A diagnostic analysis of the impact of forecast errors on production planning via MRP system nervousness

Abstract. The purpose of this paper is to examine the impact of forecast errors on the performance of a multi-product, multilevel production planning system via MRP system nervousness. The accuracy of forecasting methods was at one time a major concern of production scheduling and inventory control. However, with the advent of material requirements planning (MRP) systems, the significance of selecting an accurate forecasting method has diminished. Inaccurate forecast results are taken as a fact of life in production planning. Instead of attempting to develop an accurate forecasting method, efforts have been devoted towards providing an appropriate buffering method ai the master production schedule level or on the shop floor level to counteract fluctuations in demand. MRP is capable of rescheduling planned orders as well as open orders to restore the priority integrity after the disruptive changes of forecast errors occur. Nevertheless, excessive rescheduling may lead to a problem, generally referred to as system nervousness. This study investigates this problem by means of a computer simulation model. The results show that the presence of forecasi     

MRP system performance under lumpy demand environments

Material requirements planning (MRP) systems are deemed to deal with master schedules with lumpy demand patterns better than any other production scheduling system. Past studies have advocated important advantages of using MRP systems. The objective of this paper is to look into the impact of patterns of demand lumpiness on the performance of MRP systems by a simulation study. Results show that there is an important threshold point in terms of degree of lumpiness at which MRP system performance starts to deteriorate in the operating conditions considered. If master production schedules (MPS) can be controlled by manufacturers, MRP users should exercise caution to introduce demand lumpiness in MPS to improve system performance. If not, MRP users should then examine the given lumpiness and choose an appropriate lot-sizing rule that has been shown to take advantage of the effect of demand lumpiness.     

A closed loop automatic scheduling system (CLASS)

Abstract

CLASS is a production scheduling system, that is designed to function in either a stand-alone manner, or in conjunction with an MRP system. MRP systems innately do not have 'closed loop’ capability in the sense of being able to produce master schedules and order releases that are consistent and that respect capacity constraints. True closed loop performance requires detailed scheduling. In addition to interfacing with MRP systems, CLASS is designed to produce schedules that can be used in conventional shops or can be downloaded to automated facilities. The design goals for the system, its internal architecture, and its role in manufacturing control systems are described. The modelling and decision capabilities     

Order Promising and the Master Production Schedule*

Previous research on material requirements planning (MRP) systems has rarely considered the impact of the master production scheduling method used to promise customer orders and to allocate production capacity. Based on a simulation study of an MRP environment, we show that the correct selection of a master production schedule (MPS) method depends on the variance of end-item demand. In addition, we find evidence that the effectiveness of a particular MPS method can be enhanced by holding buffer inventory at the same level in the product structure as in the MPS.     

Integrating MRP and finite capacity planning

Traditional production control systems based on the manufacturing resource planning concept do not sufficiently support the planner in solving capacity problems, ignore capacity constraints and assume that lead times are fixed. This leads to problems on the shop floor, that cannot be resolved in the short term. This paper focuses on solving these capacity problems by improving capacity planning at the material requirements planning MRP level through integration of MRP and finite capacity planning. This results in a planning method for simultaneous capacity and material planning. The planning method is based on a new and more accurate primary process model, giving the planning algorithm more flexibility in solving capacity problems. The algorithm is based on advanced scheduling techniques and uses aggregated information, thus combining speed and accuracy. The algorithm is designed to use the available flexibility: alternative routeings, safety stock, and replanning of production orders and requirements. This paper also discusses such related issues as robustness, memory and the role of the human planner.     

Establishing safety stocks for master production schedules

The basic master production scheduling problem assumes that periodic demands are known with certainty. Uncertainty in the forecasts arc typically accommodated afterwards by adding safety stocks to a schedule. Two popular methods for establishing safety stocks are: (1) the constant cycle service level method; and (2) the constant safety stock method. This paper outlines these methods and then develops a third method which results in optimal safety stocks. The paper includes an experimental investigation aimed at comparing performances of the three safety stock methods. The constant safety stock method is shown to perform within one or two per cent of optimal, while the constant cycle service level method performs worse under most conditions. Shorter lead times, variable order interval lengths, and time-dependent forecast errors all adversely affect the performances of the non-optimal methods. An operations manager could use these results to evaluate the appropriateness of the methods for his master production scheduling environment.     

MATERIAL REQUIREMENTS PLANNING UNDER UNCERTAINTY

This paper presents a framework for characterizing and studying the uncertainty which can affect inventory investment and service level performance in a material requirements planning (MRP) system. It also presents the results of a simulation experiment which compared two techniques (safety stock and safety lead time) for building inventory to protect against uncertainty. The simulation results disclose consistent differences between the techniques in protecting a representative part against timing and quantity uncertainty in both demand and supply for the part. The paper not only provides some initial insights into the behavior of MRP systems under uncertainty, but also establishes some guidelines for choosing between safety stock and safety lead time.     

Freezing the master production schedule in multilevel material requirements planning systems under deterministic demand

This paper extends the studies by Sridharan, Berry, and Udayabhanu from single-level MPS systems to multilevel material requirements planning (MRP) systems, and examines the impact of product structure, lot-sizing rules and cost parameters upon the selection of MPS freezing parameters under deterministic demand. A model is built to simulate the master production scheduling and material requirements planning operations in a make-to-order environment. The results show that all the MPS freezing parameters studied have a significant impact upon total inventory costs and schedule instability in multilevel MRP systems. First, the order-based freezing method is preferable to the period-based method. Secondly, the study finds that increasing the freezing proportion reduces both total inventory costs and schedule instability. This finding contradicts the finding by Sridharan et al. in single-level systems. Thirdly, the study finds that a higher replanning periodicity results in both lower total inventory cost and lower schedule instability. The study also indicates that the product structure and lot-sizing rules do not significantly influence the selection of MPS freezing parameters in a practical sense under most situations. However, the cost parameter seems to significantly influence the selection of replanning periodicity.     

Production and inventory control at ABB Motors and Volvo Wheel Loaders,two examples of MRP in practical use

The paper presents the main routines of production and inventory control at ABB Motors, Västerås and Volvo Wheel Loaders, Eskilstuna. The primary interest is to present how Material Requirements Planning (MRP) is used in these two companies. If the number of end items is large, the company assembles-to-order or makes-to-order then additions to pure MRP seem to be necessary. ABB Motors and Volvo Wheel Loader use: planning bills, a normal bill of materials with 'adding bills of materials', a master production schedule planning system with an available-to-promise function and a home-made 'system' for modules available-to-promise. One important measure for the both companies is the accumulative lead-time. An increase of the Master Production Schedule in a shorter time than the accumulative lead-time is avoided, because it will lead to suggestions of purchase in past time periods and therefore most probably to future material shortages.     

A finite capacity material requirements planning system

In a discrete parts manufacturing environment, material requirement planning (MRP) is carried out without considering the manufacturing resource capacity. As a result, during implementation, adjustments in planned orders may become necessary. This paper presents a finite capacity material requirements planning algorithm (FCMRP) to obtain capacity-based production plans. These plans need no costly adjustments to satisfy the capacity constraints. Performance of the FCMRP system, when studied through a set of test examples, has been found to be superior to the existing MRP system.     

A COMPARISON OF PRODUCTION SCHEDULING POLICIES ON COSTS,SERVICE LEVEL,AND SCHEDULE CHANGES

We consider a single product, single level, stochastic master production scheduling (Mps ) model where decisions are made under rolling planning horizons. Outcomes of interest are cost, service level, and schedule stability. The subject of this research is the Mps control system: the method used in determining the amount of stock planned for production in each time period. Typically, Mps control systems utilize a single buffer stock. Here, two Mps dual-buffer stock systems are developed and tested by simulation. We extend the data envelopment analysis (dea ) methodology to aid in the evaluation of the simulation results, where Dea serves to increase the scope of the experimental design. Results indicate that the dual-buffer control systems outperform existing policies.     

Experimental earliness/tardiness production planning with the due window system

In order to use the philosophy of JIT to improve the production planning method of MRP-II, we propose the experimental software system of the earliness/tardiness produc tion planning problem with due window. By means of the approaches and model reported in this paper, the optimal production planning can be achieved. The recommended model extends the problem of due window from the shop scheduling level into the aggregated planning level of mass manufacturing systems. Simulation results have demonstrated that the experimental software is a useful tool for the production management of repetitive manufacturing enterprises.     

Computational complexity of algorithms for MRP and JIT production planning problems in enterprise resource planning systems

An enterprise resource planning system (ERP) is the information backbone of many manufacturing companies. At the core of ERP is a conventional material requirements planning (MRP) production planning system or a variation of MRP when just-in-time (JIT) principles are used in manufacturing. MRP and JIT both organize production planning into a hierarchy of long-, medium- and short-range problems. In all there are eight different problems. Some are common to MRP and JIT, others are specialized for a particular system. This paper analyses the computational requirements of these problems. This is important for ERP because it plans for large numbers of products (e.g. 50 000 products at 3M Company and 44 000 products at States Industries in Oregon) at large numbers of locations (e.g. 82 locations in 21 countries for Visteon Automotive Systems of Michigan and 19 locations at Boeing). We show that adequate algorithms exist for some problems, but better algorithms are needed for other problems if ERP is to provide useful production plans.     

Master Production Scheduling Under Rolling Planning Horizons with Fixed Order Intervals

Fixed interval scheduling is studied in the context of a rolling horizon framework that is developed by building on previous work in the master scheduling area. The rolling horizon framework includes a stationary scheduling model which uses the “time fencing’concept by partitioning the planning horizon into three sections. The lengths of these sections and the frequency at which the stationary problem is updated and resolved are discussed as parameters of the rolling horizon model. Two different interpretations of the freeze interval parameter are examined, enabling confirmation and clarification of results presented in an earlier study. Details are given for three methods of calculating safety stocks as a function of rolling horizon parameters, including a method which results in optimal safety stock levels. A comparison of the safety stock methods shows that the constant safety stock method can result in inventories that are significantly above optimal under certain conditions, whereas the constant service level method consistently yields nearly optimal results.     

AN EVALUATION OF FORECAST ERROR IN MASTER PRODUCTION SCHEDULING FOR MATERIAL REQUIREMENTS PLANNING SYSTEMS.

Typical forecast-error measures such as mean squared error, mean absolute deviation and bias generally are accepted indicators of forecasting performance. However, the eventual cost impact of forecast errors on system performance and the degree to which cost consequences are explained by typical error measures have not been studied thoroughly. The present paper demonstrates that these typical error measures often are not good predictors of cost consequences in material requirements planning (MRP) settings. MRP systems rely directly on the master production schedule (MPS) to specify gross requirements. These MRP environments receive forecast errors indirectly when the errors create inaccuracies in the MPS. Our study results suggest that within MRP environments the predictive capabilities of forecast-error measures are contingent on the lot-sizing rule and the product components structure When forecast errors and MRP system costs are coanalyzed, bias emerges as having reasonable predictive ability. In further investigations of bias, loss functions are evaluated to explain the MRP cost consequences of forecast errors. Estimating the loss functions of forecast errors through regression analysis demonstrates the superiority of loss functions as measures over typical forecast error measures in the MPS.     

Education: MRP/GT: A FRAMEWORK FOR PRODUCTION PLANNING AND CONTROL OF CELLULAR MANUFACTURING

American industry typically uses material requirements planning (MRP) for manufacturing control. This paper presents production planning and control procedures based on group technology (GT), which is used in British manufacturing. A translation between these ideas and the American approach is made, and it is suggested that a combination of MRP and GT is viable. The problems that arise, especially in the areas of lot-sizing and sequencing/scheduling, and their possible solutions are discussed. Since increased adoption of GT is expected within the next decade, an intensified research effort is warranted in these and other areas so that existing MRP systems can be modified or extended to handle cellular manufacturing control problems. Subject Areas: Material Requirements Planning and Production/Operations Management.     

THE USE OF INDUSTRIAL SOFTWARE TO CREATE EXPERIENTIAL LEARNING ACTIVITIES IN OPERATIONS MANAGEMENT COURSES

Computer-based manufacturing planning and control (MPC) systems are widely used in industry to gain competitive advantage through integration and coordination of managerial activities. In collegiate business schools, important operations management activities are taught and studied, often by sequential examination of discrete topics such as aggregate production planning, master production scheduling, capacity planning, material planning, and production activity control. This paper explores the potential use of industrial MPC software in the classroom to create experiential learning activities that address the dynamic and integrative nature of operations management. Experiences with this pedagogical approach over the past decade are reported.     

The value of rescheduling functionality within standard MRP packages

One of the basic functions of an MRP system is to issue rescheduling messages that urge the planner tospeed up or slow down open orders. It seems in practice that these messages are not used at all by planners. This is mostly due to the inaccuracy of MRP, that more or less ignores safety time, safety stocks and lotsize flexibility in the calculation of reschedule-in messages. Reschedule-out messages are usually ignored because planners do not see the value of the message. Other reasons for not adhering to rescheduling messages are a lack of maintenance of MRP parameters or simply the wrong use of the MRP function. In the future, MRP rescheduling functionality will be used even less than today, due to the changing role of MRP within the planning framework. With the uprise of finite capacity scheduling packages, MRP is being pushed one level upward in the planning hierarchy. This means that rescheduling functionalities for the short term will become completely obsolete in MRP systems.     

Production planning and control for remanufacturing: literature review and analysis

This article reviews the literature on production planning and control (PPC) for remanufacturing. The objectives are threefold: to determine whether the gaps identified by Guide (Guide Jr, V.D.R., 2000. Production planning and control for remanufacturing: industry practice and research needs. Journal of Operations Management, 18, 467–483) on the subject with respect to the main complicating characteristics of remanufacturing have been fulfilled; to classify the literature based on an appropriate structure to obtain a better understanding of the subject identifying sources of future research and to provide a useful source for scholars and practitioners. Seventy-six papers were examined and classified. It was found that none of the studies deals simultaneously with all of the complicating characteristics, and that more practical research is needed. In addition it was found that we lack studies regarding forecasting and aggregate planning considering disassembly of returned products, material matching restrictions or stochastic routings, master production scheduling considering material matching restrictions or stochastic routings, ordering system and capacity planning considering material matching restrictions and inventory control and management considering stochastic routings.     

Reference model for implementing an MRP system in a highly diverse component and seasonal lean production environment

Companies are currently choosing to integrate logics and systems to achieve better solutions. These combinations also include companies striving to join the logic of material requirement planning (MRP) system with the systems of lean production. The purpose of this article was to design an MRP as part of the implementation of an enterprise resource planning (ERP) in a company that produces agricultural implements, which has used the lean production system since 1998. This proposal is based on the innovation theory, theory networks, lean production systems, ERP systems and the hybrid production systems, which use both components and MRP systems, as concepts of lean production systems. The analytical approach of innovation networks enables verification of the links and relationships among the companies and departments of the same corporation. The analysis begins with the MRP implementation project carried out in a Brazilian metallurgical company and follows through the operationalisation of the MRP project, until its production stabilisation. The main point is that the MRP system should help the company's operations with regard to its effective agility to respond in time to demand fluctuations, facilitating the creation process and controlling the branch offices in other countries that use components produced in the matrix, hence ensuring more accurate estimates of stockpiles. Consequently, it presents the enterprise knowledge development organisational modelling methodology in order to represent further models (goals, actors and resources, business rules, business process and concepts) that should be included in this MRP implementation process for the new configuration of the production system.