MRP Ⅱ(制造资源计划)在制造业的应用

在1979牛,推出COPICS生产管理软件之后,美国许多公司以物料需求为计划和基础,又推出了制造资源计划（MinufacturingResourcesPlanning简称MRPⅡ）的生产管理软件。这是现在最引人注目的一种生产管理系统,它是以计算机为基础,集计划、生产、采购、销售、财务和能力需求为一体的新的管理思想与方法。据统计,目前美国已有几万家企业运用了这个系统;在我国,自80年代初引人MRPⅡ管理以来,众多的企业对应用MRPⅡ进行管理已由过去的消极被动观望发展到现在的积极主动实施,并从中获得可喜的效益。企业管理需要MRPⅡ“八五”以来…     

中小企业ERP生产计划体系分析与设计

本文以我国中小型制造企业为研究对象，分析了我国中小企业ERP生产计划管理体系的特点和应具有的功能，并根据系统功能目标，对主生产计划（Master Production Schedule，MPS）、物料需求计划（MaterialRequioement Planning，MRP）和能另需求计划（Capacity Requirements Planning，CRP）进行了分析，实现了生产计划控制的有机结合，提出了一个针对中小企业的解决方案。     

ERP信息化在轧钢生产中的应用

生产与控制管理模块是ERP的核心,它是以客户需求和市场预测等为主要依据,通过主生产计划(MPS)和物料需求计划(MRP)两个层次的运算,自动生成生产计划、采购计划和委外计划,经过有关部门审核后成为正式的订单(Order),而后,下达给相关部门执行,并控制执行情况。本文主要探讨ERP信息化在轧钢生产中的应用。     

生产计划与控制在洁净行业的应用研究

随着工业化的发展,大气污染已越来越严重,PM2.5的危害越来越受到人们重视,室内空气净化行业作为一门前景广阔的新兴行业,竞争也将不断加剧。企业只有建立起适用的生产计划与控制系统,才能提高自身的管理水平和竞争力。本文以奥祥医药工程有限公司作为研究对象,通过细致、深入地调研以及分析,应用制造资源计划(MRPⅡ)、物料需求计划(MRP)、能力需求计划(CRP)、准时制生产(JIT)等理论进行改善并实现均衡生产,提高企业运作效率的目标。     

企业应用MRPⅡ的环境分析与对策

MRP（MaterialRequirementPlanning）译为物料需求计划，是一种以计算机为基础的生产作业计划的编制和控制的先进方法。２０世纪７０年代起，MRP在美国被推广，成为加工装配型企业编制生产作业计划、控制原材料与在制品的有效手段，实现按最终产品的需求量，由系统自动回答何时、何处、需要多少、何种零部件或其它物料以及企业能力需求等数据的目的，解决了大规模生产过程的物料需求问题。８０年代初，出现了制造资源计划MRPII（ManufacturingResourccsPIanning），它在上述MRP的基础上加进了企业财务管理功能，形成了对企业内部所…     

制造企业MRP实施方案解析

通过对ERP（企业资源计划）系统子模块MRP（物料需求计划）的上线方案的描述,阐述在制造企业如何成功实施及后续维护MRP系统,以期为企业建立提供决策、计划、控制与经营业绩评估的全方位和系统化的管理平台。     

基于风险管理的ERP内部会计实时控制

随着以加强内部控制、提高经济效益为导向的企业管理理念和管理模式的不断创新,管理信息技术也在不断提高,从以库存管理为基础研发的MRP(物料需求计划)系统到以物料和资金管理为基础的MRPⅡ(制造资源计划)系统,再到以人、财、物、信息等企业资源进行整合优化的ERP系统,会计控制系统正呈现由传统的事后静     

《制造业库存控制技术与策略》系列讲座之四库存控制与仓储的关系

物流管理流程中库存控制最关键的一个控制点是库存数据的准确性。 这一点从企业实施ERP的过程就可以得到印证。企业实施ERP要成功，要有两个标志，一个是库存数据准确性要达到95％以上；另一个是MRP是可运行的，也就是说这个企业是用MRP来下达采购与生产计划，而不是手工计划，并且MRP运行结果是可靠的。[第一段]     

企业ERP项目实施探讨

要想了解ERP的发展基础必须先了解MRP（Material Requirements planning，MRP），MRP称为物料需求计划是20世纪60年代发展起来的一种计算物料需求量和需求时间的系统，在企业物料管理工作中应用。但是在企业管理中，生产管理不仅涉及物流，还涉及资金流。这要求把财务子系统与生产子系统结合到一起，建立整体化的管理系统，实现资金流与物流的统一管理。上世纪80年代，人们把制造、财务、     

绩效评价系统与企业资源计划系统

企业资源计划(Enterprise Resources Planning,简称ERP)是90年代初期由美国著名的咨询公司Granter Group Inc．首先提出的一种在物料需求计划(Material Requirement Planning,简称MRP)和制造资源计划(Manufacturing Resources Planmng,简称MRPⅡ)的基础上发展起来的更高层次的管理理念和模式。ERP涵盖了企业管理的大部分功能,如财务和成本管理、供销管理、人力资源管理、生产计划管理、质量管理、项目管理等,将生产、销售、人事、研发、财务五大管理功能整合于一个系统中,实现了不同地理位置     

The interchangeability of safety stocks and safety lead time

Due to the uncertainty in estimating both the demand for end products and the supply of components from lower levels, buffering techniques should be included before the loading of a material requirement planning (MRP) system. Safety stocks and safety lead time are two techniques of providing buffering for loading. There have been many studies made concerning the determination of the amount of safety stocks and safety lead time. Some guidelines for choosing between safety stocks and safety lead time for dealing with uncertainty in both demand and supply also have been established. Although these two different methods have been used successfully, it has not been documented that using these two methods in a given situation will yield essentially the same results; that is, the interchangeability of these two buffering techniques has not been explored quantitatively.Since the net influence of safety stocks and safety lead time and their quantitative interchangeability are of major interest, an analytical model is proposed for this study. The lead-time offset procedure for components loading are represented by a matrix model that is based on a lot-for-lot lot-sizing technique. This lead-time offset matrix model is the product of the precedence matrix and the fixed-duration matrix. The precedence matrix is formed according to the total requirement factor matrix and the duration matrix is formed by each component process time. Thus, the lead-time offset matrix will generate the starting period of each component.When the lead-time offset procedure is modeled, the net influence of buffering quantity can be analyzed. The planned safety stock that is normally used to accommodate unexpected demand, shortage in supply, and defects from the operation at each process can be combined with demand to form the master production schedule. The revised lead time due to the integration of the safety stocks can be calculated through the lead-time offset model. The safety lead time may extend the component process time as well as overall production lead time if the designated safety lead time is longer than the available slack time in a fixed lead-time loading system.When the proposed lead-time offset model is further examined, it is found that planned safety stocks at the higher level can buffer the fluctuations of lower level components quantity as well as the fluctuations of same level components quantity. Safety stocks can also buffer shortages that are caused by the delay of raw material and manufacturing processes. Thus, safety stocks can be used to buffer unexpected delay time up to certain limits. A planned safety lead time at higher level component process can buffer the fluctuations of lower level components process time, as well as the same level component process time. The safety lead time can be used to produce additional products to meet unexpected excessive demand up to certain limits under the following conditions: 1. The excessive demand is known before the actual processing of the components in the lowest level. 2. The raw material at the lowest level is available.Although safety stocks and safety lead time are interchangeable in terms of the ability to buffer variations in quantity, the conditions for safety lead time are seldom met in actual practices. Thus, the slack time in a fixed lead-time loading system cannot be considered as an effective measure to substitute safety stocks. However, all or part of the delay in manufacturing processes or the supply from the lower level components can be buffered by the safety stock and the MPS will still be met. From this study, it is obvious that the slack time can be reduced when safety stocks are planned for an MRP system. The reduction of fixed lead-time duration will be beneficial to the overall planning and scheduling in MRP systems.     

Multiplant MRP

Many manufacturing firms have multiple manufacturing plants, located in geographically diverse parts of the world. This situation is becoming more common, as firms establish new plants in foreign countries to take advantage of low labor cost. In such cases, it is not unusual for the firm to retain production capability of certain key parts in a backup plant, with the necessary equipment and trained workforce in place. High volume production could be obtained relatively quickly from the backup plant in case of an emergency at the main supplying plant. In such multiplant settings, the transportation costs are significant. Throughout this paper, we use the term “multisourced parts” to describe parts produced in more than one location.Material Requirements Planning (MRP) is the component of a total manufacturing control system that is designed to manage inventory and plan orders for parts and material with dependent demand (demand derived from the demand of other items). Most of the literature on MRP systems discusses MRP methodology in a single-plant environment. Most MRP software systems in use today are single-plant systems.Currently, it is common for firms with multiple plants treated as cost centers to use an independent single-plant MRP system for each and handle the transshipment problems manually. Because of lack of coordination of production schedules between supplying and demanding plants, those firms hold more inventory and experience longer lead times than necessary to compensate for uncertainties in schedules and supply policies.The purpose of this article is to enhance single-plant MRP systems for coping with multiplant situations in which: the plants are regarded as cost centers, there exist multisourced parts, and the transportation costs are significant. The multiplant MRP system should recognize that parts are produced in different plants, make offset calculations for in-transit lead times, and consider transportation costs when establishing production requirements and shipping routes for multisourced parts. The objective is, beginning with the corporate-determined master schedule for finished products, to communicate in one planning cycle time-phased planned order release schedules and shipping/delivery schedules to each manufacturing plant producing components for the finished products.We first present a simplified framework for the multiplant MRP system, where a transportation algorithm is incorporated into the MRP logic. Then we refine this simplified framework to handle more complex aspects of a multiplant network. These complexities include the treatment of requirements that are not shipped on time and the regeneration of new MRP schedules. We also observe that the solution to the transportation problem described above is affected by the lot-sizing rules employed. In addition, we discuss several important issues and decisions that confront a firm when implementing a multiplant MRP system.     

MRP原理在后方仓库物资管理中的应用

将MRP原理中可借鉴部分应用于军用物资管理中,进行后方仓库物资管理信息系统的开发,实现物资需求、储备、供应的有序发展及精确化保障。     

Research issues for multi-level lot sizing in MRP systems

What lot size model(s) to use in a Material Requirements Planning (MRP) system is an unresolved and often debated issue. The concept of dependent demand, the complex network defined by the product structure, the dynamics of an operating MRP-based system, and the subsequent use of the planned order release schedule by other company subsystems represent a totally new environment for making and managing lot size decisions.The purpose of this paper is to identify and briefly examine ten research issues related to lot sizing in a dependent demand product structure. These ten issues expand the solution space for lot sizing in an MRP-based system compared to a reorder point based system. Areas for further research are suggested.     

Irregular workloads with MRP systems: Some causes and consequences

Material Requirements Planning (MRP) systems have been widely applied in industry to better manage multiproduct, multistage production environments. Although many applications have been quite successful, much is still left to the planner's intuition as to how to assure that master schedules, component lot sizes, and priorities realistically conform to the capacity limits at individual work centers. Capacity issues may indeed be the soft spot in MRP logic.This paper explores some possible causes of irregular workload patterns when using an MRP system. Better insight on which factors cause temporary bottlenecks could help managers better assess the vulnerability of their plants to this problem. It might also suggest ways of dampening peaks and valleys. The problem setting is a multistage environment; several products are made from various subassemblies and parts. Each shop order is routed through one or more capacitated work centers. An order is delayed either by temporary capacity shortages or the unavailability of components. Of course, the second delay can be caused by capacity problems previously encountered by the shop orders of its components.Seven experimental factors are tested with a large-scale simulator, and five performance measures are analyzed. The factors are the number of levels in the bill of material, the average load on the shop, the average lot size, the choice of priority rule, demand variability, the use of a gateway department, and the degree of equipment specialization. We have one measure of customer service, two for inventory, and two for workload. The workload measures are unconventional, since our interest is when workload variability occurs and how it affects inventory and customer service.The simulator has been developed over the course of eight years, and since this study has been further enhanced to handle many more factors. The simulator was validated recently with real data at two manufacturing plants. It is quite general, in that the bills of material, shop configuration, routings, worker efficiencies, and operating rules can be changed as desired.An initial screening experiment was performed, whereupon the average load and priority rules were not statistically significant at even the .05 level. A full factorial analysis with two replications was then conducted on the five remaining factors. Multivariate analysis of variance (MANOVA) and analysis of variance (ANOVA) statistical tests have been performed.The results confirm that workload variability can have a detrimental impact on customer service and inventory. The following structural changes to the manufacturing system can be beneficial, but tend to be more difficult to achieve. More BOM levels improve customer service, but increase inventory and capacity bottlenecks. Resource flexibility is a powerful tool to reduce workload variability. Capacity slack averaging much over 10% is wasteful, having no benefits for inventory and customer service. In general, revising the routing patterns only, such as creating more dominant paths, will not give big payoffs. The following procedural changes are easier to implement. Master schedules which smooth aggregate resources are an excellent device to reduce workload variability. Even with a smooth MPS, debilitating workload variability can still occur due to the design of the BOM, lot size, and leadtime offset parameters. Selecting a priority rule does not seem to be of overriding importance compared to master scheduling and component lot sizing. These findings must be considered within the context of the range of plant environments encompassed by this study.     

基于MATLAB的物料需求计划优化模型研究

根据企业对物料的需求预测和企业自身的资源约束条件,基于某种目标建立物料需求计划的线性优化模型,利用MATLAB软件求得满足该目标的最优物料需求计划。结合某汽车配件产品的实例分析,获得物料需求计划的可行且最优的方案,避免了传统物料需求计划制定后再通过细能力计划检验物料需求计划是否可行的过程,提高了物料需求计划制定的效率。     

Overlapping operations in material requirements planning

Material requirements planning (MRP) is a planning and information system that has widespread application in discrete-parts manufacturing. The purpose of this article is to introduce ideas that can improve the flow of material through complex manufacturing systems operating under MRP, and that can increase the applicability of MRP within diverse manufacturing environments.MRP models the flow of material by assuming that items flow from work station to work station in the same batches that are used in production. That is, once work starts on a batch of a certain item at a certain work station, the entire batch will be produced before any part of the batch will be transported to the next work station on its routing plan. Clearly, efficiency can be increased if some parallelism can be introduced. The form of parallelism investigated here is overlapping operations.Overlapping operations occurs when the transportation of partial batches to a downstream work station is allowed while work proceeds to complete the batch at the upstream work station. The potential efficiencies to be gained are the following:

• Reduced work-in-process inventory

• Reduced floor space requirements

• Reduced size of transfer vehicles

Additional costs may accrue through additional cost of transportation of partial batches and through additional costs of control.Some MRP software vendors provide the data processing capability for overlapping operations. However, the user is given little or no guidance on overlapping percentages or amounts. It is our intent to provide a simple, robust technique to MRP users who would like to overlap operations and gain some or all of the above efficiencies.An optimal lot-sizing technique is derived by considering a generic two work station segment of a manufacturing system. Under the assumptions of constant demand and identical production rates, a cost function that considers setup costs, inventory holding costs and transportation costs is derived. This cost function is minimized subject to the constraint that the production batch is an integer multiple of the transfer batch. We solve for the optimal production batch, the optimal transfer batch, and the integer number relating them. Solutions are obtained as closed form, easy to-evaluate formulas.By introducing more parallelism, overlapping operations can reduce lead time. However, this will not happen without modification of MRP logic to accommodate such reduced lead time. We derive a formula that shows how a significant lead time compression can easily be obtained and implemented in MRP.We consider an example to illustrate the application of the technique on typical data from the electronics industry. The outcome showed a cost savings of approximately 22.5% over the standard MRP approach.Overlapping operations allows the applicability of MRP to an increasing number of situations that are not modeled faithfully by conventional MRP logic. Three such situations that occur often are the following:

• Limited size of transfer vehicles dictate that several transfers should be planned.

• Lead time requirements prohibit nonoverlapped operations.

Our analysis suggests how to accommodate these difficult practical situations into MRP.Overlapping operations in material requirements planning provides an enhancement that allows wider applicability, shortened lead times, and lower total costs. It may be applied selectively to any two work stations where it is deemed appropriate. Due to the structure of the cost function, it is possible to make the transfer lot-sizing decisions independent of the production lot-sizing decisions. Therefore, significant improvements can be made through overlapping with minimum disruption to the existing MRP system machinery. It is our conviction that overlapping operations is an important concept that can and will impact MRP. We suggest the approach presented here as a systematic way to implement overlapping.     

Manufacturing lead time accuracy

This article addresses the question of accuracy of planned lead times (PLTs) that are used with a material requirements planning system. Lead time error is defined as the difference between an item's PLT and the actual lead time (flow time) of an order to replenish the item. Three related topics are discussed: the relationship between system performance and average lead time error, the transient effect on work-in-process (WIP) inventory of increasing PLTs, and the relative accuracy of three methods of determining PLTs. A distinction is made between available and WIP inventory. The former includes any purchased item, fabricated part, assembly, or finished good that is in storage and available for use or delivery. WIP denotes materials associated with open orders on the shop floor.It was concluded that average lead time error has a considerable affect on system performance. PLTs that are on average too long or too short increase available inventory; and the further the average error is from zero, the more pronounced the increase. Contrary to conventional wisdom, increasing PLTs will increase the service level (decrease backorders), unless PLTs are already severely inflated and MPS uncertainty (forecast error) is small. If PLTs are inflated, decreasing them will decrease the number of setups per unit time in the case of considerable demand uncertainty. Contrary to conventional wisdom, increasing PLTs causes only a transient rise WIP inventory.The fact that the average lead time error has a significant effect on the three areas of system effectiveness mentioned above does not imply that a given order's lead time should be managed in a way that forces its actual lead time to match the PLT. Stated another way, the material planner may use the latest information to manage a given order's lead time; however, if the average discrepancy between the actual and planned lead times is large, system performance can be improved by changing the PLTs to approximate the average flow times.Three methods that have been proposed for determining PLTs are compared. They are historical averages of the actual flow times, calculated lead times based on standard times and historical averages of the queuing time at the appropriate work centers, and the QUOAT lead time proposed by Hoyt. The third was found to perform poorly unless the work content of all operations is identical. With one exception, no differences were found between the first two methods. The simpler historical average method was superior to the calculated lead time in the case where the work content of each operation varies and when considerable demand uncertainty exists.The results are based on simulation experiments employing a generalized MRP/Job-Shop stochastic simulation model. The program launches orders based on standard MRP logic, reschedules open orders by moving the due date in or out to coincide with revised need dates, moves manufacturing orders through a job shop, schedules the delivery of purchase orders, and updates inventory levels. The product structure tree contained eight distinct items, with four levels and one end item. There is no reason to believe that the conclusions would be any different had a larger system been studied.     

Resolving uncertainty in manufacturing systems

This paper examines the effectiveness of three commonly practiced methods used to resolve uncertainty in multi-stage manufacturing systems: safety stock under regenerative material requirements planning (MRP) updates, safety capacity under regenerative MRP updates, and net change MRP updates, i.e., continuous rather than regenerative (periodic) updates. The use of safety stock reflects a decision to permanently store materials and labor capacity in the form of inventory. When unexpected shortages arise between regenerative MRP updates, safety stock may be depleted but it will be replenished in subsequent periods. The second method, safety capacity, overstates the MRP capacity requirements at the individual work centers by a prescribed amount of direct labor. Safety capacity either will be allocated to unanticipated requirements which arise between MRP regenerations or will be spent as idle time. The third method, net change, offers a means of dealing with uncertainty by rescheduling instead of buffering, provided there is sufficient lead time to execute the changes in the material and capacity plans.Much of the inventory management research has addressed the use of safety stock as a buffer against uncertainty for a single product and manufacturing stage. However, there has been no work which evaluates the performance of safety stock relative to other resolution methods such as safety capacity or more frequent planning revisions. In this paper, a simulation model of a multi-stage (fabrication and assembly) process is used to characterize the behavior of the three resolution methods when errors are present in the demand and time standard estimates. Four end products are completed at an assembly center and altogether, the end products require the fabrication of twelve component parts in a job shop which contains eight work centers. In addition to the examination of the three methods under different sources and levels of uncertainty, different levels of bill of material commonality, MRP planned lead times, MRP lot sizes, equipment set-up times and priority dispatching rules are considered in the experimental design.The simulation results indicate that the choice among methods depends upon the source of uncertainty, and costs related to regular time employment, employment changes, equipment set ups and materials investment. For example, the choice between safety stock and safety capacity represents a compromise between materials investment and regular time employment costs. The net change method is not designed to deal effectively with time standard errors, although its use may be preferred over the two buffering alternatives when errors are present in the demand forecasts and when the costs of employment changes and equipment set ups are low. The simulation results also indicate that regardless of the method used, efforts to improve forecasts of demands or processing times may be justified by corresponding improvements in manufacturing performance.     

互联网环境下企业生态系统与CRM、SCM的外部整合研究

本文从分析企业系统的生态环境着手,论述了在互联网环境下企业外部与CRM、SCM整合的必要性