基于面向负荷的生产控制的紧急订单插单问题

面向负荷的生产控制及与其相应的交货期设置方法的订货生产系统中,存在紧急订单的插单问题。针对此问题提出了一种重排插单方法。建立了订单重排问题的混合整数规划模型,并采用一种基于动态规划思想的启发式求解方法进行求解。通过仿真实验比较了在含有面向负荷的生产控制和基于面向负荷生产控制的交货期设置方法的生产系统中,重排插单、退单插单和顺延插单三种插单方法的表现。结果表明,重排插单方法优于另外两种插单方法,证明了重排插单方法的有效性。     

基于竞争和能力限制的订单竞价与交货期设置

针对竞争环境下的订单接受决策问题,提出一种订单赢取决策方法.该方法考虑了订单竞价和交货期两个影响因素,建立了订单竞价和交货期的决策过程模型.基于订单竞价构成以及成本估算的准确性,通过平衡优化订单竞价和获取概率,以利润最大化为目标,建立了订单竞价决策算法;为避免订单的延迟损失,使交货期决策更为准确,提出一种基于已有负荷和可能负荷的订单交货期设置方法及算法.通过算例给出了详细的求解过程,说明了该算法的有效性.     

运用聚类算法的订单归并模型研究

针对面向订单的生产管理问题,建立一套订单管理系统,对订单统一管理.在此基础上,深入研究订单归并模型,提出基于交货期和加工工艺的订单归并聚类模型,保证工件的准时交货和加工流程的统一化.实际生产时,对归并订单进行细化分组,相似加工尺寸、同名称和同型号的工件分为一个子订单,减少加工设备的调整次数,提高生产效率.该系统在某重型...     

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.     

MTS/MTO混合型生产排产决策研究

MTS/MTO混合生产系统中订单投放排序是个NP-hard问题,为了解决这个问题,提出了一种基于负荷控制的混合订单投放排序控制模型.该模型包括两个主要模块:综合考虑影响MTS/MTO混合生产系统中订单的紧急因素,给出订单紧急度计算方法,根据紧急度值确定订单的投放优先级;采用修正集成负荷统计法实时控制生产线设备负荷,依据设备负荷上限阈值确定订单池中订单投放时间以及投放条件.最后通过遗传算法完成该模型的调度案例分析,结果表明:该排序模型与现有排序模型相比,有利于缩短订单的加工时间,提高设备利用率.     

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.     

MTO环境下订单跟踪系统研究

客户定制化和代工生产企业,按照客户订单组织生产。为控制订单交货期、生产进度和产品质量,需要对订单进行系统跟踪。本文首先对订单跟踪所需的订单、制造过程、组织模型进行研究。然后在订单跟踪功能和内容研究的基础上,提出了面向离散制造、适合MTO(Make-to-Order,面向订单制造)环境下的订单跟踪系统框架,并对系统实现关键技术进行说明。最后,应用案例验证了模型、系统框架的有效性。     

不同交货期时间窗下的平行机生产问题研究

在工业4.0环境下,满足定制生产需求并能够准时交货的智能工厂成为发展趋势。研究在JIT原则下,考虑订单交货期、到达时间和设备产能资源等约束条件下的平行机生产排序问题,以订单任务提前生产的总时间最小化作为目标,基于历史订单构建虚拟订单进行产品组合,建立交货期约束系统求解模型,使用"最小提前生产时间的启发式算法"进行求解,解决不同交货期约束下平行机生产排序过程中的资源冲突、工期延误、设备浪费等问题,以保证准时交货。最后,使用仿真案例实验验证该方法的可行性,为进一步研究不同交货期时间窗下较大规模的复杂平行机排序问题提供可借鉴的方法。     

面向飞机装配的生产管理技术研究

针对飞机装配作业生产管理复杂的特点,以及难以制定合适的生产计划以及生产调度难等问题,在深入分析飞机装配作业过程的基础上,提出了一种面向订单设计的飞机装配生产管理方法.该方法以飞机装配过程为核心,利用多级网络计划技术制定适应生产现场的柔性生产计划,采用面向生产现场的生产调度方法实现生产调度优化,从而实现了生产现场能快速组织装配资源按时完成生产订单.该方法已在实际生产中得到应用,并取得良好的效果.     

基于交货期约束的集成工艺/计划系统

为解决单件小批订货生产方式下交货期满足问题，研究CAPP／PPS集成并行模式下加工过程决策的调度方法，提出把交货期和资源负荷作为工艺设计过程的约束，基于动态分析并行协同设计模式，在一定交货期和动态的资源负荷约束下，基于约束传播和智能回溯算法的约束推理，对构成零件每个加工表面的加工方案一次调度成功，在此基础上，通过作业计划优化调度仿真，实现工艺设计与作业计划并行协同设计，达到快速准时生产的目的。     

Using Data Mining for Due Date Assignment in a Dynamic Job Shop Environment

Due date assignment is an important task in shop floor control, affecting both timely delivery and customer satisfaction. Due date related performances are impacted by the quality of the due date assignment methods. Among the simple and easy to implement due date assignment methods, the total work content (TWK) method achieves the best performance for tardiness related performance criteria and is most widely used in practice and in study. The performance of the TWK method can be improved if the due date allowance factor k could render a more precise and accurate flowtime estimation of each individual job. In this study, in order to improve the performance of the TWK method, we have presented a model that incorporated a data mining tool – Decision Tree – for mining the knowledge of job scheduling about due date assignment in a dynamic job shop environment, which is represented by IF-THEN rules and is able to adjust an appropriate factor k according to the condition of the shop at the instant of job arrival, thereby reducing the due date prediction errors of the TWK method. Simulation results show that our proposed rule-based TWK due date assignment (RTWK) model is significantly better than its static and dynamic counterparts (i.e., TWK and Dynamic TWK methods). In addition, the RTWK model also extracted comprehensive scheduling knowledge about due date assignment, expressed in the form of IF-THEN rules, allowing production managers to easily understand the principles of due date assignment .     

考虑进度协调的模具订单投放控制策略

针对模具组装的特性,提出模具订单投放控制策略协调模具部件加工进度,使同一模具订单的不同部件在满足订单交货期的条件下同时到达装配车间。首先以满足订单交货期和协调进度为目标,建立了模具订单投放顺序优化模型;然后基于模具车间输出能力,周期性的把订单有序地投放到车间;最后设计遗传算法对建立的优化模型进行求解,并列举企业实例分析说明所提方法的合理性和实用性。     

基于能力验证的模具交货期可行性分析方法

针对模具企业在订单洽谈阶段难以确定交货期可行性这一实际问题,建立了基于能力验证方法的交货期可行性验证模型.首先在新模项目关键路径的关键工序中,构建了资源范畴这一能力验证对象,并给出了能力需求和已有负荷的计算方法,然后建立了关键负荷指数这一资源负荷评价指标.基于上述理论基础,构造了启发式算法,并通过算例说明了算法的实用性.最后,针对算法中涉及的接收概率具有不确定性的问题进行了敏感度分析.     

A hybrid neural network and selective allowance approach for internal due date assignment in a wafer fabrication plant

A hybrid neural network and selective allowance approach is proposed in this study for internal due date assignment in a wafer fabrication plant (wafer fab). In the first part, a look-ahead self-organization map-fuzzy back propagation network (SOM-FBPN) is constructed to estimate the completion time of a job. Subsequently, a selective allowance policy is established to determine the allowance that will be added to the estimated job completion time. Compared with traditional approaches, the look-ahead SOM-FBPN has many features (including incorporating the future release plan, classifying jobs, and incorporating expert opinions), and the selective allowance policy is novel by considering two different production control issues to avoid missing the due date. According to experimental results, the prediction accuracy of the look-ahead SOM-FBPN was significantly better than those of many existing approaches. Besides, the selective allowance policy considerably improved the due date related performance after adding some extra allowance.     

A due date density-based categorising heuristic for parallel machines scheduling

The effective management of shop floor resources is an important factor in achieving the goals of a manufacturing company. The need for effective scheduling is particularly strong in complex manufacturing environments. This paper presents an efficient due date density-based categorising heuristic to minimise the total weighted tardiness (TWT) of a set of tasks with known processing times, due dates, weights and sequence-dependent setup times for parallel machines scheduling. The proposed heuristic is composed of four phases. In the first phase, jobs are listed by the earliest due date (EDD). The second phase computes the due date gaps between listed jobs and categorises the jobs based on the due date density. In the third phase, the sequence of jobs is improved by a tabu search (TS) method. The fourth phase allocates each job to machines. The comprehensive simulation results show that the proposed heuristic performs better than other existing heuristics at a significantly reduced total weighted tardiness.     

Heuristic rules for tardiness problem in flow shop with intermediate due dates

In this paper, the tardiness flow shop models with intermediate due date were considered. The flow shop models consist of a set of jobs each having a number of operations, while each operation is performed in a single machine. All the jobs are considered having the same unidirectional precedence order. In the tardiness flow shop models with intermediate due date, which we call the generalized tardiness flow shop models, there exist a due date associated with the completion of each operation, and we want to find a schedule which minimizes the total tardiness of the jobs. This is a more general version of tardiness flow shop in the sense that, by assigning a large value to each of the intermediate due dates, we can obtain the traditional flow shop models. Considering the generalized tardiness flow shop models as the NP-hard problems, a set heuristic sequencing rules for finding the best permutation schedule for such problems is proposed. We conducted an extensive computational experiment using randomly generated test problems for evaluating the efficiency of the proposed rules in obtaining a near-optimal solution. The efficiency of the rules was evaluated, and those rules with better solutions were designated and reported.     

Multi-machine scheduling with deterioration effects and maintenance activities for minimizing the total earliness and tardiness costs

The due date assignment has become a challenging issue related to the interaction between various participants of the supply chain. In this paper, we consider the total earliness and tardiness penalty scheduling simultaneously with the deterioration effects and maintenance activities on an unrelated parallel machine setting. We aim to determine jointly the optimal maintenance activity positions, the optimal common due date for all the jobs, and the optimal schedule to minimize the sum of the earliness and tardiness costs. If the number of machines is fixed, we introduce a polynomial time algorithm for solving the problem. We also propose an efficient polynomial time algorithm with a lower order time complexity for finding the optimal solution of a special case of the problem.     

Single-machine due date assignment problem with deteriorating jobs and resource-dependent processing times

We study a single-machine earliness–tardiness scheduling problem with due date assignment, in which the processing time of a job is a function of its starting time and its resource allocation. We analyze the problem with two different processing time functions and three different due date assignment methods. The goal is to minimize an integrated objective function, which includes earliness, tardiness, due date assignment, and total resource consumption costs. For each combination of due date assignment method and processing time function, we provide a polynomial-time algorithm to find the optimal job sequence, due date values, and resource allocations.     

A decision support system framework to process customer order enquiries in SMEs

Research carried out here describes order processing especially with constraints of due date at the customer enquiry stage in a highly competitive global market. It highlights problems faced by small- and medium-sized enterprises (SMEs) in a make-to-order environment with particular reference to quality and speed of delivery at this critical stage. While commercial software such as manufacturing resource planning and enterprise resource planning can be used at this enquiry stage for SMEs, they may be unaffordable especially due to high maintenance running costs. This study recognizes this challenge facing SMEs during enquiry management and justifies the need that an effective decision support system (DSS) is crucial even if SMEs have some planning and control systems in place. A flow chart is presented to highlight the influence of negotiation on customer due dates to serve as a basis for forward or backward planning, and a case example illustrates the fundamental construction and applicability of the proposed DSS approach with a resultant profit maximization outcome if the strategy is carefully implemented.