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.     

Evaluation of safety stock methods in multilevel material requirements planning (MRP) systems

This paper evaluates alternative methods of establishing the safety stock level taking into consideration of historical measures of forecasting accuracy and the needs for master production scheduling and material requirement planning under a rolling time horizon. A computer model is used to simulate the forecasting, master production scheduling and material planning activities in a company that produces to stock and the production activities are managed by multilevel MRP systems. The simulation output is analysed to evaluate the impact of safety stock methods on MRP system performance. The result of the study shows that using safety stock can help to reduce total cost, schedule instability and improve service level in the MRP systems. Guidelines are developed to help managers select methods to determine safety stock in MRP system operations.     

Recursive Behavior of Safety Stock Reduction: The Effect of Lead‐Time Uncertainty

Motivated by a recent paper on the effect of lead‐time variability reduction on safety stocks, we provide evidence of the recursive nature of safety stock changes. When lead times follow a gamma distribution we demonstrate that, for cycle service levels between .60 and .70, the reduction of lead‐time variability will first increase safety stock and then either recursively decrease safety stock or make it remain constant. We also numerically show the existence of the recursive effect. A two‐by‐two matrix is introduced to assist managers in making decisions regarding safety stock policy.     

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.     

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.     

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.     

Product mix in the TFT-LCD industry

As operational costs and equipment depreciation in the TFT-LCD (thin film transistor-liquid crystal display) industry are a high percentage of the total cost, most manufacturers usually fully utilise their production capacity to reduce the average unit cost. However, when the market demand is less than the supply the stock of panels increases; this forces manufacturers to instigate a price war to reduce levels of stock and results in a wide fluctuation in panel prices. Inventory stocks of panels could be decreased by optimising the product mix. This will help manufacturers to reduce the risk of holding stocks, increase profit, and improve competitive advantage. This study uses mixed integer linear programming (MILP) to construct a product mix for the TFT-LCD industry given the conditions of profit, productivity, raw materials supply, and market demand. A case study shows that this model is proven to be effective in generating product mix for the TFT-LCD industry while improving profit. The product mix generated by this model can provide a reference for the sales department for orders and shipping, for the production department for the order quantity, and for master production scheduling for each product.     

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.     

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.     

The Value of Production Schedule Integration in Supply Chains

This study explores the value of integrated production schedules for reducing the negative effects of schedule revisions in supply chains involving buyer and supplier firms. A stochastic cost model is developed to evaluate the total supply chain cost with integrated purchasing and scheduling policies. The model minimizes the costs associated with assembly rate adjustment, safety stock, and schedule changes for all supply chain members. Through experimentation, the paper examines the impact of several environmental factors on the value of schedule integration. This study finds that schedule integration can lead to overall cost savings in a supply chain, but some firms may have to absorb costs in excess of those they would incur with independent scheduling. Environments with high inventory holding costs and long supplier lead times may not find it beneficial to adopt an integrated schedule. Forecast effectiveness plays a critical role in realizing the benefits of schedule integration. The paper concludes with suggestions for future research.     

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.     

Analysis and Approximation of a JIT Production Line*

Production lines are often modeled as queueing networks with finite inventory between each stage. Little is known, however, about the average production rate and inventory levels when the service distribution at each stage is normal. This paper approximates the service distribution using iterative methods rather than simulation. The results show that iterative methods are useful when the problem is small and that approximation of the service distribution, by another distribution with the same mean and variance, is valid for steady-state results such as average production rate or average inventory level.     

POWER APPROXIMATIONS FOR A TWO-ECHELON INVENTORY SYSTEM USING SERVICE LEVELS

We consider a two-echelon inventory system with one warehouse and several stores. The warehouse as well as the stores are controlled by periodic review (s, S) inventory policies. We study the interrelationship between the safety stocks at the warehouse and the stores. Stockouts at the warehouse will result in supply delays to the stores and cause the lead time to be stochastic. The stores may react by increasing their safety stock. However, there is a trade-off between the safety stock at the warehouse and the safety stock at the stores. We use a service level at the warehouse to quantify the effect of warehouse stockouts on the lead time to the stores. The service level at the warehouse is considered a decision variable to find the best compromise between the various safety stocks by minimizing the overall costs. Using power approximations for the (s, S) policies, we provide an iterative procedure for adjusting the lead time distribution to the stores; this can result in substantial savings, but it doesn't guarantee the overall optimality. Numerical studies are provided to test the accuracy of approximations. The effects of the different system parameters on the inventory policy give general guidelines for use of the policies.     

MULTISTAGE SAFETY STOCK PLANNING WITH ITEM DEMANDS CORRELATED ACROSS PRODUCTS AND THROUGH TIME

Determining safety stocks in multistage manufacturing systems with serial or divergent structures, where end-item demands are allowed to be correlated both between products as well as in time, is my focus. I show that these types of correlation have contrary effects on the distribution of safety stocks over the manufacturing stages and that neglecting the correlation of demand can lead to significant deviation from the optimal buffer policy. Using base-stock control and assuming total reliability for internal supplies, I present a procedure for integrated multilevel safety stock optimization that can be applied to arbitrary serial and divergent systems even when demand is jointly cross-product and cross-time correlated. As I demonstrate in an example for autocorrelated demands of a moving average type, there are specific solution properties that drastically reduce the computational effort for safety stock planning. Safety stocks determined in that way can be used as an appropriate protection against demand uncertainties in material requirements planning systems.     

Inventory Control and Scheduling of Multiple Products in a Common Facility*

Consider a set of chemical products to be produced in a single facility. Each product has its own unique reaction time (which is assumed to be independent of its batch size), as well as other cost and demand values. In this paper, we address the problem of determining the optimal number of batches, batch sizes, and an accompanying production schedule for these products in the single facility that will minimize the total cost. Two different algorithms have been developed for this problem, the performances of which are contrasted with classical cyclic production schedules. Finally, some guidelines for the application of these methods to real-life problems are outlined.     

Optimum common cycle for scheduling a single-machine multiproduct system with a budgetary constraint

This paper deals with the single machine multi-product lot size scheduling problem, and has two objectives. The first objective is to minimize the maximum aggregate inventory for the common cycle (CC) scheduling policy. A simple and easy-to-apply rule has been developed which determines the optimal production sequence that achieves this objective. The second objective is to find an optimal common cycle for minimizing the average production and inventory costs per unit time, subject to a given budgetary constraint. A method has been presented that achieves this objective     

A SIMULATION ANALYSIS OF THE JAPANESE JUST-IN-TIME TECHNIQUE (WITH KANBANS) FOR A MULTILINE,MULTISTAGE PRODUCTION SYSTEM

The Japanese “just-in-time with kanban” technique reduces in-process inventory to absolute minimal levels, in concert with the Japanese belief that inventory is an unnecessary evil. Due to the success of Japanese firms that employ this type of system, American firms would like to import this technique and emulate Japanese successes. But this Japanese success may be attributable not only to the just-in-time with kanban technique but also to the production environment in which the technique is employed. This paper simulates the just-in-time with kanban technique for a multiline, multistage production system in order to determine its adaptability to an American production environment that might include such characteristics as variable processing times, variable master production scheduling, and imbalances between production stages. The results have practical implications for those firms considering adoption of the Japanese technique.     

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.     

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     

Equivalent Alternate Solutions for the Tour Scheduling Problem*

Achieving minimum staffing costs, maximum employee satisfaction with their assigned schedules, and acceptable levels of service are important but potentially conflicting objectives when scheduling service employees. Existing employee scheduling models, such as tour scheduling or general employee scheduling, address at most two of these criteria. This paper describes a heuristic to improve tour scheduling solutions provided by other procedures, and generate a set of equivalent cost feasible alternatives. These alternatives allow managers to identify solutions with attractive secondary characteristics, such as overall employee satisfaction with their assigned tours or consistent employee workloads and customer response times. Tests with both full-time and mixed work force problems reveal the method improves most nonoptimal initial heuristic solutions. Many of the alternatives generated had more even distributions of surplus staff than the initial solutions, yielding more consistent customer response times and employee workloads. The likelihood of satisfying employee scheduling preferences may also be increased since each alternative provides a different deployment of employees among the available schedules.