Dennis E. Blumenfeld

Distribution Strategies that Minimize Transportation and Inventory Costs

This paper develops an analytic method for minimizing the cost of distributing freight by truck from a supplier to many customers. It derives formulas for transportation and inventory costs, and determines the optimal trade-off between these costs. The paper analyzes and compares two distribution strategies: direct shipping i.e., shipping separate loads to each customer and peddling i.e., dispatching trucks that deliver items to more than one customer per load. The cost trade-off in each strategy depends on shipment size. Our results indicate that, for direct shipping, the optimal shipment size is given by the economic order quantity EOQ model, while for peddling, the optimal shipment size is a full truck. The peddling cost trade-off also depends on the number of customers included on a peddling route. This trade-off is evaluated analytically and graphically. The focus of this paper is on an analytic approach to solving distribution problems. Explicit formulas are obtained in terms of a few easily measurable parameters. These formulas require the spatial density of customers, rather than the precise locations of every customer. This approach simplifies distribution problems substantially while providing sufficient accuracy for practical applications. It allows cost trade-offs to be evaluated quickly using a hand calculator, avoiding the need for computer algorithms and mathematical programming techniques. It also facilitates sensitivity analyses that indicate how parameter value changes affect costs and operating strategies.

ANALYZING TRADE-OFFS BETWEEN TRANSPORTATION, INVENTORY AND PRODUCTION COSTS ON FREIGHT NETWORKS

The purpose of this paper is to determine optimal shipping strategies (i.e. routes and shipment sizes) on freight networks by analyzing trade-offs between transportation, inventory, and production set-up costs. Networks involving direct shipping, shipping via a consolidation terminal, and a combination of terminal and direct shipping are considered. This paper makes three main contributions. First, an understanding is provided of the interface between transportation and production set-up costs, and of how these costs both affect inventory. Second, conditions are identified that indicate when networks involving direct shipments between many origins and destinations can be analyzed on a link-by-link basis. Finally, a simple optimization method is developed that simultaneously determines optimal routes and shipment sizes for networks with a consolidation terminal and concave cost functions. This method decomposes the network into separate sub-networks, and determines the optimum analytically without the need for mathematical programming techniques.

Throughput analysis of production systems: recent advances and future topics

Throughput analysis is important for the design, operation and management of production systems. A substantial amount of research has been devoted to developing analytical methods to estimate the throughput of production systems with unreliable machines and finite buffers. In this paper we summarise the recent studies in this area. In addition to the performance evaluation of serial lines, approximation methods for more complex systems, such as assembly/disassembly systems, parallel lines, split and merge, closed-loop systems, etc., are discussed. Moreover, we propose future research topics from the automotive manufacturing systems perspective.

Designing production systems for quality: Research opportunities from an automotive industry perspective

We explore the intersection of two research areas: quality and production system design. Conventional wisdom holds that a products quality is affected much more by its design than its production. Nevertheless, we argue that the production system used to manufacture a product does indeed affect its quality. We briefly review the limited literature on the intersection of quality and production system design and suggest several new research issues that are important to industry.

SYNCHRONIZING PRODUCTION AND TRANSPORTATION SCHEDULES

This paper examines whether it is cost-effective to synchronize production and transportation schedules on a production network. The network considered consists of one origin and many destinations. The origin produces parts that are shipped directly to each destination. Trade-offs between production set-up, freight transportation, and inventory costs on the network are analyzed, and total costs are compared for synchronized and independent schedules. The paper focuses on a simple production system, which can be modeled analytically and which allows the basic issues in synchronizing schedules to be addressed. Results suggest that cost savings from synchronization can be sufficiently large to warrant further research into more realistic albeit more complex production systems.

Chained cross-training of workers for robust performance

Training workers to perform multiple tasks can improve workforce agility for dealing with variations in workload. However, cross-training can be costly, time consuming to implement, is limited by worker learning capacity, and can lead to ambiguity about work responsibilities. Therefore, it is important to implement cross-training in the most efficient way and especially, due to the training time required, in a way that is robust to system changes. We use queueing and simulation analysis to investigate cross-training in the context of maintenance in a manufacturing plant. The tasks are independent and can be represented as a set of parallel queues that are served by dedicated and cross-trained workers. We propose a cross-training strategy called chaining, in which a few workers are strategically cross-trained, and show that it yields most of the benefits of cross-training all workers, with much less effort. Most importantly, we demonstrate that cross-training workers to form a “complete chain” is extremely robust in the following ways: (i) it is insensitive to the variety of ways a complete chain can be formed; (ii) it performs well even if there are major changes to or uncertainty in system parameters (such as mean task arrival rates); and (iii) performance is insensitive to control decisions that, without complete chaining, can significantly harm performance.

Chained cross-training of assembly line workers

To function properly, assembly lines require the presence of every worker. When a worker is absent, management must scramble quickly to find a replacement. Cross-training workers to perform multiple tasks mitigates this difficulty. However, since cross-training is costly and limited by learning capacity and can confound the search for quality problems, it should be used judiciously. The present paper proposes a training strategy called chaining in which workers are trained to perform a second task, and the assignments of task types to workers are linked in a chain. It is shown that chaining is a practical and effective strategy for prioritizing cross-training to compensate for absenteeism on assembly lines.

A simple formula for estimating throughput of serial production lines with variable processing times and limited buffer capacity

SUMMARY This paper develops an analytical formula for throughput (jobs per hour) of a serial production line with variable processing times and limited buffer capacity. For a line with identical workstations in series, throughput can be accurately estimated by a simple function of four parameters: mean and standard deviation of processing times, number of stations, and buffer size. Extensions of the formula to account for differences between stations are also presented. The formula allows line performance to be assessed quickly and easily with minimal data, and is useful in initial production system design.

Production system design for quality robustness

In automotive assembly plants, vehicles with defects are either repaired (e.g., components are exchanged, scratches are polished, etc.) or reworked (e.g., the whole vehicle is repainted) to maintain high product quality. The performance of vehicle quality is typically characterized in terms of the first time quality and also the quality buy rate. First time quality is defined as the good job ratio of all first time processing jobs, while the quality buy rate is the good job ratio of all processed jobs, including the first time jobs and reworked jobs. In this paper, we study a repair and rework system at an automotive paint shop with random first time quality. Specifically, we show that paint quality, in terms of quality buy rate, can be described by a function of repair capacity and first time quality. Increasing the repair capacity can improve the quality buy rate and reduce unnecessary repaints. Variations in first time quality may lead to a reduction in the quality buy rate and an increase in unnecessary repaints, and consequently, a substantial waste of production capacity and materials. In addition, we observe that the average quality buy rate depends primarily on the mean and coefficient of variation of the first time quality rather than its complete distribution. Based on these results, we introduce the notion of quality robustness and show that the design of a production system should accommodate randomness in first time quality to achieve a robust quality buy rate. Finally, a case study on a repair and rework system redesign to improve paint quality is presented.

An Analytical Evaluation of a Real-Time Traffic Information System Using Probe Vehicles

Abstract As the number of vehicle miles traveled each year continues to increase, traffic congestion only worsens, and the need for accurate, timely traffic information becomes stronger. With recent advances in technology, a growing number of vehicles are now equipped with wireless communication systems and global positioning satellite (GPS) sensors. Using such vehicles as mobile traffic probes has the promise of accurate and timely information without large infrastructure and construction expenses. To address some of the basic design and feasibility questions for the concept of using probe vehicles to provide real-time traffic information, an analytical model was developed that examines the relationships between key system parameters. The results of this modeling show that a real-time traffic information system based on probe vehicles is very feasible, and should work for freeways at penetrations over 3%, while surface roads would require more than 5%. With the increased use of in-vehicle telematics, these levels of penetration are likely to be achievable.