Quoted Lead Time Research Articles

Delivery leadtime and channel structure decisions for make-to-order duopoly under different game scenarios

We develop game-theoretic models to explore the quoted delivery leadtime, price, and channel structure decisions for a make-to-order duopoly system under three game scenarios. Under the integrated-manufacturer first scenario, we find that (i) decentralization of the supply chain increases quoted leadtime; and (ii) both manufacturers may choose different channel structures under symmetric duopoly. By comparing with the symmetric scenario and the retailer first scenario, we find that a manufacturer facing a decentralized rival adopts decentralization when leadtime sensitivity, leadtime cost, and price elasticity are very small; the effect of decentralization on quoted leadtime largely depends on game scenario.

Lead Time Quotation and Customer Utility in an M/M type Base Stock System

Information on demand and lead time is useful for production control and consumer’s decision. In this paper, a one-stage production and inventory system with a base stock policy, which is defined by Savasaneril et. al (2010), is considered. Each arriving customer decides whether he/she enters the system based on the quoted lead time informed by the system. The decision is made by a utility function of customers. An optimal lead time policy for the system to maximize the system’s profit is derived by a Markov decision process. Several kinds of heuristic policies are compared with optimal policies with respect to both profits and customer’s utilities.

Coping with production time variability via dynamic lead-time quotation

In this paper, we propose two dynamic lead-time quotation policies in an M/GI/1 type make-to-stock queueing system serving lead-time sensitive customers with a single type of product. Incorporating non-exponential service times in an exact method for make-to-stock queues is usually deemed difficult. Our analysis of the proposed policies is exact and requires the numerical inversion of the Laplace transform of the sojourn time of an order to be placed. The first policy assures that the long-run probability of delivering the product within the quoted lead-time is the same for all backlogged customers. The second policy is a refinement of the first which improves the profitability if customers are oversensitive to even short delays in delivery. Numerical results show that both policies perform close to the optimal policy that was characterized only for exponential service times. The new insight gained is that the worsening impact of the production time variability, which is felt significantly in systems accepting all customers by quoting zero lead times, decreases when dynamic lead-time quotation policies are employed.

Capacity and lead-time management when demand for service is seasonal and lead-time sensitive

In today’s competitive business environment, quick service with minimal waiting time is an important factor for customers when choosing a service. Many service organizations guarantee a uniform lead-time to all customers in order to gain competitive advantages in the market. In selecting a lead-time to quote, the firm has to take into consideration not only how customers will react to the delivery time guarantee, but also whether it has adequate capacity to fulfill the commitment. A short lead-time can bring both benefits and costs. It can increase customer demand, but might require a higher capacity level. We present a mathematical model and a solution method for determining the optimal quoted lead-time and capacity level for a profit-maximizing firm with time-varying and lead-time sensitive demand. The firm incurs convex capacity costs and pays lateness penalties whenever the actual lead-time exceeds the quoted lead-time. A few studies have been conducted on the relationship between uniform lead-time, capacity, demand, and overall profitability. However, none of them takes the time variation of demand into account. Our work differs from previous research in that we explicitly model such a demand pattern.

The Research of the Lead Time and the Profit in Centralized Dual-Channel Supply Chain

Internet has changed customers’ consumption patterns a lot. And it also has changed the manufactures’ sale model. These phenomena bring us reformation and challenge. In direct channel, price is always cheaper than that in traditional channel and we can get much profit. Empirical studier shows that lead time is one of the major factors influencing consumer acceptance. A short lead time can increase the logistics, but the long lead time will reduce customers’ acceptance and the loyalty. Therefore, researching the lead time and the profit is important for dual-channel. In this paper, we study the lead time in centralized dual-channel supply chain and its impact on profit. We build the dual-channel supply chain model including quoted lead time and examine the relationship about the lead time, profit and

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.

A Decision Support System for the Stochastic Aggregate Planning Problem

An advanced decision support system is presented to answer aggregate planning questions regarding the trade-off between demand (product-mix) and supply (capacity) in a multi period stochastic setting. This tool improves the effectiveness and efficiency of sales and operation planning meetings by accounting for both revenues and costs that are relevant at the intermediate planning horizon. We develop a multi product, multi routing model, where a routing consists of a sequence of operations on different resources. Given customer demand in each time period, the model obtains the optimal production quantities in every period for each alternative routing, while explicitly taking into account the stochastic nature of both demand patterns and production lead times. This is the key difference between our approach and traditional aggregate planning models. At the same time, an optimal capacity level for each resource is obtained. We include trade-offs between level and chase strategies by charging costs for inventory, work-in-process, backorders, setups, regular time, overtime, etc. Outsourcing is considered as an alternative source with a stochastic lead time. The methodology builds upon a queueing network to estimate product’s lead time distribution and associated quoted lead time with a service level. More system improvements can be obtained by proper lot sizing. This model is a mixed integer non-linear programming problem. We show that the search process of the differential evolution algorithm is efficient to find stable results within acceptable time limits. A scenario analysis reveals interesting managerial insights.

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.

Manufacturing Work Study and System Analysis of the NIFOR Digester Screw Press

It is generally assumed that the probability of the customer placing an order is always one, implying that customers will place orders regardless of producer quoted lead times and customer lead time expectations. As the job shops increasingly compete on the basis of the delivery speed and reputation, the relative performance of quoted versus actual realized lead times will have a strong effect on whether the customer will place future orders or not. A work study and manufacturing system analysis was conducted on the NIFOR digester screw press to study the techniques of job shop scheduling. Incessant delay in manufacturing process, job tardiness and unsatisfactory customers feedback had led to this research work. The work involves critical examination of all the resources and factors which affect the efficiency of the job shop. Machines set up times and run times were collected at each machine centre for all the components produced during the period of evaluation. The data collected were used as input data for the Gantt chart to evaluate the total actual times spent in performing each task. The work provides useful information for the development of an improved method of job scheduling for effective machine utilization so as to minimize the total time required for completion of all manufacturing tasks and reduce job tardiness.

Lead-time quotation when customers are sensitive to reputation

Firms consider a variety of factors when making lead-time promises, including current shop status and the size of the incoming order. The profit-maximising model presented in this paper is the first to include reputation effects explicitly in a lead-time optimisation model. Reputation is considered to be the lasting effect on the market of a firm’s delivery performance over time, and so it affects the future as well as the current profits. The model is complicated, and a counter-example demonstrates that qualitative monotonicity results are not obtainable. A computational study explores the relationships between shop status, order size, reputation, market characteristics and the lead-time decision. Regression analysis sheds light on these relationships and suggests three heuristics, which provide near-optimal solutions with relatively short running times.

Expected Tardiness Computations in Multiclass Priority M/M/c Queues

We discuss the evaluation of expected tardiness of an order at the time of arrival in an M/M/c queuing system with N priority classes, considering both nonpreemptive and preemptive service disciplines. Upon arrival, a customer order is quoted a lead time of d, and placed in the queue according to the priority class of the customer. Orders within the same priority class are processed on a first-come, first-served basis. We derive the Laplace transforms of the expected tardiness of the order given the quoted lead time, priority class of the order, and system status. For the special case of single priority class, the Laplace transform can be inverted into a closed-form expression. For the case with multiple priority classes, a closed-form expression cannot be obtained, hence, we develop three customized numerical inverse Laplace transformation algorithms. Two of these algorithms provide upper and lower bounds for the expected tardiness under a simple condition on system parameters. Using this property, we obtain error bounds for our customized algorithms; such bounds are not available for general purpose numerical inversion algorithms in the literature. Next, we develop a novel methodology to compare the precision of general purpose numerical inversion algorithms and analyze the performances of three algorithms from the literature. Finally, we provide a recommendation scheme given computational time and error tolerances of the decision maker. The methods developed in this paper for the accurate estimation of expected tardiness establish an important step toward developing due date quotation policies in a multiclass queue, contributing to the due date quotation literature that has been largely focused on single-class queues.

Production and lead time quotation under imperfect shop floor information

We study the value of shop floor information for a manufacturer that operates under a make-to-stock queue scheme and quotes lead times to arriving customers. Two settings are analyzed where in the first setting the manufacturer is able to perfectly track the shop floor status, and in the second setting the manufacturer makes decisions under imperfect information. Under imperfect information, the problem is modeled as a Partially Observable Markov Decision Process. In the computational analysis, first the impact of information distortion on the policies is analyzed and it is shown that the increased likeliness of observing the true status of the system does not necessarily lead to higher profit. Further numerical analysis shows that as the inaccuracy in the data (range of error) increases, the value of information increases. The value of information is likely to be higher under high holding cost and low traffic. Then, the effect of Make-to-Order (MTO) and Make-to-Stock (MTS) queue schemes, as well as the effect of different lead time quotation schemes on the value of information are evaluated. Under MTO queue scheme shop floor information is more valuable under high traffic intensity, whereas under MTS queue scheme information is more valuable under lower intensity. Finally, the analysis reveals that if a firm quotes more precise lead times, then the need for actual shop floor information increases.

Optimal Pricing and Capacity Investment for Delay-Sensitive Demand

We study a firm's joint decisions on product prices, delivery lead times, and capacity investments of the production facility. We assume customers are strategic and heterogeneous in their sensitivity to waiting. The firm can offer a single service to all customers or two services with different delivery lead times and prices. We investigate a firm's optimal decisions when the firm is a monopolist or under a duopoly competition. We find that a monopoly firm's optimal capacity level decreases in service level. For a monopoly firm providing differentiated services, we find that the optimal facility utilization level does not depend on unit capacity cost. Furthermore, we demonstrate that a monopoly firm always gets more profits by providing differentiated services than a single service. For duopoly competition, we show the existence of a Nash equilibrium. Finally, we illustrate that a firm offering shorter lead time quotation may earn less profit than one offering longer lead time quotation when two firms compete in an industry with discrete lead times.

Order acceptance and scheduling policies for a make-to-order environment with family-dependent lead and batch setup times

In many make-to-order production situations with batch setup times, customer orders are grouped into family-dependent batches to limit the loss of capacity due to setups. These batches, however, cannot be too large, since the make-to-order character requires that orders have to be produced in time. This trade-off between setup time efficiency and due-date adherence creates a challenging scheduling problem referred to in the literature as the Customised Stochastic Lot Scheduling Problem. Typically, suppliers reduce the complexity of the production problem by quoting lead times that are equal for all customer families. This choice, however, is in many cases too restrictive. In this paper, we show quantitatively by means of Markov decision processes (MDPs) that using family-dependent lead times can result in a significant gain in profit as compared with using standard lead times. We develop a simple heuristic acceptance/scheduling policy, and demonstrate that this heuristic performs very well compared with the optimal policy of the MDP for a wide range of parameters.

In This Issue

In This Issue

Congestion-Based Lead-Time Quotation for Heterogenous Customers with Convex-Concave Delay Costs: Optimality of a Cost-Balancing Policy Based on Convex Hull Functions

We consider a congestible system serving multiple classes of customers who differ in their delay sensitivity and valuation of service (or product). Customers are endowed with convex-concave delay cost functions. A system manager offers a menu of lead times and corresponding prices to arriving customers, who then choose the lead-time–price pair that maximizes their net utility (value minus disutility of delay and price). We investigate how such menus should be chosen dynamically (depending on the system backlog) to maximize welfare. We formulate a novel fluid model of the problem and show that the cost-balancing policy (based on the convex hulls of the delay cost functions) is socially optimal if the system manager can tell customer types apart. If types are indistinguishable to the system manager, the cost-balancing policy is also incentive compatible under social optimization. Finally, we show through a simulation study that the cost-balancing policy does well in the context of the original (stochastic) problem by testing it against various natural benchmarks.

Adaptive lead time quotation in a pull production system with lead time responsive demand

In this paper, a single-stage single-class kanban controlled manufacturing system is considered, where the problem is quoting accurate lead times for orders that are generated by an MRP system. Order release mechanism as in classical MRP is sensitive to the changes in the lead time according to the concept of lead time syndrome. The objective is to establish a cost effective lead time quoting procedure. The problem is modeled as a two-dimensional Markov chain, and it is solved explicitly by using matrix geometric techniques. Comparative analysis is done between static and dynamic lead time quoting procedures, and significant cost benefits of the dynamic procedure are shown under various scenarios. Guidelines for setting design parameters such as the number of kanbans and the frequency of updating the lead time are provided through numerical tests.

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.

Congestion-based leadtime quotation and pricing for revenue maximization with heterogeneous customers

This paper studies a queuing model where two customer classes compete for a given resource and each customer is dynamically quoted a menu of price and leadtime pairs upon arrival. Customers select their preferred pairs from the menu and the server is obligated to meet the quoted leadtime. Customers have convex–concave delay costs. The firm does not have information on a given customer’s type, so the offered menus must be incentive compatible. A menu quotation policy is given and proven to be asymptotically optimal under traditional large-capacity heavy-traffic scaling.

Contributors

Contributors