数据可视化技术在炼钢-连铸生产调度中的应用

根据炼钢-连铸生产调度的特点,应用Dundas数据可视化技术,实现了在炼钢-连铸生产管理中对调度计划以甘特图的形式进行展示、监控和调整的功能。     

炼钢连铸动态调度专家系统设计与仿真

针对炼钢连铸的生产特点,研究了炼钢连铸动态调度专家系统.系统通过混合知识表示形成知识网络,构建树状层次结构实现知识库模块化管理,运用推理机实现动态调度策略实时推理,加强了系统的柔性和知识的重用性.系统能够根据调度方案和生产数据实时监控生产过程,及时识别扰动,并实现重调度.仿真结果表明,系统具有很好的实时性和交互性,能够保持生产的稳定运行.     

炼钢-连铸生产进度控制系统的研究

有效的炼钢-连铸生产进度控制系统对钢铁企业提高生产率具有重要意义。本文针对某大型钢铁公司炼钢连铸生产调度问题,提出了具有该公司工艺特点的排程模型,结合由设备、工件、订单引起的动态事件,开发出进度控制系统。经实际数据测试,证明了算法的有效性和控制系统的实用性。     

基于系统分析的炼钢连铸重调度框架

针对炼钢连铸生产过程受动态扰动因素的影响而使得初始调度不可行的情况,应用系统分析方法,从扰动因素、策略、方法以及性能评价4个层次提出了基于系统分析的炼钢连铸重调度框架,并对框架中的研究内容展开了深入分析和讨论,以期为企业管理者决策时提供依据和参考.     

钢铁联合企业的计划与调度系统

钢铁企业的计划与调度是企业高效组织,有序生产,保证产能、经济效益最大化的最核心的生产管理功能.计划部分需要考虑板型设计、物料计划、生产计划等,在详细的排产阶段需要设计热金属交付、连铸、轧制等时刻表甘特图.     

基于UML的钢铁企业APS订单计划系统建模

在基于APS的钢铁企业生产计划体系中,订单计划将客户订单转化为生产订单,其内容包括对订单在工序上的分解及交货期的初步确定等.本文从某钢铁企业对订单计划管理的实际需求出发,采用UML建模语言对钢铁企业APS中的订单计划系统进行需求分析,构造了系统的用例图和分析类图,并对订单拆分、库存匹配和产能匹配等典型用例进行了动态建模.本文研究的订单计划系统以客户订单为输入,可以实现订单的拆分、库存匹配和产能匹配,确定订单的交货期,进而合理安排中长期订单计划,达到帮助企业编制高效的生产批量计划和生产调度方案的目的.     

两阶段法求解混装模式下的加热炉调度

针对目前加热炉调度模型少有考虑混装模式下加热炉调度优化的不足,建立了连铸-热轧混装-体化模式下的加热炉生产调度优化模型,并提出了基于贪婪算法和模拟退火算法的两阶段求解方法.生产数据测试表明该模型和算法能有效解决加热炉调度问题.     

基于RSView SE的炼钢-连铸过程监控仿真系统

本文在对炼钢-连铸的工艺流程以及仿真参数进行分析的基础上,运用工厂监控软件RSViewSE建立包括数据采集、各类参数控制、报警控制以及设备起停控制等功能的炼钢-连铸过程监控仿真系统.系统已载入生产实际数据运行,效果良好.     

炼钢连铸生产调度问题的两阶段遗传算法

将炼钢连铸生产过程抽象为混合流水车间,建立了0-1型混合整数线性规划调度模型。模型将严格连续浇注作为等式约束,并通过分段惩罚来平衡炉次的驻留时间。在对模型进行Benders分解的基础上,提出了将GA与LP结合的两阶段遗传算法。在算法设计中,提出了一种新的染色体编码来表示炉次设备指派与排序方案,给出了相应的遗传操作方法。算法的第一阶段通过最小化设备析取冲突来寻找高质量的种群,第二阶段通过求解线性规划模型来指导遗传算法的迭代过程。基于生产实际数据的仿真实验表明,该算法能够有效求解炼钢连铸生产调度问题。     

钢轧一体化生产计划的体系结构

制造执行系统是钢铁企业信息化的核心,钢轧一体化生产计划系统则是钢铁企业制造执行系统的关键功能之一,能实现订单、工艺、质量、设备和生产等各种信息的高度集成和处理.本文分析了钢轧一体化生产计划问题的特点.提出了钢轧一体化生产计划的体系结构模型,并分别从层次的观点、过程的观点、功能的观点和集成的观点深入地探讨了钢轧一体化生产计划体系结构模型的核心内容.其中,层次观点对定位和界定钢轧一体化生产计划起着重要的作用:功能结构观点为构筑基于组件技术的钢轧一体化生产计划系统提供了功能结构和技术框架:过程观点明确了钢轧一体化生产计划内部过程的循环结构,体现出钢轧一体化生产计划是联系各个外部系统的主线;集成观点强调协调炉次批量计划、浇次批量计划和轧制批量计划在钢轧一体化生产计划编制中的作用.本文有利于拓展钢轧一体化生产计划问题的建模思路和求解方法,对钢轧一体化管理系统的开发具有一定的指导意义.     

生产型虚拟企业制造合作伙伴选择模型研究

在分析虚拟企业制造合作伙伴选择研究现状及其存在问题的基础上,首先结合生产型企业产品实现过程不同阶段的特点,提出了虚拟企业制造合作伙伴选择过程模型;其次探讨了虚拟企业制造合作伙伴的评价准则,并在采用Delphi法进行循环调查和指标修改的基础上,利用相关度评价法确定出了虚拟企业制造合作伙伴评价指标体系;然后设计了虚拟企业制造合作伙伴三阶段、四步骤评价模型及其制造合作伙伴筛选方案,并结合某筑路机械制造企业实际,进行了其虚拟企业制造合作伙伴筛选实证研究,提出了相关实施方法建议.     

A simulation study of performance of MRP based systems under interaction effects

This paper pertains to a study carried out on a typical Material Requirements Planning (MRP) based system. An integrated MRP based system was developed. This integrated package facilitates studying the effects of variations in Master Production Schedules (MPS), Bill of Materials (BOM) structure, inventory supports, lot sizing, capacity planning, scheduling rules and shop floor conditions. The system behaviour is captured using simulation. The direct and interacting roles of uncertainties, capacity variations, scheduling rules and lot sizing rules on the system performance have been studied in detail. The details of the system, the modules and their capabil-iiies and the analyses of results are presented in this paper.     

制造型企业的产品应变力及其评价

制造型企业的敏捷性归根到底在于其所提供产品的应变力。本文在明确产品应变力的内涵及影响制造型企业产品应变力因素的基础上,提出了制造型企业产品应变力评价的TCRP模型、建立了评价指标体系并给出了评价的方法,以寻求提高产品应变力和企业敏捷性的正确途径。     

一种基于带熵的遗传算法在车间调度中的应用

车间调度问题是现代制造业快速发展的瓶颈因素,因此提高车间调度的效率和有效性就成了生产制造领域大家普遍关注的问题。现行的车间调度问题遗传算法已经不能满足现代制造业快速发展的要求,多因为其静态性或效率差,表现为早熟或收敛停滞,究其根本原因还是GA的最优参数的选取问题,本文引入了信息熵的概念,以动态调整交叉概率和变异概率,从而给出了可以快速获得最优解的自适应遗传算法,并对此改进算法加以实例仿真验证其有效性。     

Supporting Quick Response Through Scheduling of Make-to-Stock Production/Inventory Systems*

Scheduling of traditional job shops in make-to-order systems has seen extensive research over the past three decades. In such systems, performance is often related to various job completion metrics such as average flow time, average lateness, etc. This paper examines a scheduling problem in a make-to-stock environment where individual job completion measures are irrelevant. In this case, customer orders are satisfied through on-hand inventory where customer service is more closely related to the manufacturer's ability to quickly satisfy demand. We consider the role of scheduling in reducing inventories and improving customer service in the context of a manufacturer who assembles several different products on a single assembly line. We develop scheduling rules for such a system and experimentally compare their performance to those typically used in such environments. Our results indicate that rules which consider the inventory position and demand forecast outperform traditional fixed cycle rules.     

MC模式下供应链动态调度的蚁群寻优分析

在对MC模式下供应链调度的基本运作特征描述及界定基础上,分析了调度过程中主导矛盾的缓解思路;通过将该思路引入动态调度的运作过程,分析了MC模式下的供应链动态调度机理.在调度求解过程中,引入蚁群觅食的寻优机理并对其进行特定的算法设计及改进,提出了供应链动态调度的蚂蚁寻优算法.算法特点为在运算过程中不仅能够反映该生产方式独特的运作特征要求,而且能够融入对主导矛盾的缓解思路.通过仿真,验证了算法的可行性.     

Planning problems of state road transport—India

This article focuses on some of the Planning Problems of State Road Transport Undertakings in India. It seeks to examine the environment in which the State Road Transport Undertakings are called upon to operate. It seeks to clarify the nature of the product and services rendered and also identify the constraints under which the State Road Transport Undertakings are called upon to operate. Finally the article seeks to examine certain strategic planning problems involved, such as nationalization of private operations, consolidation and expansion, traffic and route surveys and scheduling aspects. It is concluded that what ultimately matters is what the passenger gets and not what the undertaking plans and hence the article emphasises the importance of Operational Planning to meet the needs of the passenger as the basis of Corporate Planning for State Road Transport Undertakings. The issues examined in this article will be of relevance to State Road Transport Undertakings in other developing countries.     

Flexible reasoning using sensible agent-based systems: A case study in job flow scheduling

Planning and control systems for highly dynamic and uncertain manufacturing environments require adaptive flexibility and decision-making capabilities. Modern distributed manufacturing systems assess the utility of planning and executing solutions for both system goals (e.g. minimize manufacturing production time for all parts or minimize WIP) and local goals (e.g. expedite part A production schedule or maximize machine X utilization). Sensible Agents have the ability to alter their autonomy levels to choose among a set of decision models in order to handle the differences between local and system goals. In this paper, Sensible Agents are applied to a production planning and control problem in the context of job shop scheduling and decision model theory. Sensible Agents provide for trade-off reasoning mechanisms among system and local utilities that are flexible and responsive to an agent's abilities, situational context and position in the organizational structure of the system.     

A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs,financial budget,and resource constraint in multiple manufacturers

We study a coordinated serial-batching scheduling problem that features deteriorating jobs, financial budget, resource constraints, resource-dependent processing times, setup times, and multiple manufacturers simultaneously. A unique feature but also a significant challenge in this problem is the dual constraints on resources, i.e., financial budget and resource quantity. Some key structural properties are first identified for the setting where the jobs and resources are already assigned to each manufacturer, which enables us to develop the optimal resource allocation scheme. Then, a polynomial-time scheduling rule is proposed to search for the optimal solution for each manufacturer in this setting. Then, a hybrid BA-VNS algorithm combining Bat algorithm (BA) and variable neighborhood search (VNS) is proposed to tackle the studied problem, and the optimal scheduling rule is implemented in its encoding procedure. Finally, computational experiments are conducted to test the performance of the proposed algorithm, and the efficiency and improvements are compared with those of BA, VNS, and Particle Swarm Optimization (PSO), with respect to convergence speed as well as computational stability.