Refuse or reuse: managing the quality of returns in product recovery systems

Increasing legislative and societal pressures are forcing manufacturers to become environmentally-conscious and take responsibility for the fate of their goods after they have been used by consumers. As a result, some manufacturers operate hybrid systems which produce new goods and recover used goods. Product recovery describes the process by which used products are returned to their manufacturers or sent to a specialised facility for recovery, before being sold on the original or a secondary market. The quality of the returned goods is a significant issue in product recovery systems as it can affect both the type of recovery and costs associated with it. Quality in product recovery systems has not been adequately studied, with many authors either ignoring the possibility of receiving lower quality returns, or assuming they are disposed of rather than recovered. However, such assumptions ignore the possibility that the firm might be able to salvage value from lower quality returns by using them for parts or materials. This thesis presents four models that investigate the importance of considering the quality of returns in the management of inventory in a product recovery system, by examining the cost-effectiveness of recovering both high quality and low quality returns. The first model is a deterministic lot-sizing model of a product recovery system. It was found that performing both high and low quality recovery reduced the sensitivity of the optimal cost to operational restrictions on the choice of decision variables. The second model is a discrete-time, periodic-review model formulated as a Markov decision process (MDP) and introduces uncertainty in demand, returns, and the quality of the returns. It was found that performing both types of recovery can lead to cost savings and better customer service for firms through an increased fill rate. The third model addresses those industries where produced and recovered goods cannot be sold on the same market due to customers’ perceptions and environmental legalisation. Using an MDP formulation, the model examines a product recovery system in which produced and recovered goods are sold on separate markets. The profitability of offering two-way substitution between these markets was investigated. It was found that offering substitution can allow firms to increase both their profits and fill rates. The fourth model examines the issue of separate markets and substitution in the continuous time domain using a semi-Markov decision process. The continuous nature of the model allows more detailed examination of the substitution decision. It was found that offering substitution can allow firms to increase their profit and in some cases also increase their fill rate. In some cases, production is performed less frequently when downward substitution can be offered, and recovery is performed less often when upward substitution can be offered. The findings of this thesis could be used to help a firm that is currently recovering high quality returns assess the cost-effectiveness of also recovering lower quality returns. Recovering low-quality items, rather than disposing of them, may allow a firm to increase the amount it recycles. The findings highlight the importance of considering the quality of returns when managing a product recovery system as they show that economic gains can be achieved by reusing rather than refusing low quality returns

Optimal scope of supply chain network & operations design

The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are significant and that has attracted considerable research attention since the late 1990s. This doctoral thesis focuses on developing manageable and realistic optimization models for solving four contemporary and interrelated supply chain network and operations design problems. Each requires an integrated decision-making approach for advancing supply chain effectiveness and efficiency. The first model formulates the strategic robust downsizing of a global supply chain network, which requires an integrated decision-making on resource allocation and network reconfiguration, given certain financial constraints. The second model also looks at the strategic supply chain downsizing problem but extends the first model to include product portfolio selection as a downsizing decision. The third model concerns the redesign of a warranty distribution network, which requires an integrated decision-making on strategic network redesign and tactical recovery process redesign. The fourth model simultaneously determines the operational-level decisions on job assignment and process sequence in order to improve the total throughput of a production facility unit

Optimal lot-sizing, pricing, and product intergenerational lifestyle decisions for the case of disruptive innovations in fashion

The objective of this dissertation is to determine production schedules, production quantities, selling prices, and new product introduction timing to fulfill deterministic price-dependent demand for a series of products in such a way as to maximize profit per period. In order to accomplish the above task, some main assumptions are made. First, it is assumed that the series of products being considered are associated with sequential non-disruptive innovations in technology as well as disruptive innovations in fashion. That is to say, the products represent subsequent generations in the same family of products in an industry that experiences repeated minor technological innovations and in which product success is due in part to fashionability (Fisher, 1997). Second, it is assumed that the planning horizon is sufficiently long and product lifecycles are sufficiently short that several generations of the product family are planned. Third, it is assumed that the producer is following a solo-product roll strategy (Billington, Lee, & Tang, 1998). This means that the inventory of one product iteration is exhausted at the same time that the next product iteration is introduced and ready for sale. Fourth, it is assumed that demand for each product iteration is governed by a modified version of the Bass (1969) diffusion model that incorporates price. Fifth, it is assumed that the various demand and cost characteristics being considered do not change from one product iteration to the next. Sixth, it is assumed that no backlog of demand is maintained and that any unmet demand is lost. Seventh, it is assumed that the manufacturer is a monopolist or at least the dominant member of a market that is made up of it and smaller competitors that are not large enough to affect the market in a meaningful way. The formulated profit maximization problem uses the Thomas (1970) model which in turn depends in its solution on theorems first presented by Wagner and Whitin (1958a). An extensive numerical study that aims at examining the sensitivity of the planned product lifecycle length and profit per period to changes in model parameters is performed using software developed especially for that purpose. The results of the analysis reveal that the above two measures are more sensitive to changes in market-oriented parameters than to changes in operations-oriented parameters. Managerial implications of the research findings are discussed

Revenue Management for Make-to-Order and Make-to-Stock Systems

With the success of Revenue Management (RM) techniques over the past three decades in various segments of the service industry, many manufacturing firms have started exploring innovative RM technologies to improve their profits. This dissertation studies RM for make-to-order (MTO) and make-to-stock (MTS) systems. We start with a problem faced by a MTO firm that has the ability to reject or accept the order and set prices and lead-times to influence demands. The firm is confronted with the problem to decide, which orders to accept or reject and trade-off the price, lead-time and potential for increased demand against capacity constraints, in order to maximize the total profits in a finite planning horizon with deterministic demands. We develop a mathematical model for this problem. Through numerical analysis, we present insights regarding the benefits of price customization and lead-time flexibilities in various demand scenarios. However, the demands of MTO firms are always hard to be predicted in most situations. We further study the above problem under the stochastic demands, with the objective to maximize the long-run average profit. We model the problem as a Semi-Markov Decision Problem (SMDP) and develop a reinforcement learning (RL) algorithm-Q-learning algorithm (QLA), in which a decision agent is assigned to the machine and improves the accuracy of its action-selection decisions via a “learning process. Numerical experiment shows the superior performance of the QLA. Finally, we consider a problem in a MTS production system consists of a single machine in which the demands and the processing times for N types of products are random. The problem is to decide when, what, and how much to produce so that the long-run average profit. We develop a mathematical model and propose two RL algorithms for real-time decision-making. Specifically, one is a Q-learning algorithm for Semi-Markov decision process (QLS) and another is a Q-learning algorithm with a learning-improvement heuristic (QLIH) to further improve the performance of QLS. We compare the performance of QLS and QLIH with a benchmarking Brownian policy and the first-come-first-serve policy. The numerical results show that QLIH outperforms QLS and both benchmarking policies

Application of Semi-Analytical Methods in Production Systems Engineering: Serial Lines

Production lines can be designed by an analytical, semi-analytical, or numerical approach. This paper gives a brief introduction to the analytical approach of a single buffer line, the aggregation method, and the analytical approach of a multi-buffer line. An automotive paint shop production system will be used as a figurative example to compare the aggregation method and the recently developed analytical approach for a multi-buffer line. A discussion at the end will show the advantages and disadvantages of the analytical approach

Evaluating the impact of adopting 3d printing services on the retailers

As additive manufacturing technology becomes more responsive to consumers’ demand, one important question for the retailers is whether they should provide 3D printing services in their brick-and-mortar store in addition to the traditional off-the-shelf product? If so, what should be the retailers pricing scheme to achieve a higher profit? What should be the optimal inventory level of off-the-shelf products? What is the optimal capacity of 3D printers? In this study, stochastic models are examined to capture the joint optimal 3D product price and capacity of 3D printers to maximize retailer’s expected profit while considering consumer product choices. Moreover, a stochastic model is developed to capture joint optimal pre-made inventory level and 3D product price to maximize retailer’s expected profit considering 3D services are offered in the off-the-shelf stock-out situations as a one-way substitution. Utilizing the Markov Decision Process, a framework for queuing systems is developed to examine the performance of various production/inventory strategies that optimize the system’s performance. Here, four strategies are developed: (i) providing only off-the-shelf products, (ii) providing only 3D printed products, (iii) substituting the shortage of the off-the-shelf products by 3D printed products, and (iv) providing consumers the options of selecting either the off-the-shelf product or the customized product produced by additive manufacturing. In essence, this approach assists decision makers in both capacity planning and inventory management. For all models, analytical results and numerical examples are given in order to demonstrate managerial insights

Constructive solution methodologies to the capacitated newsvendor problem and surrogate extension

The newsvendor problem is a single-period stochastic model used to determine the order quantity of perishable product that maximizes/minimizes the profit/cost of the vendor under uncertain demand. The goal is to fmd an initial order quantity that can offset the impact of backlog or shortage caused by mismatch between the procurement amount and uncertain demand. If there are multiple products and substitution between them is feasible, overstocking and understocking can be further reduced and hence, the vendor\u27s overall profit is improved compared to the standard problem. When there are one or more resource constraints, such as budget, volume or weight, it becomes a constrained newsvendor problem. In the past few decades, many researchers have proposed solution methods to solve the newsvendor problem. The literature is first reviewed where the performance of each of existing model is examined and its contribution is reported. To add to these works, it is complemented through developing constructive solution methods and extending the existing published works by introducing the product substitution models which so far has not received sufficient attention despite its importance to supply chain management decisions. To illustrate this dissertation provides an easy-to-use approach that utilizes the known network flow problem or knapsack problem. Then, a polynomial in fashion algorithm is developed to solve it. Extensive numerical experiments are conducted to compare the performance of the proposed method and some existing ones. Results show that the proposed approach though approximates, yet, it simplifies the solution steps without sacrificing accuracy. Further, this dissertation addresses the important arena of product substitute models. These models deal with two perishable products, a primary product and a surrogate one. The primary product yields higher profit than the surrogate. If the demand of the primary exceeds the available quantity and there is excess amount of the surrogate, this excess quantity can be utilized to fulfill the shortage. The objective is to find the optimal lot sizes of both products, that minimize the total cost (alternatively, maximize the profit). Simulation is utilized to validate the developed model. Since the analytical solutions are difficult to obtain, Mathematical software is employed to find the optimal results. Numerical experiments are also conducted to analyze the behavior of the optimal results versus the governing parameters. The results show the contribution of surrogate approach to the overall performance of the policy. From a practical perspective, this dissertation introduces the applications of the proposed models and methods in different industries such as inventory management, grocery retailing, fashion sector and hotel reservation

Spare Parts Management of Aging Capital Products

Spare parts are critical for operations of capital products such as aircraft, refineries, trucks, etc/, which require maintenance regularly. Original Equipment Manufacturers (OEMs) bear the responsibility of undisrupted maintenance service and spare parts flow for their capital products. Due to various factors OEMs lose their spare parts suppliers occasionally and these losses threaten the reliability of their maintenance service and capital products. In this thesis, we consider supply risk in management of spare parts inventory. The thesis consists of two parts: First we develop advance indicators for future supply problems of spare parts and suggest a model utilizing those indicators for inventory control of spare parts. Our results indicate that OEMs can save significantly by utilizing those indicators together with our model in their daily business. Second, we consider secondary markets and their effects on spare parts supply chains of OEMs. Secondary markets are chap supply sources for spare parts needs of OEMs. Therefore effective usage of them yield significant cost savings and boost service rate of OEMs. Furthermore, secondary markets are sources of competition since low prices on those markets attract some customers of OEMs. These two factors are considered from the perspective of spare parts inventory control. In the second part, we conclude that for OEMs it is beneficial to use secondary markets as a supply source as long as they adjust their selling prices accordingly

Analysis of an inventory system with product perishability and substitution: a simulation-optimization approach

This thesis focuses on some inventory management policies for substitutable and perishable items under demand uncertainty. A set of perishable products with fixed shelf lives is considered under an (R,Si) system of inventory control where demand for a preferred product can be satisfied by a substitute product with a known probability, in the event of a stockout of the preferred product. While taking demand substitution and product expiration into account, the retailer is faced with the decision of determining the order-up-to level, Si, for each product i which maximizes expected total profit, given a common review period, R, determined exogenously.Under demand uncertainty, the problem detailed in this thesis involves stochastic optimization. An exact closed form expression, however, for expected profits becomes difficult for certain parameter values involving product shelf-life, product substitution, and lead time. As an alternative approach, order replenishment, demand consumption, substitution, and product expiration can be effectively modeled using discrete-event simulation. Through a discrete-event simulation model, each realization of the profit function can be evaluated for a selected value of Si, and a mean profit value can be estimated after a number of replications of a simulation run. In order to find the best Si solution, the technique of simulation-optimization is used.This thesis also examines the impact of key parameters such as substitution characteristics, shelf-life, cost structure, lead time, and number of products on the choice of inventory issuing policy on both the optimal Si levels and corresponding mean profit values. Through a factorial experimental design, the effects of these parameters on system performance are analyzed. In addition, heuristics are proposed and tested in order to provide managers with a convenient set of rules for determining near-optimal Si values in practice.Ph.D., Decision Sciences -- Drexel University, 200