生产过程中缓冲设置的模拟方法

分析了瓶颈资源、缓冲、生产提前期之间的关系，以及目前各种用于确定约束资源的方法．针对工序能力比较接近的情况，提出了一种利用Q—GERT和仿真技术的方法，既能真实体现生产中的实际情况，也能准确确定系统中的瓶颈资源．从而使企业在保证较短的生产提前期的同时，大大节省了人力、物力。     

MRPⅡ系统中生产提前期的柔性化研究

生产提前期的准确性和柔性化是影响ＭＲＰⅡ系统运行的关键问题之一，本文在论述了ＭＲＰⅡ系统的基本特点的基础上，分析了生产提前期的确定原理，提出了一种运用计划评审技术（ＰＥＲＴ）中的三值估计法原理确定生产提前期的方法，并说明了该方法的要点和运用程序。     

批制造业中考虑多工序能力平衡的提前／拖期生产计划方法

在跟踪当今提前／拖期生产计划问题研究现状的基础上，针对考虑多工序能力平衡的提前／拖期生产计划方法的瓶颈问题，提出了两种解决方法－关键工序法和松驰法，为将集ＭＲＰ与ＪＩＴ于一体的Ｐｕｓｈ／Ｐｕｌｌ混合策略应用于实际架起了桥梁。     

精益生产实践中提前期绩效的改进与实证——以3M中国工厂为例

为了在推行精益生产实践中缩短生产提前期,提出了一种按单制造（MTO）模式下的提前期绩效改进模型.针对3M中国工厂HH系列显示屏（LCD HH）产品的业务流程,通过因果矩阵和失效模式与结果分析（FMEA）,找出影响提前期绩效的关键因素,并采用价值流分析、统计检验等方法来进一步论证.研究发现,通过业务过程优化（如业务流程重组）和信息技术整合（如看板管理）,3M中国工厂生产率从原来的平均1 505件/h提高到1 600件/h,产品可获得性水平从89.7%提高到90%以上,明显缩短了生产提前期,从原来的5.88d缩短到3d,最终提高了公司的客户满意度和竞争能力.     

一个小批量多品种的生产计划模型

用线性目标规划方法构造了一个小批量多品种企业产生管理系统的年度生产计划模型，结合工厂实际提出了在物料需求计划中计算提前期的经验公式，最后则用AHP方法确定了作业计划中的零件优先加工系数。     

季节性产品的两级供应链产量-提前期决策模型

以具有明显季节性的空调产品为研究对象,研究单一周期、单一产品类型的由空调制造商和经销商组成的两级供应链系统,分析了空调企业普遍存在的淡季产量决策误差大、旺季产能不足等问题,结合实践提出了季节性产品MTO-MTS集成的生产模式;并且建立了需求不确定条件下该生产模式的成本模型,给出了不同参数条件下提前期的取值规律,以及不同条件下最优提前期对应的最优产量和各项成本及其变化趋势,为季节性产品生产决策中提高交付的响应性提供了依据.     

MRPⅡ系统提前期的估计及柔性化

应用“漏斗模型”分析加工能力对ＭＲＰⅡ系统提前的影响。基于关键路径和瓶颈机床提出一种提前期的估算方法。通过引入ＡＢＣ库存控制法和ＪＴＩ的思想，提高生产提前期的柔性和适应性。     

MTO再制造系统最优生产计划提前期研究——基于最小相对熵的方法

研究了MTO再制造系统关于单一核心部件在分拆和采购提前期均不确定下的生产运作;由于回收部件并非100%可用,使得以最小化再制造成本为目标得到的生产计划提前期呈现双峰分布的形式;本文将最小相对熵(MRE)方法应用于生产计划提前期分布的拟合,仿真算例表明:与传统的正态分布和Pearson近似方法相比,MRE近似的结果更为接近目标服务水平和真实的成本曲线,所得结论对再制造企业安排生产计划、设备投资以及旧产品回收策略等有现实的指导意义.     

考虑系统波动因素的DBR瓶颈缓冲区容量设置

DBR方法中的缓冲区容量设置直接影响产品的生产提前期和系统的有效产出,最终影响产品的市场竞争力。针对静态设置的缓冲区容量不能根据生产系统波动程度进行调整的问题,提出一种动态设置缓冲区容量的方法。首先分析影响缓冲区容量设置的3个因素,采用G/G/1排队模型衡量瓶颈前工序生产自然波动、瓶颈前工序数量和瓶颈工序随机波动对缓冲区容量设置的影响,并考虑避免机器故障和机器维修导致的瓶颈“饥饿”,求解机器故障因素和机器维修因素所需要的最小缓冲区容量。在此基础上,提出一种基于系统仿真的动态调节缓冲区容量的方法。最后通过案例分析,验证了所提方法的有效性和实用性。     

需求和提前期不确定下的两级供应链系统研究

由一个部件提供商和一个装配商组成的两级组装供应链系统,部件提供商提供两种不同的部件给装配商进行装配;分析在单销售周期内,系统上同时存在部件的生产提前期和装配提前期的不确定,以及需求的不确定时,系统的特性.采用博弈论方法,装配商确定装配计划提前期,以及向部件提供商提交的订购量;而部件提供商确定部件生产计划提前期,以及部件批发价格.得出,首先,不确定提前期导致供应链系统订购量减小;其次,在分散控制的组装供应链系统中,系统的总生产、装配计划提前期,要大于集中控制系统中的,并且装配计划提前期与部件生产计划提前期无关;再者,过大的提前期不确定性对组装供应链系统的影响要比需求不确定对组装供应链的影响大.     

Implementation of delayed differentiation in batch process industries: a standardization problem

Postponement consists in holding some activities in a supply chain until customer orders are received, these activities being differentiation manufacturing process or distribution activities. The delayed differentiation consists in maintaining products in an undifferentiated state as long as possible during the manufacturing process. This approach permits firms to be more responsive and other advantages that are often mentioned are risk-pooling and lead-time uncertainty reduction. Industrial applications of postponement mainly concern automotive or computers industries (large assembly systems). This paper studies the implementation of delayed differentiation in batch process industries. First, the addition of an intermediate stock is proposed between the two main stages of a process, which leads to an important reduction of the lead-time, but the inventory cost can be prohibitive. Reducing this stock gives rise to a standardization problem. Second, a standardization of the component types in the intermediate stock is performed to make this stock economically profitable. A 01 linear-programming model of the standardization problem is proposed. This model takes into account costly batch resources: standard components are chosen in order to optimize the use of batch resources. An industrial application of this approach is presented (an aluminium-conversion industry). In this case, a drastic reduction of components in the intermediate stock is performed since the number of component is reduced from about 100 to eight standard components.     

Cycle time reduction by improved MRP-based production planning

The important practical problem of planning the production of large assemblies employing an MRP-based system is considered. The objective is to produce products on-time, with minimal cycle time and low work-in-process costs. The approach is based on the determination of accurate lead-time estimates and on the introduction and use of lead-time offsets in the solution methodology. An effective Lead-time Evaluation and Scheduling Algorithm (LETSA) is employed that can perform detailed backward scheduling of operations belonging to a large assembly on a given facility with an objective of minimizing the cycle time. A scaling procedure is used to account for capacity sharing effects by multiple products in a common facility. These scaled lead-time estimates are then employed by an MRP-based system to release work-orders on the shop-floor. The effectiveness of these lead-times and lead-time offsets are evaluated by simulating production using the MRP generated order release times and verifying on-time completion of the multiple assemblies in the common facility. Numerical experiments are presented to validate the performance of the approach. Optimized batch sizes for minimal work-in-process (WIP) costs can also be obtained using LETSA. Thus, the important objectives of minimizing cycle time for on-time delivery and minimizing schedule costs can be accomplished simultaneously.     

Lead-time reduction in a stochastic inventory system with learning consideration

We develop a continuous review inventory model where lead-time is considered as a controllable variable. Lead-time is decomposed into all its components: set-up time, processing time and non-productive time. These components reflect the set-up cost reduction, lot size lead-time interaction and lead-time crashing, respectively. The learning effect in the production process is also included in the processing time component of the lead-time. The finite investment approach for lead-time and set-up cost reduction and their joint optimization, in addition to the lot size lead-time interaction, introduce a realistic direction in lead-time management and control. A numerical example and a sensitivity analysis are presented using the design of experiments to investigate the effect of the model parameters and, in particular, those related to the different lead-time components on the the expected total cost.     

Real time production improvement through bottleneck control

Variability is a key characteristic for evaluating the performance of a process. Small variability for a bottleneck machine can generate high production variability. Short-term production analysis and bottleneck identification are imperative for enabling optimal response to dynamic changes within the system. In comparison to the rich and abundant literature available on long-term analysis, only a small section of the literature addresses the dynamic bottleneck control policies, which may be used to maximise sustainable benefits. In this paper, a real time bottleneck control method is introduced to efficiently utilise the finite manufacturing resources and to mitigate the short-term production constraints by using two practical approaches: initial buffer adjustment and maintenance task prioritisation. The objective for real time bottleneck control is to obtain a continuous production improvement towards a balanced-line status to increase the throughput efficiently. The benefits of this method are presented by considering an industrial case study of an automotive assembly line. The results obtained from this case study show significant production improvements as compared to traditional approaches.     

Periodic capacity management under a lead-time performance constraint

In this paper, we study a production system that operates under a lead-time performance constraint which guarantees the completion of an order before a pre-determined lead-time with a certain probability. The demand arrival times and the service requirements for the orders are random. To reduce the capacity-related operational costs, the production system under study has the option to use flexible capacity. We focus on periodic capacity policies and model the production system as a queuing system that can change its capacity periodically and choose to operate in one of the two levels: a permanent capacity level and a permanent plus contingent capacity level. Contingent capacity is supplied if needed at the start of a period, and is available during that period, at a cost rate that is decreasing in period length in different functional forms. Next, we propose a search algorithm that finds the capacity levels and the switching point that minimizes the capacity-related costs for a given period length. The behaviour of the capacity-related costs changes drastically under different period lengths and cost structures. In our computational study, we observe that the periodic capacity flexibility can reduce the capacity-related operational costs significantly (up to 35%). However, in order to achieve these savings, the period length must be chosen carefully depending on ambition level and capacity-related costs. We also observe that the percentage savings are higher for more ambitious lead-time performance constraints. Moreover, we observe that the use of contingent capacity makes the total system costs more insensitive to the lead-time performance requirements.     

Improving a practical DBR buffering approach using Workload Control

This paper deals with improving the lead-time performance of a small packaging manufacturer in the Netherlands that had already implemented several facets of Theory of Constraints (TOC) in 1997. Since then, delivery reliability and profits have increased and lead-times reduced substantially. In an attempt to achieve further lead-time improvements in 2001, the firm recently encountered some limitations of its partial TOC implementation. In this paper we focus on the modifications of its order acceptance and buffer management system that were necessary in order to obtain the desired lead-time reduction. We describe how Workload Control principles were introduced to improve the buffering approach and planning procedures the firm had been using since 1997. It shows that Workload Control provides effective tools that can be used in combination with the Drum-Buffer-Rope mechanism in order to balance the flow of work to the production floor.     

Lead-time quotation when customers are sensitive to reputation

Firms consider a variety of factors when making lead-time promises, including current shop status and the size of the incoming order. The profit-maximising model presented in this paper is the first to include reputation effects explicitly in a lead-time optimisation model. Reputation is considered to be the lasting effect on the market of a firm’s delivery performance over time, and so it affects the future as well as the current profits. The model is complicated, and a counter-example demonstrates that qualitative monotonicity results are not obtainable. A computational study explores the relationships between shop status, order size, reputation, market characteristics and the lead-time decision. Regression analysis sheds light on these relationships and suggests three heuristics, which provide near-optimal solutions with relatively short running times.     

Flexibility-enabled lead-time reduction in flexible systems

This paper presents the results of a conceptual study and simulation experimentation aimed at understanding the underlying mechanisms of sequencing flexibility-enabled manufacturing lead-time reduction. In spite of a large body of literature on flexibility, the exact mechanism that enables flexibility to reduce the lead time is not fully understood. As a part of our research efforts on the proactive application of flexibility for the performance enhancement of manufacturing systems, we are motivated to study how flexibility can be employed in a proactive manner to reduce the manufacturing lead time and to develop an understanding of the underlying mechanisms. Towards this end, we have developed simulation models of simple flexible manufacturing systems and studied the effect of sequencing flexibility on the lead-time performance under different conditions of part load and machine load balancing. The studies indicated that sequencing flexibility has a significant effect on the lead-time performance of the manufacturing system, and the effect of flexibility varies under different conditions of load balancing. Further studies indicate the existence of complex interactions between the sequencing flexibility, process concurrency, processor load balancing, and manufacturing lead time. This paper intends to discuss some of the interesting results of these studies with a focus on the inherent mechanisms of sequencing flexibility-enabled lead-time reduction.     

A criterion of production model selection for building material with delivery delay

In the construction industry, delivery times of building materials are often delayed to fit the progress of construction, and therefore parts manufacturers are forced to hold extra parts inventory over the period of the delivery delay. To minimise the inventories, two production models, i.e., push and pull type production models can be widely considered. When production lead-time is short and length of delivery delay is long, a pull type may require smaller inventories to keep a certain service level, and a push type may require smaller inventories under the condition of longer production lead-time and shorter length of delivery delay. To examine performance of average inventory level under different system conditions, factors such as ratio of average length of delivery delay to production lead-time, length of production cycle, and coefficient of variation of demand are chosen to define different system conditions. As the performance measure, the ratio of push type inventory to pull type inventory is used in the comparison of the push and pull types, and a quantitative criterion of production model selection is presented.