Freezing the Master Production Schedule Under Demand Uncertainty

Managing the trade-off between achieving a stable master production schedule (MPS) and being responsive to changes in customer requirements is a difficult problem in many firms where providing a high level of customer service is viewed as an important competitive factor. One alternative for managing this trade-off is to freeze an agreed portion of the MPS. This paper investigates the impact of adjustments in the design parameters of MPS freezing methods on two performance measures (MPS lot-sizing cost and stability) under stochastic demand conditions in a rolling planning horizon environment given a service level target. Simulation experiments are reported which indicate that many of the conclusions regarding the design of MPS freezing methods obtained under deterministic demand conditions hold under stochastic demand.     

LOT‐SIZING RULE AND FREEZING THE MASTER PRODUCTION SCHEDULE UNDER CAPACITY CONSTRAINT AND DETERMINISTIC DEMAND

This paper investigates the performance impact of lot‐sizing rule (LSR) selection and freezing of the master production schedule (MPS) in multi‐item single‐level systems with a single resource constraint under deterministic demand. The results of the study show that the selection of LSRS and the parameters for freezing the MPS have a significant impact on total cost, schedule instability, and the service level of the system. However, the selection of LSRS does not significantly influence the selection of the MPS freezing parameters. The basic conclusions concerning the performance of the freezing parameters under a capacity constraint agreed with previous research findings without consideration of capacity constraints.     

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.     

Effect of forecast errors on rolling horizon master production schedule cost performance for various replanning intervals

Master production schedules are usually updated by the use of a rolling schedule. Previous studies on rolling schedules seem to form the consensus that frequent replanning of a master production schedule (MPS) can increase costs and schedule instability. Building on previous research on rolling schedules, this study addresses the impact of overestimation or underestimation of demand on the rolling horizon MPS cost performance for various replanning frequencies. The MPS model developed in this paper is based on actual data collected from a paint company. Results indicate that under both the forecast errors conditions investigated in this study, a two-replanning interval provided the best MPS cost performance for this company environment. However, results from the sensitivity analysis performed on the MPS model indicate that when the setup and inventory carrying costs are high, a 1-month replanning frequency (frequent replanning) seems more appropriate for both of the above forecast error scenarios.     

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.     

A Model for Master Production Scheduling in Uncertain Environments

In uncertain environments, the master production schedule (MPS) is usually developed using a rolling schedule. When utilizing a rolling schedule, the MPS is replanned periodically and a portion of the MPS is frozen in each planning cycle. The cost performance of a rolling schedule depends on three decisions: the choice of the replanning interval (R), which determines how often the MPS should be replanned; the choice of the frozen interval (F), which determines how many periods the MPS should be frozen in each planning cycle; and the choice of the forecast window (T), which is the time interval over which the MPS is determined using newly updated forecast data. This paper uses an analytical approach to study the master production scheduling process in uncertain environments without capacity constraints, where the MPS is developed using a rolling schedule. It focuses on the choices of F, R, and T for the MPS. A conceptual framework that includes all important MPS time intervals is described. The effects of F, R, and T on system costs, which include the forecast error, MPS change, setup, and inventory holding costs, are also explored. Finally, a mathematical model for the MPS is presented. This model approximates the average system cost as a function of F, R, T, and several environmental factors. It can be used to estimate the associated system costs for any combination of F, R, and T.     

A Comparative Analysis of Master Production Scheduling Techniques for Assemble-To-Order Products

This paper studies the master production scheduling (MPS) activity of manufacturing firms that produce assemble-to-order (ATO) products. It describes four techniques for master scheduling ATO products: end-product bills, modular bills, super bills, and percentage bills. These procedures are compared in terms of the percentage of customer orders delivered late, the mean tardiness of customer order deliveries, and the total cost of inventory using simulation analysis. The results indicate that the performance of an MPS technique is affected by the level of uncertainty of the end products' demands and the degree of component commonality in the product structure. In particular, modular bills produce the highest customer service level and super bills produce the lowest total inventory cost under most operating conditions. The conclusions also suggest that the choice of a particular MPS technique is often a compromise between the benefits of improved MPS performance and the costs of implementing and executing the MPS system.     

MEASURING MASTER PRODUCTION SCHEDULE STABILITY UNDER ROLLING PLANNING HORIZONS

Maintaining a stable master production schedule (MPS) is difficult for many firms, especially when material requirements planning is used to manage production operations. This paper is concerned with the problem of measuring MPS stability, and the impact on stability of three important decision variables in managing the MPS within a rolling-horizon framework in a make-to-stock environment: the method used to freeze the MPS, the proportion of the MPS frozen, and the length of the planning horizon for the MPS. Simulation experiments conducted to determine the impact of these decision variables, as well as other important product demand and cost characteristics, on MPS stability are reported. The results indicate MPS stability can be influenced by managerial action directed toward management of the MPS as well as changes in important product cost and requirements characteristics.     

Master Scheduling in Assemble-To-Order Environments: A Capacitated Multiobjective Lot-Sizing Model

Basic characteristics of an assemble-to-order environment make effective master scheduling extremely difficult. Limited resource capacities and dynamic customer end-item demand contribute to the complexity of the master production scheduling problem. To gain flexibility and responsiveness within this system, the master production schedule (MPS) focuses at the component level. This research proposes a master scheduling technique for manufactured components which combines a multiobjective capacitated multi-item/multi-stage lot-sizing model with an interactive multiple objective optimization solution procedure. To evaluate the model's performance as a realistic and practical master scheduling tool, this study focuses on the National Cash Register (NCR) electronics manufacturing facility in Columbia, South Carolina.     

Replanning the Master Production Schedule for a Capacity-Constrained Job Shop

This research examines the use of both frozen and replanning intervals for planning the master production schedule (MPS) for a capacity-constrained job shop. The results show that forecast error, demand lumpiness, setup time, planned lead time, and order size have a greater impact on the mean total backlog, total inventory, and number of setups than the frozen and replanning intervals. The study also shows that a repetitive lot dispatching rule reduces the importance of lot sizing, and a combination of repetitive lot dispatching rule and single-period order size consistently produces the lowest mean total backlog and total inventory. The results also indicate that rescheduling the open orders every period produces a lower mean total backlog and total inventory when the forecast errors are large relative to the order sizes. This result suggests that the due date of an open order should be updated only when a significant portion of the order is actually needed on the new due date.     

Rolling horizon master production schedule performance: A policy analysis

In this paper, a simulation experiment has been developed to examine the combined influence of the design, inventory and environmental factors on the cost performance of a rolling horizon master production schedule. Specifically, a 2 5 factorial design was used to examine the effects associated with three rolling schedule design policies, one inventory policy and one environmental condition of forecast error on MPS cost performance. The study was based on actual data from a paint company. Results suggest that the choice of appropriate lot-size and inventory policies have a significant influence on MPS costs and that there are indeed important interactions between these policies and other design factors of a rolling schedule.     

GREENING THE SERVICE PROFIT CHAIN: THE IMPACT OF ENVIRONMENTAL MANAGEMENT PRACTICES

This paper explores the relationship between environmental practices and performance in services and the impact of such practices on the external portion of the service profit chain. Using structural equation modeling, it tests the hypotheses developed with data from the European hospitality industry. The findings suggest that environmental practices are positively related to performance through the mediating effect of enhanced customer satisfaction and loyalty. The paper's contributions include: the conceptual development of the relationship between environmental practices and performance in services, the incorporation of environmental practices within the service profit chain, and the testing of their impact on customer satisfaction.     

Planned Lead Times in Multistage Systems

This study investigates the impact of planned lead times on performance in multistage manufacturing where material requirements planning is used in a make-to-stock environment. We simulate a variety of different operating environments and find: (1) planned lead times are important to customer service levels under all operating environments examined, but have a smaller impact on inventory investment; (2) tight due dates introduced by short planned lead times hurt customer service without saving much inventory; (3) small increases to tight planned lead times improve customer service substantially with small inventory increases; (4) co-component inventories change with planned lead times, and disparity between such inventories is a sign of poor timing coordination; (5) the fixed order quantity rule performs better than the periodic order quantity rule; and (6) tall product structure and large lot sizes require particular attention to planned lead times. The findings also extend the current understanding of planned lead times by including uncertainties such as forecast error, yield loss, and equipment reliability. The study concludes with a way to diagnose and improve poorly set planned lead times.     

The Production of Several Items in a Single Facility with Linearly Changing Demand Rates

In this paper we extend the ELSP model to allow for linearly changing demand rates over a fixed planning horizon. This extension of the ELSP research provides a model that can be used in coordinating the production and marketing planning activities in a firm. The model allows the user to evaluate the impact of changes in product demand on production costs and customer service. We solve the model using a standard nonlinear programming package (MINOS) and show through examples based on actual production data how the model can be used to support coordinated production and marketing planning.     

顾客服务己化量表开发与验证

在相关文献回顾的基础上,进一步凝练顾客服务己化的概念内涵,并综合运用焦点小组访谈、开放式问卷调查、扎根理论的编码技术等方法,编制了顾客服务己化的初始测量题项。经过预调研和正式调研,结合信度分析及因子分析等统计方法,形成了包含8个问项的顾客服务己化概念测量量表。以顾客契合和顾客情绪作为校标,基于契合原理构建了“顾客服务己化-顾客情绪-顾客契合”概念模型,进一步验证所开发量表的效用,探讨顾客服务己化对顾客契合的效应机制。研究表明,顾客服务己化正向影响顾客契合,顾客情绪在其中起中介作用。     

A technique for uncertainty reduction based on order commonality

The use of commonality is widely diffused as a criterion to reduce uncertainty in demand forecasts for the master production schedule (MPS). Nevertheless, studies have mostly focused on exploiting component commonality in make to stock and assemble to order manufacturing. This paper refers to planning environments with two specific characteristics. First, the degree of certainty of the demand is extremely low, due to product complexity, with poor modularization and standardization, and to the presence of few customers of large dimensions. Second, the delivery lead time is less than the total lead time. In this situation, demand for MPS planning units is extremely uncertain and sporadic. It is therefore necessary to formulate in advance forecasts of customer orders with a redundant configuration. In this paper a technique for the reduction of demand uncertainty is introduced, based on the exploitation of order commonalities. In particular, relations between order commonality and uncertainty reduction in a planning environment with such complex features are illustrated. Then, guidelines for the implementation of the technique in order to reduce over-planning in the master production schedule are provided. Finally, the performances of the technique are empirically analysed by means of both a simulation model and experimental application in a telecommunication systems manufacturer     

Measuring and analysing supply chain schedule stability: A case study in the automotive industry

Final assembly plants send material schedules to first-tier suppliers who in turn send schedules to second-tier suppliers and so on through the multiple tiers of the supply chain. A key cost driver for the supply chain is a schedule characteristic termed stability. The Total Quality Management approach is applied to improve schedule stability in the supply chain of a large vertically integrated automotive manufacturer. A measurement described, actual stability results are provided, the causes of instability are listed, and some corrective actions are specified. Results indicate that schedule stability can be improved without damaging the performance of other measures such as inventory and customer responsiveness. and analysis process is     

The Integration of Cost and Capacity Considerations in Material Requirements Planning Systems

Within the sequential framework of material requirements planning (MRP), a master production schedule (MPS) of end-item production is prepared and a bill-of-material processor is used to convert the MPS into a plan for needed subassemblies, parts, and materials. This study examines the impact of different procedures for considering inventory-related costs and capacity limitations in the two phases of planning: master production scheduling and bill-of-material (BOM) processing. A total of nine procedures are considered for integrating the two phases of planning. The results indicate that the integrated procedures have a significant effect on the trade-offs among inventory-related costs, work load variations, over/under time costs, and excess work loads. Further, the results suggest that the method used to develop the MPS has the primary influence on these trade-offs, but the method used by the BOM processor can sometimes have a moderating effect.     

On the fair optimization of cost and customer service level in a supply chain under disruption risks

This paper presents a new decision-making problem of a fair optimization with respect to the two equally important conflicting objective functions: cost and customer service level, in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to select suppliers of parts required to complete the orders, allocate the demand for parts among the selected suppliers, and schedule the orders over the planning horizon, to equitably optimize expected cost and expected customer service level. The supplies of parts are subject to independent random local and regional disruptions. The fair decision-making aims at achieving the normalized expected cost and customer service level values as much close to each other as possible. The obtained combinatorial stochastic optimization problem is formulated as a stochastic mixed integer program with the ordered weighted averaging aggregation of the two conflicting objective functions. Numerical examples and computational results, in particular comparison with the weighted-sum aggregation of the two objective functions are presented and some managerial insights are reported. The findings indicate that for the minimum cost objective the cheapest supplier is usually selected, and for the maximum service level objective a subset of most reliable and most expensive suppliers is usually chosen, whereas the equitably efficient supply portfolio usually combines the most reliable and the cheapest suppliers. While the minimum cost objective function leads to the largest expected unfulfilled demand and the expected production schedule for the maximum service level follows the customer demand with the smallest expected unfulfilled demand, the equitably efficient solution ensures a reasonable value of expected unfulfilled demand.     

基于交互模型的客户服务质量与关系质量的实证研究

目前,关系质量及其影响因素得到越来越多的关注,但客户服务对关系质量的影响机制尚未明确.本文从消费者与服务提供商交互的角度来探讨客户服务质量对关系质量的影响关系,构建了客户服务过程中两类交互质量与关系质量维度的影响模型,并分析了关系质量内部维度的作用机理.通过对295名零售企业顾客的问卷调查以及实证分析,本文得出了以下的结论:(1)顾客与环境的交互质量对关系质量中顾客满意、顾客信任维度存在直接正向影响,而顾客与服务人员的交互只对顾客满意有直接的正向影响;(2)顾客满意对于顾客信任和顾客承诺均存在直接的正向影响.