MRPⅡ、JIT、TOC生产计划与控制比较研究

在对MRPⅡ、JIT、TOC三种生产管理思想的适用性和优缺点分析、比较的基础上，在生产计划与控制的不同层面，根据不同要求，对MRPⅡ、JIT、TOC进行了定位分析，并把MRPⅡ定位在厂级或企业级，负责主生产计划、物料需求及各车间零部件的月、周计划；TOC定位在车间级，负责车间或工段工序日作业计划与调度、物料的投放；JIT定位在生产现场，负责作业计划的执行、生产的控制和现场的反馈。     

MRPII、JIT、TOC生产计划与控制比较研究

在对MRPII、JIT、TOC三种生产管理思想的适用性和优缺点分析、比较的基础上,在生产计 划与控制的不同层面,根据不同要求,对MRPII、JIT、TOC 进行了定位分析,并把MRPII定 位在厂级或企业级,负责主生产计划、物料需求及各车间零部件的月、周计划;TOC定位在车 间级,负责车间或工段工序日作业计划与调度、物料的投放;JIT定位在生产现场,负责作业 计划的执行、生产的控制和现场的反馈。     

MRPⅡ、JIT与TOC集成生产管理模式研究及应用

制造资源计划(MRP Ⅱ)、准时生产(JIT)与约束理论(TOC)均是降低库存、提高生产率和企业生产管理水平的重要理论和工具.在对三者的特点进行分析和比较的基础上,提出一种将MRP Ⅱ、JIT与TOC集成的生产管理模式,建立MRP Ⅱ、JIT和TOC集成生产管理模型,并开发车间制造过程信息系统.该系统已应用于某阀类车间的生产管理中,取得了良好的应用效果.     

集成化车间作业计划动态关键路径编制算法

针对单件小批生产加工装配式制造的特点,结合车间作业计划与物料需求计划的集成化管控需求,提出了基于生产过程网络图的动态关键路径作业计划编制算法.算法按照零部件加工装配过程中的工艺顺序和装配关系,将计划期内订单的形成过程抽象化为生产过程网络图,并将物料需求计划映射为网络图中的节点,进行生产能力控制和加工装配约束.以生产过程网络图为作业计划编制的对象模型,以订单的交货期为依据,采用倒排的方式,通过动态寻找网络图中的关键路径来确定车间作业计划顺序和资源分配.通过某密封产品生产企业机加车间生产计划编制的实例,证明了该算法能快速有效地在有限生产能力条件下编制高效可行的车间作业计划,保证作业计划与物料需求计划的一致性.     

面向状态的车间控制策略研究

当前的生产计划和控制系统较好地解决了企业中期的物料需求计划与能力需求计划问题,而车间以下层次的生产作业计划与控制是其薄弱环节。这里通过对现代车间生产活动控制的功能、目标和现代车间制造系统基本特征的考察、分析,揭示了现代车间控制的根本矛盾,提出了面向状态的车间控制策略和方法并进行了应用研究。     

CIMS环境下生产计划与控制系统的研究与开发

本文在CIMS环境下,将物料需求计划、能力需求计划与车间生产作业计划、车间作业管理集成于一体,详细介绍了基于MRPⅡ的生产计划与控制系统的总体结构与开发策略,用人机交互的方式可以非常方便地制定出主生产计划并对生产作业进行有效地控制.     

MES:一个有效的制造执行过程计划和控制技术

指出MES是在企业资源计划和生产经营计划与制造设备控制之间的一种面向制造执行过程管理和控制的有效技术。通过对MES的定位分析、功能模型分解、典型案例的应用效果介绍，系统地阐述了制造执行系统。     

主件网络图与部套制造树之间的映射关系研究

网络计划和物料需求计划相结合,可以有效解决单件小批生产类型企业的生产计划与控制问题,其结合的关键是建立网络图和详细的产品结构,以及工艺流程之间的映射关系.根据大型复杂产品的生产特点,采用主件网络图和部套制造树为网络计划和物料需求计划的数据模型,提出了二者的定义和规范化要求,然后归纳了二者之间的映射规则.在此基础上,提出了映射算法和链分解方法,映射方法用于根据部套制造树提取主件网络图,链分解方法用于分析经设备平衡后的主件网络图对部套制造树中零部件投入产出时间的约束.实际应用表明,提出的定义、映射关系和算法是可行的,可以有效结合网络计划和物料需求计划.     

数控加工车间的集成生产计划与控制模式研究

针对传统的数控加工车间的生产计划与控制模式的弊端,构建了一种基于TOC的MRPⅡ生产计划系统和JIT生产控制系统相结合,同时考虑资源约束和订单插入的集成生产计划和控制模式.该模式能以生产需求、JIT拉动与APS模拟排产相结合的方式进行生产计划排产,同时利用车间能力需求计划、看板系统和PDM技术对生产过程实施实时跟踪控制.此模式对数控加工车间的生产效率提高具有重要意义.     

基于MRP／均衡生产的诸控制模型

在讨论制造资源计划和准时制生产特点的基础上，提出适合于大批量和中小批量并存的制造系统的生产计划与控制模式，能力平衡计划，均衡生产计划的数学模型。     

一种多移动机器人运动规划的混合式方法

基于多移动机器人运动的集中式规划法和分布式规划法，提出将两种方法结合使用进行多移动机器人运动规划的混合式方法。此法宏观上采用集中式规划法进行规划任务总体分配，执行则引用分布式规划法加以实现。通过分析表明了这种方法解决了集中式运动规划法响应速度慢和分布式规划法难以求得规划最优解的不足。     

Integrated assembly and machining planning for electronic products using a genetic algorithm approach

To produce an electronic product, both assembly operations and machining operations are required in the process plan. In most cases, the assembly operations and machining operations need to be combined in a continued order with an integrated sequence. This is different from the traditional process planning approaches in which machining operations and assembly operations are separated as two independent tasks with no interactions. For an electronic product, the two types of operations and the associated costs may affect each other in an interactive way. Therefore, the sequence planning of assembly operations and machining operations must be analyzed with an integrated model. In this research, a graph-based model is presented to represent the assembly and machining operations in an integrated model. The related operation cost functions are developed to evaluate the costs for the integrated assembly and machining sequences. The integrated sequence planning problem is solved using a genetic algorithm approach with an objective of lowest operation costs. As a result, the assembly operations and machining operations can be planned in an integrated sequence suitable for producing electronic products. The result shows that the developed method using the genetic algorithm approach is efficient for solving the integrated sequence planning problem. Example products are demonstrated and discussed.     

Implementation of a “backwards planning” technique in the automation of process planning

It is essential to automate the process-planning function to achieve true integration of CAD and NC machining for computer-integrated manufacturing. Several planning techniques have been used for this purpose and the popular method called the “bottom-up” approach or “backwards planning” has been successfully used in developing an expert process-planning system called EXCAP. This paper describes the implementation of this approach, providing details and examples of the model-updating module which enables the planning to be executed automatically for turned components.     

设施规划在我国的应用与发展

介绍了设施规划在当今世界的发展概况和它的定义；阐述了设施规划的作用，原则以及相关的方法和技术；讨论了本人对设施规划在我国企业中应用的看法，以及它对我国经济发展和技术进步的意义；最后就设施规划的应用前景作了展望。     

KNOT POINT PLANNING FOR CARTESIAN TRAJECTORY GENERATION BASED ON INHERITANCE BISECTION ALGORITHM

The computation algorithm of knot point planning for Cartesian trajectory generation of manipulator is investigated. A novel inheritance bisection algorithm (IBA) based on conventional bisection algorithm (BA) is proposed. IBA has two steps. The first step is the 1st knot point planning under lower set position accuracy; the second step is the 2nd knot point planning that inherits the results of the 1st planning under higher set position accuracy. The simulation results reveal that the number of inverse kinematical calculation (IKC) caused by IBA is decreased compared with BA. IBA is more efficient to plan knot points.     

多产品环境下的一种递阶生产计划系统

为求解多产品环境下带顺序相关调整时间(成本)的递阶生产计划问题,提出了一个两层模型.上层的综合生产计划模型求得各产品类在各时段的生产计划,下层的族分解模型则将上层得到的计划分解到所属的各产品族.为避免当族分解模型中各产品族间的调整时间较大时,上层得到的综合计划不可行,将调整上层计划所带来的额外费用集成到族分解模型的目标函数中,从而可以最优地调整得到综合计划.最后,利用某模具制造企业的数据进行了验证,结果表明,所提出的递阶生产计划模型比整体的方法求解规模小,比传统的递阶生产计划模型的成本低.     

产品网络计划及其算法的研究

研究了产品网络计划及其特点,以实际应用为背景,提出了从工艺设计到产品网络计划的转换算法,通过分解工艺信息和物料信息,计算提前期和关键路径,完成从工艺设计到生产管理的产品网络计划的转换。另外,在产品网络计划的基础上提出了一个工时能力平衡的模型并设计了一个近似求解算法。设计实现的系统弥补了计算机辅助工艺规划无法和生产直接关联、生产计划管理系统又无法自动生成计划的缺陷,为工艺设计和生产计划建立起通信的桥梁,在实际生产中有着广泛的应用前景。     

基于生产线仿真的工艺规划研究

为了满足工艺规划同后续生产环节更为紧密集成的要求,在对生产线进行分析的基础上提出了虚拟生产线集成仿真平台的思想,通过工艺与生产线的并行规划来获得优化的工艺。详细说明了集成仿真平台中的工艺规划结构和工时定额规划的方法,最终通过实例表明了生产线仿真对工艺规划的辅助作用。     

Concurrent process/inspection planning for a customized manufacturing system based on genetic algorithm

Producing products with multiple quality characteristics is always one of the concerns for an advanced manufacturing system. To assure product quality, finite manufacturing resources (i.e., process workstations and inspection stations) could be available and employed. The manufacturing resource allocation problem then occurs, therefore, process planning and inspection planning should be performed. Both of these are traditionally regarded as individual tasks and conducted separately. Actually, these two tasks are related. Greater performance of an advanced manufacturing system can be achieved if process planning and inspection planning can be performed concurrently to manage the limited manufacturing resources. Since the product variety in batch production or job-shop production will be increased for satisfying the changing requirements of various customers, the specified tolerance of each quality characteristic will vary from time to time. Except for finite manufacturing resource constraints, the manufacturing capability, inspection capability, and tolerance specified by customer requirement are also considered for a customized manufacturing system in this research. Then, the unit cost model is constructed to represent the overall performance of an advanced manufacturing system by considering both internal and external costs. Process planning and inspection planning can then be concurrently solved by practically reflecting the customer requirements. Since determining the optimal manufacturing resource allocation plan seems to be impractical as the problem size becomes quite large, in this research, genetic algorithm is successfully applied with the realistic unit cost embedded. The performance of genetic algorithm is measured in comparison with the enumeration method that generates the optimal solution. The result shows that a near-optimal manufacturing resource allocation plan can be determined efficiently for meeting the changing requirement of customers as the problem size becomes quite large.