Recoverable Items Research Articles

Bi-objective stochastic closed-loop supply chain network design under uncertain quantity and quality of returns

In this paper, we seek to optimize closed loop supply chain (CLSC) network design by determining the location of distribution and collection facilities and the assignment of forward and reverse flows that maximize the system profit and minimize CO2 emissions. To account for the difficulty of predicting and controlling recoverable items in practice, we incorporate into the proposed bi-objective model three types of uncertainties: return quantity, return quality and remanufacturing costs. We use the ε-constraint method to solve the resulting bi-objective scenario-based two-stage stochastic program and generate a set of Pareto-optimal solutions. Our numerical experiments show that both network configuration and performance levels are sensitive to variations of the quality and quantity of returns, in particular when the penalty for not processing returns is high. They also reveal the importance of stochastic modelling since the value of the stochastic solution can be significant in many cases. However, by increasing the size of the problem, the runtime of the ε-constrained stochastic model can be dramatically increased and memory shortage issues may occur. Therefore, we investigate the computational performance of a metaheuristic method based on a non-dominated sorting genetic algorithm (NSGAII) and a linear programming (LP) relaxation. Our method is capable of approximating the Pareto frontier on instances where the ε-constraint method cannot provide any feasible solution within the same time limit.

Re-ordering policies for inventory systems with recyclable items and stochastic demand – Outsourcing vs. in-house recycling

Investing in recoverable items is an increasing trend in a variety of manufacturing industries. Such industries seek to balance their supply chain costs while reducing solid waste (non-biodegradable). Our work develops mathematical models of inventory systems that rely on newly manufactured and recoverable items to satisfy market demand. Specifically, we consider continuous (r, Q) re-ordering policies for single-item inventory systems with stochastic demand and recycling. The first model assumes outsourcing the recovery of used items to a supplier, where returns (collected used items) arrive in random quantities with every order. The second model assumes performing the recovery process in-house; i.e., at the manufacturer's facility. The proposed mathematical framework considers an infinite time horizon where demand and the amount recovered are stochastic. This work focuses on developing environmentally responsible inventory policies/models that could help in greening supply chains. It also presents a numerical study to compare the proposed models and quantify the trade-off cost between the two; i.e., should the recovery process be in-house or outsourced.

Inventory model optimisation for a closed-loop retailer-manufacturer-supplier system with imperfect production, reworks and quality dependent return rate

This study investigates a closed-loop supply chain (CLSC) inventory model consisting of a retailer, a manufacturer and a supplier. Here, the return rate is considered to be varied which depends upon the quality level of returned items. The manufacturer performs manufacturing and remanufacturing processes to satisfy the retailer's demand. The manufacturing process is assumed to be imperfect and produces some defective items. All defective items are then reworked. Two recovery processes are considered in the model, which are remanufacturing and refurbishing. The recoverable items which cannot be perfectly recovered will be categorised as refurbishable items and then sold to the secondary market at a reduced price. A solution methodology is provided to find the optimal solutions of the model. A numerical example and sensitivity analysis are performed to show the application of the model and to understand the effects of the changes in key parameters on the model's behaviour, respectively.

Inventory model optimisation for a closed-loop retailer-manufacturer-supplier system with imperfect production, reworks and quality dependent return rate

This study investigates a closed-loop supply chain (CLSC) inventory model consisting of a retailer, a manufacturer and a supplier. Here, the return rate is considered to be varied which depends upon the quality level of returned items. The manufacturer performs manufacturing and remanufacturing processes to satisfy the retailer's demand. The manufacturing process is assumed to be imperfect and produces some defective items. All defective items are then reworked. Two recovery processes are considered in the model, which are remanufacturing and refurbishing. The recoverable items which cannot be perfectly recovered will be categorised as refurbishable items and then sold to the secondary market at a reduced price. A solution methodology is provided to find the optimal solutions of the model. A numerical example and sensitivity analysis are performed to show the application of the model and to understand the effects of the changes in key parameters on the model's behaviour, respectively.

Lot sizing decisions in a closed-loop supply chain system with remanufacturing

We propose a closed-loop supply chain model consisting of a supplier, a manufacturer and a retailer under deterministic demand and quality dependent return rate. The manufacturer performs all of the operations regarding used/returned item management, including collection, inspection, sorting, recovery, and also waste disposal. The retailer's demand is fulfilled either by newly manufactured items or by remanufactured items. Two recovery processes are considered in the model, which are remanufacturing and refurbishing. The recoverable items which cannot be recovered as-good-as-new-one will be classified as refurbishable items and then sold to the secondary market at a lower price. We use multiple remanufacturing cycle and multiple production cycle policy to develop the proposed model. An iterative procedure is proposed to determine the optimal solutions. A numerical example is then presented for illustrative purpose and a sensitivity analysis is performed to show the effects of the changes in key parameters on the model's behaviour. The results from sensitivity analysis show that the optimal value of each decision variables is influenced by the demand and raw material buying price, while the joint profit is influenced by the demand, customer purchasing price, and the regular production cost.

Lot sizing decisions in a closed-loop supply chain system with remanufacturing

We propose a closed-loop supply chain model consisting of a supplier, a manufacturer and a retailer under deterministic demand and quality dependent return rate. The manufacturer performs all of the operations regarding used/returned item management, including collection, inspection, sorting, recovery, and also waste disposal. The retailer's demand is fulfilled either by newly manufactured items or by remanufactured items. Two recovery processes are considered in the model, which are remanufacturing and refurbishing. The recoverable items which cannot be recovered as-good-as-new-one will be classified as refurbishable items and then sold to the secondary market at a lower price. We use multiple remanufacturing cycle and multiple production cycle policy to develop the proposed model. An iterative procedure is proposed to determine the optimal solutions. A numerical example is then presented for illustrative purpose and a sensitivity analysis is performed to show the effects of the changes in key parameters on the model's behaviour. The results from sensitivity analysis show that the optimal value of each decision variables is influenced by the demand and raw material buying price, while the joint profit is influenced by the demand, customer purchasing price, and the regular production cost.

Integrated inventory control with recovery and disposal

This paper deals with a cooperative process between the vendor and the buyer in an integrated production inventory model. The buyer inspects all the arriving items and returns all of the defective items to the vendor. The vendor recycles every defective item; all recoverable items are repaired and then sold to the third-party buyers. In this paper, the first scenario discussed, the vendor has a superior bargaining power over the buyer, and in the second, the buyer has a better bargaining power. For each scenario, a method is used for finding an optimal strategy. Furthermore, in the leader–follower cooperative game, we develop three algorithmic procedures to find the minimum expected annual total cost for each model. Simultaneously, we optimise the order quantity of the buyer, the length of lead time of the buyer, the size of shipments from the vendor to the buyer and the numbers of shipments per production run from the vendor to the buyer for this integrated inventory model. Finally, the expected annual total costs of the models are compared to determine the managerial implications of results.

Opportunities and Barriers to Resource Recovery and Recycling from Shredder Residue in the United States

Shredder residue is the by-product remaining after ferrous and nonferrous metals have been recovered from the processing of vehicles, white goods, and peddler scrap. Shredder residue consists of glass, plastics, rubber, dirt, and small amounts of metal. It is estimated that 5–7 million tons of this shredder residue are landfilled each year in the United States. Technical advancements, coupled with European Union directives and the economic climate, have transformed the recycling of shredder residue in Europe. In the United States, however, regulatory controls and the cheap cost of landfill have worked against the advancement of recycling and recovery of this resource. The Argonne National Laboratory, which is funded by the U.S. Department of Energy, has investigated the effectiveness of recycling shredder residue into polymers. Other research has examined the use of shredder residue in waste-to-energy applications. To improve our ability to process and recycle shredder residue, an investigation of the regulatory, economic, and technological challenges was undertaken. The objective was to conduct a comprehensive review of work done to date, to document the composition of typical shredder output and to identify potential recoverable items (residual metals, plastics, rubber, foam, etc.). Along with uncovering potential new markets, the research would identify the technical, regulatory, and economic barriers to developing those markets.

Optimal control of production and remanufacturing for a recovery system with perishable items

In this paper, a recovery system for perishable items is introduced and developed considering production and remanufacturing capacity constraints. The system consists of two inventories, one for serviceable items and the other for returned and recoverable items. Taking the production cost, remanufacturing cost, disposal cost, and the loss caused by deterioration into account, the optimal control model is established to minimise the total cost. The continuous-time dynamic optimal production, remanufacturing and disposal rates that minimise the total cost are obtained using Pontryagin’s maximum principle. Additionally, to highlight the advantage of the dynamic optimal policy, the case of the static optimal policy that does not vary with time is investigated and compared with the dynamic policy. It is shown that the dynamic optimal policy is significantly better than the static optimal policy. A numerical example is provided to illustrate the proposed methods.

Optimal Acquisition and Inventory Control for a Remanufacturing System

Optimal acquisition and inventory control can often make the difference between successful and unsuccessful remanufacturing. However, there is a greater degree of uncertainty and complexity in a remanufacturing system, which leads to a critical need for planning and control models designed to deal with this added uncertainty and complexity. In this paper, a method for optimal acquisition and inventory control of a remanufacturing system is presented. The method considers three inventories, one for returned item and the other for serviceable and recoverable items. Taking the holding cost for returns, recoverable and remanufactured products, remanufacturing cost, disposal cost, and the loss caused by backlog into account, the optimal inventory control model is established to minimize the total costs. Finally, a numerical example is provided to illustrate the proposed methods.

An optimal policy for recovery and procurement under multiple setups

This paper attempts to find the economic ordering quantity (EOQ) and economic procurement quantity (EPQ) for a system in which the demand can be satisfied by a combination of newly purchased products and recovered, used products. Used products are collected from customers and then they undergo recovery processes. These recovered products are regarded as perfectly new ones. The model developed here considers a realistic case, where there can be multiple setups for both recoveries and procurements. We study cases where production/procurement rate is finite and infinite. We obtain the EOQ for newly procured products and the optimal inventory level of recoverable items to start the recovery process simultaneously. The total cost equation is found to be the function of the inventory level of recoverable items to start recovery and the ratio of orders for newly procured items to setups. Then, a search procedure to find the optimal control parameters is presented. The models have been validated with illustrating numerical examples and sensitivity analysis.

Lot sizing for a recoverable product with inspection and sorting

This paper studies an inventory system where demand is satisfied by recovered and new purchased items. Used units of a product, returned by (or collected from) customers, are kept in recoverable inventory until the start of a combined process of inspection and recovery. Recovered (remanufactured) items are assumed to be as-good-as new. However, some recovered items do not qualify to be classified as “remanufactured” and are perceived by customers to be of secondary quality. These refurbished items are sold to a secondary market at a reduced price. A simple formula that determines the optimal inventory level of recoverable (used) items is developed to be able to start the inspection and recovery processes and the economic order quantity for procurement. According to the relationships among the parameters, this paper proposes and analyzes models that describe the system of interest, which are considered extensions of the work of Koh, Hwang and Sohn [Computers and Industrial Engineering 43(1–2), 59–73, 2002].

Economic evaluation of disassembly processes in remanufacturing systems

A model to deal with the disassembly processes in remanufacturing systems is presented with focus being on evaluating their economic consequences. More specifically, the model assists decisions such as to which degree and for the sake of which components should the returned items be disassembled. Consequently, using the economic values of recoverable items, the inventory holding costs of these items are obtained. This information is further used to determine the inventory control policy. To access such economic values, the above average cost approach is compared with the net present value method. The latter is often considered a more ‘correct’ way in remanufacturing systems from the viewpoint of inventory control. The results from the economic evaluation model are intended to aid companies in systematically evaluating current as well as projected remanufacturing systems.

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 control of a one product recovery system with leadtimes

In this paper a recovery system for a single product is investigated. Besides a remanufacturing and a manufacturing facility the system consists of one inventory for returned and recoverable items and one for serviceable items. Demands are satisfied from serviceable inventory, which can be replenished by remanufactured returned items, which are as good as new, or by new produced items. Additionally, there is the possibility of disposing of returned items. We determine the cost optimal manufacturing, remanufacturing and disposal rates for the system under the assumptions of a linear cost structure, a finite planning horizon and deterministic and dynamic demand and return rates. Thereby we study two classes of policies, one where backorders are forbidden and another one where they are allowed. In contrast to the existing literature positive leadtimes are considered.

An optimal ordering and recovery policy for reusable items

This paper deals with a joint EOQ and EPQ model in which the stationary demand can be satisfied by recycled products and newly purchased products. The model assumes that a fixed proportion of the used products are collected from customers and later recovered for reuse. The recovered products are regarded as perfectly new ones. We obtain (i) the economic order quantity for newly procured products and (ii) the optimal inventory level of recoverable items to start the recovery process, simultaneously. According to the relationship between parameters, we propose some numerical models to analyze the system. Then a solution procedure to find the optimal control parameters is presented, and finally some numerical examples are given to illustrate the model.

Optimal control of a one product recovery system with backlogging

In this paper a product recovery system for one product is investigated. The system contains one inventory for returned and recoverable items and one for serviceable items. Demands are satisfied from serviceable inventory where backlogging of demands is allowed. In addition, there is the possibility of disposal for the returned products. We assume deterministic but dynamic return and demand rates and a linear cost structure. The Pontryagin maximum principle is used to determine the optimal production, remanufacturing and disposal policy.

Replenishment policies for inventories of recoverable items with attrition

Optimal ( s, S) replenishment policies are determined for inventories of recoverable items in which an item occasionally is lost or must be discarded. Two types of recoverable items are considered: rental items and repairable spares. The objective is to minimize total expected order, holding, repair and shortage costs per unit of time. A discrete time Markov chain yields steady-state probabilities for the number of items in the system. Total cost functions are developed for two types of resupply time: immediate and deterministic. Examples are included to illustrate the sensitivity of the optimal ( s, S) policies to parameter changes.

OPTIMAL ALLOCATION OF RECOVERABLE ITEMS*

ABSTRACTAllocation of at most n recoverable items among m demand locations is considered. Items are assumed to be demanded singly and independently and are eventually returned to the demand location. If a stockout occurs, the demand is lost and a penalty corresponding to lost profit is assessed. The allocation that minimizes the sum of expected stockout costs plus holding costs is readily obtained. An example involving allocation of rental cars among outlets is solved in detail.

Exact analysis of a two‐echelon inventory system for recoverable items under batch inspection policy

AbstractWe investigate a two‐echelon (base‐depot) inventory system of recoverable (repairable) items. The arrivals of demand at the bases are in a Poisson manner and the order sizes are random. The failed units can be repaired either at the base or at the depot, and the units beyond economic repair are condemned. Inspection of the failed units is carried out in the batches they arrive, that is, arrival batches are not broken up. The exact expressions for stationary distribution of depot inventory position, and of the number of backorders, onhand inventory, in‐repair inventory at all locations are derived under the assumptions of constant repair and lead times. Special cases of complete recoverability, nonrecoverability, and of the unit order size are also discussed.