David F. Pyke

A Two-Location Inventory Model with Transshipment and Local Decision Making

In situations where a seller has surplus stock and another seller is stocked out, it may be desirable to transfer surplus stock from the former to the latter. We examine how the possibility of such transshipments between two independent locations affects the optimal inventory orders at each location. If each location aims to maximize its own profits--we call this local decision making--their inventory choices will not, in general, maximize joint profits. We find transshipment prices which induce the locations to choose inventory levels consistent with joint-profit maximization.

Periodic review, push inventory policies for remanufacturing

Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. This research is focused on product recovery, and in particular on production control and inventory management in the remanufacturing context. We study a remanufacturing facility that receives a stream of returned products according to a Poisson process. Demand is uncertain and also follows a Poisson process. The decision problems for the remanufacturing facility are when to release returned products to the remanufacturing line and how many new products to manufacture. We assume that remanufactured products are as good as new. In this paper, we employ a “push” policy that combines these two decisions. It is well known that the optimal policy parameters are difficult to find analytically; therefore, we develop several heuristics based on traditional inventory models. We also investigate the performance of the system as a function of return rates, backorder costs and manufacturing and remanufacturing lead times; and we develop approximate lower and upper bounds on the optimal solution. We illustrate and explain some counter-intuitive results and we test the performance of the heuristics on a set of sample problems. We find that the average error of the heuristics is quite low.

Performance characteristics of stochastic integrated production-distribution systems

Abstract A conflict often arises between production and marketing or distribution in many firms. Production management would like batch sizes to be large and production smoothed so that additional set-up costs and work force change costs are minimized. Distribution management, on the other hand, would like batch sizes to be small, with frequent changeovers, so that production responds quickly to the changing picture of market demand. It is our purpose in this paper to analyze the management of materials in an integrated supply chain operation. We present a model of a simple integrated production-distribution system and examine its performance characteristics. We present an algorithm for obtaining near-optimal solutions. We limit our examination to a basic single-product, three-location network which consists of a single-station model of a factory, a finished goods stockpile, and a single retailer. This basic network serves to illustrate the key tradeoffs of interest.

Multiproduct integrated production--distribution systems

Abstract In many firms the goals of the production staff are in conflict with those of the marketing staff. Often the resolution of the conflicting goals is to require a stockpile of finished goods to hold large amounts of inventory. The two functional areas thus are buffered. It is our opinion that an integrated view of the entire production-distribution system may generate significant savings by trading off the costs associated with the whole, rather than minimizing production and distribution costs separately. In this paper we develop a model of an integrated production-distribution system comprised of a single station model of a factory, a stockpile of finished goods, and a single retailer. The concepts and solution methodology, however, show promise for more complex networks. Multiple products with stochastic, independent demand are produced at the factory, stored at FG, and distributed to the retailer where demand is met or backlogged. In addition, FG may order an expedite batch of a particular product if its stock level decreases to a specified expedite reorder point. Expedite batches have nonpreemptive priority over normal replenishment batches. We approximate the distributions of key random variables to compute costs and service levels for all products across the supply chain. We find that our approximations are often quite accurate. Our limited tests of the performance of the near-optimization algorithm indicate that it provides solutions very close to the optimal. We also provide results that yield insight into the behavior of this integrated system.

Sales and operations planning : an exploratory study and framework

Purpose – The paper seeks to develop a framework for sales and operations planning (S&OP) that is based on previous literature and company interviews. It is designed to help managers understand how effective their S&OP processes are and how to progress to advanced stages.Design/methodology/approach – The S&OP literature, is reviewed and the results of a number of company interviews are presented. These lead to a new framework, with descriptions of each stage, and to implementation insights for managers.Findings – After highlighting key dimensions for establishing a firms S&OP maturity on a five‐stage framework and, with the use of this framework, exploring in a preliminary way the relationship between firm size or process type (job shop, batch flow, continuous flow, etc.) and its degree of S&OP plan integration, little apparent relationship was found. However, the data suggest that business processes are enablers of S&OP plan integration, but that information technology is not clearly so.Research limitat...

Manufacturing and supply chain management in China:: A survey of state-, collective-, and privately-owned enterprises

Because of the booming economy, interest in China has soared in recent years. The government has decided to privatize many State-owned enterprises (SOEs), so foreigners can much more easily invest in existing firms than ever before. Is it wise to consider investing in these SOEs? Certainly, many have major problems. How sophisticated are Chinese manufacturing firms? Do they understand modern principles of manufacturing strategy and supply chain management? What is the level of installed technology, from traditional production planning systems, like MRP, to robotics? This paper attempts to answer these questions based on a survey of 100 firms in the Shanghai area. We surveyed State-owned enterprises, collective-owned enterprises and privately held firms, and we discovered some fascinating insights about their differences and their similarities. We discovered that the differences among the ownership types are generally insignificant, suggesting that our results are quite general. We find that these firms are far more advanced using explicit manufacturing strategies than we had expected. However, they are not as advanced in supply chain management as many Western firms. They report significant communication with customers and suppliers -- more with customers than suppliers -- but the nature of the communication is often limited to one dimension, particularly on the downstream side. Firms that communicate with customers tend to do so with suppliers as well.

Push and pull in manufacturing and distribution systems

Abstract The terms “push” and “pull” have been used to describe a wide variety of manufacturing and distribution environments. To some, the distinction refers to a specific attribute which can be identified by observing the mechanisms for controlling material flow on the factory floor. To others push and pull can be defined in terms of a specific policy for the management of inventories and production schedules. Finally there are skeptics who maintain that the push/pull dichotomy is a fiction created by academics or unscrupulous consultants to promote their latest theories or systems. In this paper, we review the various definitions of push and pull in operations literature. It is clear from this review that the attributes which distinguish pull systems from push systems are not well understood. The purpose of this paper is twofold. First, we clarify the meaning of push and pull in manufacturing and distribution systems. This clarification gives rise to a framework for push and pull that can serve as a classification scheme for material control systems. While we do not claim that our framework sufficiently classifies all material control systems, we demonstrate its application to a number of common systems. Thus, this framework can be used to analyze and compare management procedures for different classes of material control policies (such as MRP, kanban, base stock). This analysis is particularly useful to designers of material control systems, as well as those doing empirical research, who need to consider in depth various aspects of material control. Second, we intend to stimulate research efforts by the use of our framework. We demonstrate one such use of the framework by introducing a model of a particular integrated production-distribution system. Our model represents a simple, three-location, production-distribution system with multiple products. We develop a system that is predominantly pull, and several systems with varying degrees of push. In the particular example we discuss, our pull system provides lower costs and higher service levels than the push systems. In developing our framework, we analyze material flow decisions in terms of four related decisions that can be used to distinguish push systems from pull systems: 1) batch size, 2) timing of a production or shipment request, 3) setting dispatch or allocation rules, and 4) the presence of interference mechanisms for expediting or handling of emergency orders. The first two decisions are primarily concerned with individual products or parts. The second two decisions introduce the added complexity of multiple products, locations and customers. For each decision, we examine the authority for the decision and the information content used in making the decision. We shall see that it is not possible or useful to label a manufacturing system as being entirely push or entirely pull. We argue that push and pull are characteristics of the underlying decision-making process; and hence manufacturing control systems, which embody a collection of decisions, will contain elements of push or pull to varying degrees. Nevertheless, certain systems, containing such diverse elements often give the impression that they are predominantly one or the other. Our extended definitions provide a more complete picture that can be useful to researchers engaged in empirical work, as well as to managers concerned with system design. The paper is organized as follows: following an introduction and a review of various definitions of push and pull, we describe integrated production-distribution systems. In the next section we present our framework for defining push and pull systems. Throughout this section we refer to commonly used planning and control systems, such as MRP, kanban, DRP, fair shares, and OPT. We then introduce a model that can be used to compare different material control systems. Finally, we present a summary and conclusions.

Allocation of buffers to serial production lines with bottlenecks

The optimal placement of a predetermined amount of buffer capacity in balanced serial production lines is a well-understood problem: in lines with moderate variability, the optimal allocation involves equal numbers of buffers at each site; in lines with severe variability, the equal allocation is modified slightly to place more buffers toward the center of the line. Buffering unbalanced lines is a much less well-understood problem. We study the problem of buffering serial lines with moderate variability and a single bottleneck; i.e., a single station with a larger mean processing time than all other stations. Our analysis shows that a bottleneck station draws buffers toward it, but the optimal allocation depends on the location and severity of the bottleneck, as well as the number of buffers available. Furthermore, relatively large imbalances in mean processing times are required to shift the optimal buffer allocation away from an equal allocation. Finally, line length appears to have a relatively small e...

Priority repair and dispatch policies for reparable‐item logistics systems

In this article we present the results of a simulation study concerned with reparable electronic equipment on military aircraft. Past studies in the literature have considered priority rules at the repair depot, and one study considered an allocation scheme for distributing repaired items to bases. In this study, we examine the use of a priority rule for sequencing items at a repair depot in conjunction with a priority rule for allocating repaired items to bases. We examine, among other things, the conditions under which it is favorable to consider priority rules. The results indicate that the important variables are the efficiency of the lateral resupply system, the initial allocation of spare stock, and the time it takes to ship items from the depot to bases. The objective throughout is to minimize the expected number of aircraft grounded due to lack of parts.

Multi-item service constrained (s, S) policies for spare parts logistics systems

Many organizations providing service support for products or families of products must allocate inventory investment among the parts (or, identically, items) that make up those products or families. The allocation decision is crucial in todays competitive environment in which rapid response and low levels of inventory are both required for providing competitive levels of customer service in marketing a firms products. This is particularly important in high-tech industries, such as computers, military equipment, and consumer appliances. Such rapid response typically implies regional and local distribution points for final products and for spare parts for repairs. In this article we fix attention on a given product or product family at a single location. This single-location problem is the basic building block of multi-echelon inventory systems based on level-by-level decomposition, and our modeling approach is developed with this application in mind. The product consists of field-replaceable units (i.e., parts), which are to be stocked as spares for field service repair. We assume that each part will be stocked at each location according to an (s, S) stocking policy. Moreover, we distinguish two classes of demand at each location: customer (or emergency) demand and normal replenishment demand from lower levels in the multiechelon system. The basic problem of interest is to determine the appropriate policies (siSi) for each part i in the product under consideration. We formulate an approximate cost function and service level constraint, and we present a greedy heuristic algorithm for solving the resulting approximate constrained optimization problem. We present experimental results showing that the heuristics developed have good cost performance relative to optimal. We also discuss extensions to the multiproduct component commonality problem.