Ruud H. Teunter

Matching Demand and Supply to Maximize Profits from Remanufacturing

The profitability of remanufacturing depends on the quantity and quality of product returns and on the demand for remanufactured products. The quantity and quality of product returns can be influenced by varying quality-dependent acquisition prices, i.e., by using product acquisition management. Demand can be influenced by varying the selling price. We develop a simple framework for determining the optimal prices and the corresponding profitability. We motivate and illustrate our framework using an application from the cellular telephone industry.

Review of inventory systems with deterioration since 2001

This paper presents an up-to-date review of the advances made in the field of inventory control of perishable items (deteriorating inventory). The last extensive review on this topic dates back to 2001 (Goyal S.K. and Giri B.C., Recent trends in modeling of deteriorating inventory, European Journal of Operational Research, 134, 1–16). Since then, over two hundred articles on this subject have been published in the major journals on inventory control, indicating the need for a new review. We use the classification of Goyal and Giri based on shelf life characteristics and demand characteristics. Contributions are highlighted by discussing main system characteristics, including price discounts, backordering or lost sales, single or multiple items, one or two warehouses, single or multi-echelon, average cost or discounted cash flow, and payment delay.

Inventory models with lateral transshipments: A review

Lateral transshipments within an inventory system are stock movements between locations of the same echelon. These transshipments can be conducted periodically at predetermined points in time to proactively redistribute stock, or they can be used reactively as a method of meeting demand which cannot be satisfied from stock on hand. The elements of an inventory system considered, e.g. size, cost structures and service level definition, all influence the best method of transshipping. Models of many different systems have been considered. This paper provides a literature review which categorizes the research to date on lateral transshipments, so that these differences can be understood and gaps within the literature can be identified.

Lot-sizing for inventory systems with product recovery

We study inventory systems with product recovery. Recovered items are as-good-as-new and satisfy the same demands as new items. The demand rate and return fraction are deterministic. The relevant costs are those for ordering recovery lots, for ordering production lots, for holding recoverable items in stock, and for holding new/recovered items in stock. We derive simple formulae that determine the optimal lot sizes for the production/procurement of new items and for the recovery of returned items. These formulae are valid for finite and infinite production rates as well as finite and infinite recovery rates, and therefore more general than those in the literature. Moreover, the method of derivation is easy and insightful.

Optimal core acquisition and remanufacturing policies under uncertain core quality fractions

Cores acquired by a remanufacturer are typically highly variable in quality. Even if the expected fractions of the various quality levels are known, then the exact fractions when acquiring cores are still uncertain. Our model incorporates this uncertainty in determining optimal acquisition decisions by considering multiple quality classes and a multinomial quality distribution for an acquired lot. We derive optimal acquisition and remanufacturing policies for both deterministic and uncertain demand. For deterministic demand, we derive a simple closed-form expression for the total expected cost. In a numerical experiment, we highlight the effect of uncertainty in quality fractions on the optimal number of acquired cores and show that the cost error of ignoring uncertainty can be significant. For uncertain demand, we derive optimal newsboy-type solutions for the optimal remanufacture-up-to levels and an approximate expression for the total expected cost given the number of acquired cores. In a further numerical experiment, we explore the effects of demand uncertainty on the optimal acquisition and remanufacturing decisions, and on the total expected cost.

Dynamic lot sizing with product returns and remanufacturing

We address the dynamic lot sizing problem for systems with product returns. The demand and return amounts are deterministic over the finite planning horizon. Demands can be satisfied by manufactured new items, but also by remanufactured returned items. The objective is to determine those lot sizes for manufacturing and remanufacturing that minimize the total cost composed of holding cost for returns and (re)manufactured products and set-up costs. Two different set-up cost schemes are considered: there is either a joint set-up cost for manufacturing and remanufacturing (single production line) or separate set-up costs (dedicated production lines). For the joint set-up cost case, we present an exact, polynomial-time dynamic programming algorithm. For both cases, we suggest modifications of the well-known Silver Meal (SM), Least Unit Cost (LUC) and Part Period Balancing (PPB) heuristics. An extensive numerical study reveals a number of insights. The key ones are that, under both set-up cost schemes: (1) the SM and LUC heuristics perform much better than PPB, (2) increased variation in the demand amounts can lead to reduced cost, showing that predictability is more important than variation, and (3) periods with more returns than demand should, if possible, be avoided by ‘matching’ demand and return.

The newsboy problem with resalable returns: a single period model and case study

We analyze a newsboy problem with resalable returns. A single order is placed before the selling season starts. Purchased products may be returned by the customer for a full refund within a certain time interval. Returned products are resalable, provided they arrive back before the end of the season and are undamaged. Products remaining at the end of the season are salvaged. All demands not met directly are lost. We derive a simple closed-form equation that determines the optimal order quantity given the demand distribution, the probability that a sold product is returned, and all relevant revenues and costs. We illustrate its use with real data from a large catalogue/internet mail order retailer.

On the necessity of a disposal option for returned items that can be remanufactured

We study a single item hybrid production system with manufacturing and remanufacturing. It is assumed that remanufacturing is profitable and that, on average, there are more demands than returns. We investigate using simulation, for a variety of cases with different demand, return, manufacturing, and remanufacturing characteristics, what the cost reduction associated with having a disposal option for returned items is. The results show that there is only a considerable cost reduction if an item is very slow-moving, the recovery rate is high, and remanufacturing is almost as expensive as manufacturing.

How to set the holding cost rates in average cost inventory models with reverse logistics

Among both inventory theorists and practitioners, it is common use to include an opportunity cost rate in the holding cost rate. In that way, the cost of capital can be roughly incorporated in an average cost (AC) inventory model. The traditional way for calculating the opportunity cost rate is to multiply the interest rate (or discount rate) by the marginal cost for producing/ordering an item. For single source inventory systems with only forward logistics, this method is easy to use, and leads to near-optimal policies from a discounted cash flow (DCF) point of view. For inventory systems with reverse logistics, however, the method is no longer straightforward. In this paper we compare different methods for calculating the opportunity cost rates of returned non-serviceable, remanufactured, and manufactured items. We discuss which method gives the best results for a specific reverse logistics model with setup costs, non-zero lead times, and disposal.

Forecasting intermittent demand: a comparative study

Methods for forecasting intermittent demand are compared using a large data set from the UK Royal Air Force. Several important results are found. First, we show that the traditional per period forecast error measures are not appropriate for intermittent demand, even though they are consistently used in the literature. Second, by comparing the ability to approximate target service levels and stock holding implications, we show that Crostons method (and a variant) and Bootstrapping clearly outperform Moving Average and Single Exponential Smoothing. Third, we show that the performance of Croston and Bootstrapping can be significantly improved by taking into account that an order in a period is triggered by a demand in that period.