矩阵,再通过求解主、客观偏好的最大总偏差最小化的优化问题,确定属性的权重.利用有序加权几何平均算子给出各方案的群体综合属性值和排序结果.应用实例验证了方法的可行性和合理性.     

作业车间瓶颈簇识别方法

针对传统作业车间调度瓶颈识别方法划定多瓶颈候选集时缺乏科学的划分范围、划分层次和划分依据等问题,提出机器簇、瓶颈簇、主瓶颈簇及阶次的概念,建立了作业车间瓶颈簇的识别模型.考虑机器的主次之分和多维特征属性,基于聚类思想及多属性决策理论提出了作业车间瓶颈簇的识别方法.选择识别瓶颈的机器特征属性,采用免疫进化算法获得调度优化方案并计算机器的特征属性值;采用层次聚类法,获得不同距离下机器簇的集合及其树状结构图;基于理想解相似度顺序偏好法确定并比较机器簇的簇中心,识别出瓶颈簇和非瓶颈簇;对瓶颈簇的子簇依次进行比较,通过多次识别逐步确定出多阶主瓶颈簇集合.最后,采用24组作业车间调度问题标准算例,将所提方法与移动瓶颈识别法、正交试验识别法、机器负荷识别法等进行比较,证明了其可行性及优势.     

基于犹豫模糊集的机器自主及人机联合多属性决策方法

为了充分利用产品评价数据中的信息并结合专家经验选出客观合理的产品方案,将犹豫模糊集理论应用于工业产品评价数据处理,提出一种机器自主决策方法和两种人机联合决策方法。机器自主决策方法通过建立产品评价数据犹豫模糊决策矩阵,使用TOPSIS框架进行方案排序实现了无人参与的自动化决策;按照决策者是否参与隶属度打分,提出两种情况下的人机联合决策方法,构建了人机联合犹豫模糊决策矩阵,实现了人机协同决策。以宝信带钢产品的性能评估与选择为案例,验证了所提方法的实用性。     

面向云制造作业车间的机器能力界定方法

针对面向云制造作业车间,研究不同扰动情形下机器保护能力的设置以及参与云服务能力的划分问题。揭示了系统有效产出随机器能力增长变化的规律。提出了能力松弛率和可用调度时间的概念,建立了面向云制造作业车间的机器能力界定模型。设定了不同的非瓶颈能力松弛率和扰动水平,通过对非瓶颈能力的分级利用,得到了非瓶颈松弛率对系统性能的影响曲线。基于聚类算法提出了非瓶颈能力界定方法,给出了不同扰动水平下每台非瓶颈机器的生产能力、保护能力和云服务能力,为企业自制与云服务能力划分与利用提供了决策依据。     

基于贝叶斯网络的机器全生命周期安全性评估模型

目前机器安全性评估方法主要考虑机器使用时的安全性能。为更科学和完整地评估机器的安全性，还应关注机器在运输、安装、维护和拆解等生命周期中的机器安全性影响因素。以液压机为例分析了机器生命周期的相关任务及其安全影响因素，并利用贝叶斯网络刻画安全影响因素间的复杂依赖关系，构建了面向机器全生命周期的安全性评估模型。应用实例表明，该模型能综合考虑机器各生命周期的安全风险因素，对机器安全性做出合理评价，并能依据贝叶斯网络的反向推理功能找出影响机器安全的关键要素。     

求解流水车间调度问题的瓶颈指向启发式算法

针对最小化时间表长的流水车间调度问题,提出一种根据工件加工时间特征构建工件调度的瓶颈指向启发式算法。首先,为构建初始工件排序,充分利用各机器负荷一般不相等的特点,瓶颈阶段前加工时间较短而之后加工时间相对较长的工件优先开始加工;其次,当有工件等待加工时,根据工件在瓶颈机器前或后加工时间的特征调整工件加工顺序;最后,采用邻近工件成对交换和插入的方式改进初始调度。当瓶颈机器趋于中间阶段,或瓶颈机器上工件的加工时间趋于增加时,求解效果较好。数据实验表明算法是有效的。     

扰动情形下瓶颈利用对作业车间调度的影响

针对瓶颈100%利用后无法应对扰动而造成调度方案无法执行的问题,提出了瓶颈能力释放率和瓶颈能力释放区的概念,研究了瓶颈利用对作业车间调度的影响.在识别瓶颈的基础上,设置瓶颈能力释放率等级;进行瓶颈能力的按级利用,通过遗传算法优化投料次序,输入Plant-Simulation进行模拟仿真,得到各级瓶颈能力释放率的初始调度优化方案;设置机器故障、缓冲、工艺路线更改、交货期变动等随机扰动,对各级初始调度优化方案进行再次模拟仿真,得到随机扰动下各级瓶颈能力释放率的最优调度方案;分析了随机扰动下不同等级的瓶颈能力释放率对作业调度方案的影响.算例结果证实了瓶颈扰动情形下瓶颈100%充分利用并非科学,生成的调度方案鲁棒性差且调度执行结果并非最优的结论.另外,瓶颈非100%有限利用存在最优的瓶颈能力释放率和瓶颈能力释放区,在此释放区之外,过多或过少的瓶颈保护能力对调度方案都有较大的负面影响.     

决策矩阵在空调产品概念选型阶段的应用

对决策矩阵进行了介绍,对决策矩阵的应用流程进行了分析.在空调产品概念选型阶段应用决策矩阵,不但可以缩短开发周期,提高设计效率,而且能够降低产品成本,效果良好.     

虚拟轴机床定位方法

提出一种基于改进的多传感器一致性数据融合的虚拟轴机床定位方法,在虚拟轴机床动平台的位姿测量中使用了视觉技术与电子罗盘,解决了虚拟轴机床动平台上的主轴定位问题。此方法将虚拟轴机床各根杆上的编码器信息、视觉信息与动态惯性的测量数据进行数据融合,经过动态计算获得置信距离的关系矩阵,虚拟轴机床动平台的位置与姿态的精确定位得到了保证。经过一个单轴单方向的运动测量简化试验,将虚拟轴机床动平台6自由度位姿的测量作为研究对象,对其进行仿真试验。试验结果也表明了该定位方法有效可行。     

用蚁群算法求解关节式坐标测量机的最佳测量区

本文提出了一种求解最佳测量区的方法,以进一步提高关节式坐标测量机的测量精度。首先,根据关节式坐标测量机的测量模型,建立了基于圆编码器测角误差的关节式坐标测量机误差模型。利用蒙特卡洛理论得到6个关节转角的随机数,采用数值法仿真分析测量机的测量空间。然后将包含测量空间的一立方体区域等间隔切割成343个小立方体区域,采用蚁群算法确定每个小区域由于圆编码器误差所引起的最大测量误差。最后,通过比较找到其中最大测量误差最小的区域,即为最佳测量区。研究结果表明,对于所研究的关节式坐标测量机,各个小区域的最大误差为0.069 9~0.189 6mm,其中最小值为0.069 9mm的区域为-100mm≤x≤100mm,-100mm≤y≤100mm,400mm≤z≤600mm。采用本文方法确定的最佳测量区在测量空间内为一个立方体区域,故在最佳测量区进行较高精度的测量具有实用性和可操作性。     

多分辨率快速圆检测在抑菌圈测量系统中的应用

本文提出了多分辨率快速圆检测的算法。基于多分辨率的框架,在低分辨率下快速检测圆心和半径的信息,然后映射到高分辨率中,确定圆的边缘和圆心所在的局部区域,减少处理单元的数量,并提出局部单圆验证算法获得精确的圆心和半径信息。本文提出的算法克服了圆检测精度与时空复杂度的矛盾,在高分辨率、多圆、多噪声的情况下,算法的效率下降较少。最后将圆检测算法应用于基于机器视觉的抗生素残留量检测系统中进行抑菌圈检测,结果表明处理时间短、检测精度高。     

A multi-stage fluctuation smoothing method for multiple bottlenecks in wafer fabrication

The performance of a wafer fabrication system is constrained by its bottlenecks, which is often affected by the system fluctuations and unpredicted events, e.g., machine breakdown. Considering the re-entrant process flow in wafer fabrication, we propose a scheduling method that divides the process flow into several stages and protects the bottleneck step at each re-entrant stage from the system fluctuations. Furthermore, due to the multiple bottlenecks in wafer fabrication system, we identify the bottlenecks by sensitivity analysis on machines’ capacity. Then, during the real-time scheduling, the bottlenecks with stronger constraints are assigned with higher priority than the bottlenecks with weaker constraints. Finally, a set of simulation experiments are performed to validate the effectiveness of the proposed method.     

面向数控加工的大型螺旋桨桨叶的余量估算问题研究

针对大型螺旋桨数控加工的实际需求，为解决多桨叶螺旋桨毛坯测量中的余量估算、桨叶的z向纠偏、后倾角纠偏等多个问题，提出了基于最小二乘法的毛坯寻位数学模型。根据大型螺旋桨的实际情况，对该问题的求解算法——遗传算法进行了改进，不仅避免了寻优过程中收敛到局部最优值，而且提高了计算效率。通过实验，验证了算法的实用性和可靠性。     

A genetic algorithm for the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties

In this paper, we consider the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties, with no machine idle time. The problem is strongly NP-hard. We proposed a new mathematical model, with non-linear terms and integer variables. We develop a genetic algorithm for solving the problem in medium and large size. The proposed procedure is compared with optimal solutions for the smaller instance sizes. The genetic procedure is also quite close to the optimum and provided an optimal solution for most of the test problems. Numerical examples show that the proposed algorithm is efficient and effective. Scheduling with early and tardy penalties has received extensive attention from the scheduling community because of its practical significance. Single machine scheduling environments actually occur in several practical applications. Also, the performance of many production systems is often determined by the schedules for a single bottleneck machine. Furthermore, the study of single machine problems frequently provides outcomes that prove functional for more complex scheduling areas.     

Integrating theory of constraints and particle swarm optimization in order planning and scheduling for machine tool production

Order planning and scheduling has become a significant challenge in machine tool enterprises, who want to meet various demands of different customers and make full use of existing resources in enterprises simultaneously. Based on the Theory of Constraints, a three-stage order planning and scheduling solution is proposed to optimize the whole system performance with bottleneck resources' capability as the constraints. After the identification of bottleneck resources, multicriteria priority sequencing is made with order per-contribution rate, order delivery urgency, and customer importance as the evaluation criteria, and the evaluation result deduced from the ideal point function can decide the production mode of all orders and products. Then, a PSO-based multiobjective optimization model is set up with minimizing bottleneck machines' makespan and minimizing total products' tardiness as the two objectives. Finally, the proposed solution is applied in one machine tool enterprise by integrating into Baosight MES (Manufacturing Execution System) system. In addition, some comparisons are carried out to evaluate the proposed PSO optimization method. The comparison with actual report shows that PSO can satisfy enterprise's needs better than before; the comparisons with genetic algorithm and ant colony optimization algorithms indicate that PSO is more effective than the others because of its faster convergence rate.     

Postprocessor development of a five-axis machine tool with nutating head and table configuration

The postprocessor is an important interface that transforms cutter location data into machine control data, and in a five-axis machine tool is highly complex because the simultaneous linear and rotary motions occur. Since most works of the five-axis postprocessor method have dealt only with the orthogonal machine tool’s configuration, this study presents a postprocessor scheme for two types of five-axis machine tools, each with a nutating head and a table whose rotational axes are in an inclined plane. The benefit of such a configuration is that it allows switching from vertical to horizontal machining by a single machine. The general analytical equations of NC data are obtained from the forward and inverse kinematics and the homogeneous coordinate transformation matrix. The linearization algorithm for the postprocessor is developed to ensure the machining accuracy. The presented algorithm is implemented using a window-based five-axis postprocessor with nutating axes, and programmed in Borland C++ Builder and OpenGL. A simulation is performed using solid cutting software and a trial-cut experiment was conducted on a five-axis machine tool with a nutating table to elucidate the accuracy of the proposed scheme.     

基于两种瓶颈度的制造车间多瓶颈动态预测方法

针对制造车间多瓶颈预测问题,提出一种基于两种瓶颈度的多瓶颈动态预测方法,以在合理认定瓶颈责任的前提下实现系统多瓶颈的连续准确预测。首先,建立综合瓶颈度和独立瓶颈度的概念模型,并以时间、质量和成本为参数,构建其数学模型;然后,构建包含多瓶颈双层预测机制、瓶颈多态性分析和瓶颈指数迭代预测模型的多瓶颈动态预测方法;最后,将多瓶颈动态预测方法、单瓶颈度法和PBM法运用至某汽车产品总装线,以验证该方法有效性。     

Cycle time variance minimization in dynamic scheduling of single machine systems

In this paper, we study the minimization of variance of cycle times in a dynamic single machine system where jobs arrive continuously over time. Numerous production systems give rise to single machine models, and a multiple-machine environment where the performance of a bottleneck machine determines the performance of the entire system reduces to a single machine problem [16]. Minimizing cycle time variance helps in safe predictions of the completion of job production and thus in providing the same quality of service to the customers. This allows an improved ability to meet the due dates reliably, and thus the greater coordination with further downstream operations on the jobs, as highly preferred in semiconductor manufacturing. Scheduling the bottleneck process to minimize the time of presence of the jobs in process minimizes the deterioration of cycle time-related performance measures. Low values of cycle time-related measures are also preferred for low risk of wafer contamination associated with it during processing. New scheduling rules are developed to minimize both the cycle time variance and the maximum cycle time for single machine system, wherein the machine/process is always utilized to the maximum extent and in the extreme case is heavily loaded with jobs for processing. The performance of the proposed rules is compared with the rules available in the literature and the results are presented for the objectives of minimizing cycle time variance and maximum cycle time at higher levels of machine utilization.