Lead Time Reliability Research Articles

Replenishment strategies for lost sales inventory systems of perishables under demand and lead time uncertainty

We develop an inventory control policy for perishable products considering both random demand and random lead time. We consider a B2C retail environment where excess demand is lost. The policy dynamically determines the optimal replenishment quantity under a service level constraint in every period, allowing for order-crossing, a widely disregarded characteristic in the literature. Regarding perishability, we compare the two most extreme issuing policies, first-expired-first-out (FEFO) and last-expired-first-out (LEFO), and evaluate our policy to existing inventory policies for perishables that typically ignore lead time uncertainty.We obtain several interesting findings. First, we show that ignoring lead time uncertainty and planning based on the expected lead time significantly undershoots the target service level. Even planning with the maximum lead time, under LEFO, the achieved service level would still fall considerably below the target, which the lost-sales structure can explain. On the other hand, under FEFO, the achieved service level would overshoot the target service level, which leads to unnecessary waste. Second, a more reliable lead time can significantly reduce waste, especially under LEFO. Third, our model allows us to distinguish between past, present, and future lead time uncertainty and thus to consider partial lead time information. We show the value of lead time information on outstanding orders. Fourth, we evaluate the impact of a fast but unreliable delivery option and a slow but reliable delivery option on the retailer’s average waste and ordering process. We find that the optimal choice depends on the demand characteristics.

The lead time updating trap: Analyzing human behavior in capacitated supply chains

We analyze the lead time syndrome (LTS), which describes a positive feedback loop between lead time updating and increasing order quantities. While previous studies have focused on theoretical analysis and anecdotal evidence, we examine the impact of human decision making with the help of controlled laboratory studies using a novel experimental design of a simple two tier supply chain. We show that the theoretically postulated phenomenon of the LTS can be reproduced in the lab including human decision makers. We find that the dynamic (load dependent) lead time in the supply chain serves as coordination mechanism among retailers, i.e. experimental participants, but that this mechanism can be distorted by less reliable lead times. Comparing the experimental results to an optimization model in a rolling horizon setting, we further argue that human behavior initiates the vicious cycle of the LTS in our experiments. Finally, we find individual-level evidence for behavioral decision-making, in particular hedging behavior, in our experiment, due to various forms of uncertainty. We discuss the implications of these results in the light of supply chain and production planning systems.

Accounting for three sources of uncertainty in ensemble hydrological forecasting

Abstract. Seeking more accuracy and reliability, the hydrometeorological community has developed several tools to decipher the different sources of uncertainty in relevant modeling processes. Among them, the ensemble Kalman filter (EnKF), multimodel approaches and meteorological ensemble forecasting proved to have the capability to improve upon deterministic hydrological forecast. This study aims to untangle the sources of uncertainty by studying the combination of these tools and assessing their respective contribution to the overall forecast quality. Each of these components is able to capture a certain aspect of the total uncertainty and improve the forecast at different stages in the forecasting process by using different means. Their combination outperforms any of the tools used solely. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial conditions uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improving the general forecasting performance and prevents this performance from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. Particular attention needs to be paid to the combination of the tools, especially in the EnKF tuning to avoid overlapping in error deciphering.

Stochastic lot sizing for maximisation of shareholder wealth in make-to-order manufacturing

Current research in production planning focuses mainly on optimising operational objectives, taking little consideration of the primary principle of corporate governance and investor interests. Such approaches often overlook the critical roles of the cost structure and financial position of a firm, rendering the optimisation results unreliable. This paper studies stochastic lot sizing optimisation in make-to-order manufacturing, with an aim to maximise the full investor interests, well known as shareholder wealth. It presents a relatively simple yet reliable lead time model based on probability theory and stochastic processes. Moreover, the impacts of macroeconomic factors are examined to seek potential drivers for shareholder wealth. Theoretical optimality properties are proved to validate the effectiveness of the proposed model in dealing with batch production planning. Numerical examples and analytical results are presented to illustrate the significance of considering such economic and financial constraints and shareholder wealth. These results highlight that the proposed model can help improve shareholder wealth, and that it is a useful tool for examining the potential challenges and opportunities of shareholder wealth creation in production planning.

Simulation-based experimental design and statistical modeling for lead time quotation

In a produce-to-order environment, it is of substantial interest to be able to quote a tight and reliable lead time for a new job (or order) upon its arrival to a manufacturing system. This work developed a simulation-based statistical approach to provide responsive and high-quality prediction of a new job's flow time through the system, which renders the capability of accurately quoting lead times in real time. The approach integrates analytical queueing analysis, design of experiments, and statistical modeling to quantify the dependence of a new job's flow time distribution upon the shop status “seen” by that job. To the best of our knowledge, this is the first attempt to design simulation experiments in the space spanned by a complete set of shop status factors for the thorough investigation of the possible impacts those factors may have on the distribution of a new job's flow time. The method has been applied on a scaled-down semiconductor manufacturing system, and the quality of the quoted lead time has been evaluated based on a large and well-designed validation data set in terms of the six commonly used performance criteria.

Efficient detection of contagious outbreaks in massive metropolitan encounter networks.

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the “friend sensor” scheme - a simple, but universal strategy requiring only local information - and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced “global sensor sets”, obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.

Online scheduling with immediate and reliable lead-time quotation

This paper studies an online scheduling problem with immediate and reliable lead-time quotation. A manufacturer either accepts an order by quoting a reliable lead-time on its arrival or rejects it immediately. The objective is to maximize the total revenue of completed orders. Keskinocak et al. (Management Science 47(2):264---279, 2001) studied a linear revenue function in a discrete model with integer release time of order, and proposed a competitive strategy Q-FRAC. This paper investigates a relaxed revenue function in both discrete and continuous models where orders are released at integer and real time points, respectively. For the discrete model, we present a revised Q-FRAC strategy that is optimal in competitiveness for concave and linear revenue functions with unit length and uniform weight of order, improving the previous results in Keskinocak et al. (Management Science 47(2):264---279, 2001). For the scenario with uniform length $$p$$ p and nonuniform weight of order, we prove an optimal strategy for the case with $$p=1$$ p = 1 and the nonexistence of competitive strategies for the case with $$p>1$$ p > 1 . For the continuous model, we present an optimal strategy in competitiveness for the case with uniform weight of order and linear revenue functions, and prove the nonexistence of competitive strategies for the other case with nonuniform weight of order.

Mathematical Model for Supply Planning of Multi-level Assembly Systems with Stochastic Lead Times

The deal for industrial companies is to satisfy their customers with the best quality, the most reliable lead times, and the lowest costs. One of the keys to achieve it is in the inventory control in the Supply Chain. Moreover, it is mandatory to possess necessary components in order to produce the requested products by the due date. But, as the components lead time is an unpredictable parameter, it is difficult to take it into account correctly. The paper deals with this question considering that each component has a fixed unit inventory cost; the finished product has an inventory cost and a backlogging cost per unit of time. Then, a general mathematical model for supply planning of multilevel assembly system is presented to calculate the expected value of the total cost which equals to the sum of the inventory holding costs for the components, the backlogging and the inventory holding costs for the finished product.

The impact of lead time reliability in freight transport: A logistics assessment of transport economics findings

This paper considers speed and reliability, measured by the average and variance of the lead time, to examine the relevance of the latter variable on inventory costs. By using a flexible simulation framework, it is shown that reducing variability does not necessarily reduce costs and might in fact increase the costs of safety stock, depending on the shape of the demand distribution during lead time and the targeted service level. This offers a novel explanation for the wide variety of value of reliability figures obtained in empirical transport economics research.

Planning of capacities and orders in build-to-order automobile production: A review

In an attempt to achieve a competitive edge, automotive companies operate global production networks to offer an ever increasing product variety, shorter and reliable lead times as well as competitively priced products. Cars are no longer exclusively produced based on standardized product configurations and stable sales plans but are increasingly build-to-order to match the needs of individual customers. Operations Research (OR) may contribute towards successful build-to-order operations. This is likewise reflected by the appreciable number of published papers on industry specific OR applications. To provide readers with an overview about these OR models and applications we identify current and future research issues based on the review of 49 works. We focus on two important planning objects which have not been considered in prior reviews: the planning of capacities and orders. To bridge the gap between conceptual works on the one hand and quantitative contributions on the other, we provide a framework for the structuring of planning tasks. Existing models are classified according to this framework and open issues that should be addressed in OR are discussed.

Competitive analysis for make-to-order scheduling with reliable lead time quotation

This paper makes extended studies on the discrete problem of online scheduling and reliable lead time quotation (discrete Q-SLTQ) introduced by Keskinocak et al. (Manag. Sci. 47(2):264–279, 2001). We first relax the assumption on revenue function from a linear decreasing function to any decreasing function. We present an online deterministic strategy which is optimal in competitiveness for concave revenue functions. The above results are further extended to the continuous Q-SLTQ model where orders are released at arbitrary time points. For the discrete Q-SLTQ problem, if orders are with nonuniform lengths, we prove the nonexistence of online strategies with bounded competitive ratios; otherwise if orders are with unit length but various weights, we present an optimal online strategy.

Application of linear programming to swap analysis in supply chain management of oil industry

This paper proposes and examines several swap strategies for the oil industry to create win-win situations for companies supplying oil to their customers. A realistic data from a Kuwaiti oil company and its competitor, in another part of the world, is used to build a number of Linear Programming models of the strategies under investigation. The optimal solutions of these models are analyzed to identify the strategies' advantages or disadvantages. The success of swap strategies relies on alliances and partnerships between the oil companies. They, however, seem to advocate very attractive alternative policies, create potentials for substantial cost savings and assure more reliable lead-time to delivery.

Radar-based flood forecasting for river catchments

Weather radars provide high resolution in space and time and thus deliver distributed rainfall information. They therefore have high potential for exploitation in real-time flood forecasting. However, several aspects limit the accuracy of such data in flood forecasting systems. A major aspect is associated with the error included in the radar data and the limited lead time. To assess real-time flood forecasts and improve their reliable lead times with radar rainfall data, this paper presents a framework for a radar-based flood forecasting model integrating radar rainfall data, geographical information systems, the hydrological model HEC—HMS and a short-term precipitation nowcasting system. The benefit of the radar-based flood forecast is analysed and the limits of predictability due to the meteorological aspects of the rainfall forecast as well as the hydrological model are investigated. The incorporation of the radar-based rainfall forecast demonstrates good potential for successful hydrological modelling and prediction.

Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.

Supply Chain Management under the Threat of International Terrorism

On the morning of September 11th, 2001, the United States and the Western world entered into a new era ‐ one in which large scale terrorist acts are to be expected. The impacts of the new era will challenge supply chain managers to adjust relations with suppliers and customers, contend with transportation difficulties and amend inventory management strategies. This paper looks at the twin corporate challenges of (i) preparing to deal with the aftermath of terrorist attacks and (ii) operating under heightened security. The first challenge involves setting certain operational redundancies. The second means less reliable lead times and less certain demand scenarios. In addition, the paper looks at how companies should organize to meet those challenges efficiently and suggests a new public‐private partnership. While the paper is focused on the US, it has worldwide implications.

Scheduling and Reliable Lead-Time Quotation for Orders with Availability Intervals and Lead-Time Sensitive Revenues

Motivated by applications in the manufacturing and service industries, we consider two models for coordinating scheduling with lead-time quotation: a basic model with a single customer type, and an enhanced model where an additional second customer type expects immediate service or production. In both models, revenues obtained from the customers are sensitive to the lead time, there is a threshold of lead time above which the customer does not place an order, and the quoted lead times are 100% reliable. These models are related to well-known scheduling problems, which have been studied in both offline and online settings. We introduce the immediate quotation case and study it with the (traditional) online version. We provide complexity results for the offline case, and perform competitive analysis for the online cases. A natural question of bridging the gap between the online and quotation models leads us to the delayed quotation model, which we study briefly. The analysis of these models provides useful qualitative insights as well.

Identification of aggregate resource and job set characteristics for predicting job set makespan in batch process industries

We study multipurpose batch process industries with no-wait restrictions, overlapping processing steps, and parallel resources. To achieve high utilization and reliable lead times, the master planner needs to be able to accurately and quickly estimate the makespan of a job set. Because constructing a schedule is time consuming, and production plans may change frequently, estimates must be based on aggregate characteristics of the job set. To estimate the makespan of a complex set of jobs, we introduce the concept of job interaction. Using statistical analysis, we show that a limited number of characteristics of the job set and the available resources can explain most of the variability in the job interaction.

Strategies for integrating lead time and customer-order decisions

Make-to-order manufacturers are facing unprecedented challenges to fill their customer orders quickly and to reduce their operating costs. In this paper, we first describe and discuss order taking and lead time quoting practice in a real world make-to-order manufacturing system. We then develop a model for this practical problem to study the conflicting objectives, of delivering customized orders quickly and maximizing expected profit. The primary goal of this paper is to develop a general model for studying the trade-offs and the interrelationships among the following manufacturing performance measures: manufacturing flow times, quoted lead time reliability (earliness and tardiness), throughput (or demand) rates, inventory levels, resource utilization, and expected profits. These and other related managerial issues are explored. Our structural results yield insights into basic choices between filling customer orders quickly and maximizing expected profit.