A robust optimisation model for hybrid remanufacturing and manufacturing systems under uncertain return quality and market demand

In remanufacturing research, most researchers predominantly emphasised on the recovery of whole product (core) rather than at the component level due to its complexity. In contrast, this paper addresses the challenges to focus on remanufacturing through component recovery, so as to solve production planning problems of hybrid remanufacturing and manufacturing systems. To deal with the uncertainties of quality and quantity of product returns, the processing time of remanufacturing, remanufacturing costs, as well as market demands, a robust optimisation model was developed in this research and a case study was used to evaluate its effectiveness and efficiency. To strengthen this research, a sensitivity analysis of the uncertain parameters and the original equipment manufacturer’s (OEM’s) pricing strategy was also conducted. The research finding shows that the market demand volatility leads to a significant increase in the under fulfilment and a reduction in OEM’s profit. On the other hand, recovery cost reduction, as endogenous cost saving, encourages the OEM to produce more remanufactured products with the increase in market demand. Furthermore, the OEM may risk profit loss if they raise the price of new products, and inversely, they could gain more if the price of remanufactured products is raised

Two-Period Inventory Control with Manufacturing and Remanufacturing under Return Compensation Policy

As an effective way of decreasing production cost, remanufacturing has attracted more and more attention from firms. However, it also brings many difficulties to firms, especial when firms remanufacture products which they produce. A primary problem for the case is how to acquire the used product sold by the firm itself. In this paper, we consider a return compensation policy for acquiring used product from customers. Under this policy, the return quantity of used product is a proportion of demand. We study an inventory replenishment and production planning problem for a two-period inventory system with dependent return and demand. We formulate the problem into a three-stage stochastic programming problem, where the firm needs to make decisions on the replenishment quantity of new raw material inventory in each period and the production quantities of manufacturing and remanufacturing ways. We give the optimal production policy of manufacturing and remanufacturing ways for the realized demand and prove the objective function for each stage to be concave in the inventory replenishment quantity. Moreover, we prove that the basic inventory policy is still optimal for each period and give the analytical conditions of the optimal inventory levels which are unrelated to acquisition price. Finally, we investigate numerical studies to analyze managerial insights

A replenishment control system with uncertain returns and random opportunities for disposal

We consider a replenishment control system in which product returns play an important role in inventory planning. We focus on the inventory of an individual item that is stored at a single location to meet a constant demand over time. We assume that the total amount of returns accumulated over a period of time can be represented by a compound Poisson process. We further assume that opportunities for inventory disposals or relocation arise occasionally in accordance with a Poisson process. We not only seek to resolve the issues of when to order and how much to order, we also consider the question of when to dispose of excess inventory and by how much. Inventory reductions occur when the opportunity for a disposal arises and the inventory position is deemed too high. After each disposal the inventory position is restored to a specified base-stock level. We develop a cost model of this system and highlight its properties through an extensive numerical study

Performance Evaluation of Stochastic Multi-Echelon Inventory Systems: A Survey

Globalization, product proliferation, and fast product innovation have significantly increased the complexities of supply chains in many industries. One of the most important advancements of supply chain management in recent years is the development of models and methodologies for controlling inventory in general supply networks under uncertainty and their widefspread applications to industry. These developments are based on three generic methods: the queueing-inventory method, the lead-time demand method and the flow-unit method. In this paper, we compare and contrast these methods by discussing their strengths and weaknesses, their differences and connections, and showing how to apply them systematically to characterize and evaluate various supply networks with different supply processes, inventory policies, and demand processes. Our objective is to forge links among research strands on different methods and various network topologies so as to develop unified methodologies.Masdar Institute of Science and TechnologyNational Science Foundation (U.S.) (NSF Contract CMMI-0758069)National Science Foundation (U.S.) (Career Award CMMI-0747779)Bayer Business ServicesSAP A

Aerospace Manufacturing-Remanufacturing System Modeling and Optimization

In recent years, increasing environmental concerns, costs of raw materials, and stricter government regulations have resulted in companies striving to reduce their waste materials. An earlier approach adopted was the recycling of materials such as waste paper, glass and metals. However, recycled products typically lose a portion of their added values. Different waste reduction options such as direct reuse, repair, refurbishing, cannibalization, and remanufacturing were studied to overcome this drawback. Remanufacture recaptures the value added to materials when a product was first manufactured. In the aerospace industry, where safety and performance are the overriding concerns and repairs are highly regulated, it could be perceived that remanufacturing has minimal appeal. However, the very low design tolerance of manufactured components results in a high percentage of defects. Due to the high price of raw materials, remanufacturing and components saving through “transforming” could be applied in imperfect production systems to reduce the amount of scrap materials. In this thesis, a general model is first proposed for a closed-loop supply chain network which includes the following processes: repairs, remanufacturing and transforming of selected defective components and end-of-life products, and cannibalization. A mixed integer linear programming formulation is developed to investigate the effect of various factors on profit, inventory carrying cost, and number of scrap components. Uncertainty in demand and lead-time is one of the major issues in any manufacturing supply chain. Uncertainty is incorporated into an extended model through the scenario-analysis approach and outsourcing is considered as an option for remanufacturing of the customer owned components. Demand of final products is assumed to be deterministic. The defect rate of disassembled components, however, is considered to be variable which makes the demand for spares to be variable. The lead-time of in-house remanufacturing of the customer owned components is also considered to be variable. Sensitivity analysis is performed to investigate the effect of capacity, inventory carrying cost, outsourcing cost, lead-time, and defect rate variation on profit and amount of scraps. The inventory carrying cost variations have direct effect on the inventory turnover ratio. The maximum capacity of the outsourced company and process costs per unit have significant effect on the profitability. Maintaining a long-term relationship with third-party service providers, designing the components with a longer life cycle, and transforming and remanufacturing of defective components directly impact the profitability over the life cycle of a product

Inventory Management for an Assembly System with Product or Component Returns

This paper considers an inventory system with an assembly structure. In addition to uncertain customer demands, the system experiences uncertain returns from customers. Some of the components in the returned products can be recovered and reused, and these units are returned to inventory. Returns complicate the structure of the system, so that the standard approach (based on reduction to an equivalent series system) no longer applies in general. We identify conditions on the item-recovery pattern and restrictions on the inventory policy under which an equivalent series system does exist. For the special case where only the end product (or all items used to assemble the end product) is recovered, we show that the system is equivalent to a series system with no policy restrictions. For the general case, we explain how and why the system becomes more problematic and propose two heuristic policies. The heuristics are easy to compute and practical to implement, and they perform well in numerical trials. Based on these numerical trials, we obtain insights into the impact of various factors on system performance. For example, we find that holding and backorder costs tend to increase when the average return rate, the variability of returns, or the number of components recovered increases. However, neither the product architecture nor the specific set of components being recovered seems to have a significant impact on these costs. Whether product recovery reduces total system costs depends on the magnitude of the additional holding and backorder costs relative to potential procurement cost savings.assembly systems, inventory policies, reverse logistics, remanufacturing, environment

Integrated Forward and Reverse Logistics Network Design

Many manufacturers are moving towards green manufacturing. One of the actions for environment friendly manufacturing is collection of end-of-life products (EOL). EOL products are transported to the proper facilities for reprocessing or proper disposal. Movement of collected products is performed through reverse logistics networks. Reverse logistics networks may be designed independent of forward logistics networks, or as integrated networks, known as integrated forward and reverse logistics (IFRL) networks. Recent research shows that IFRL networks are more efficient than independent networks. In this work, we study a number of IFRL networks. We present a comprehensive mathematical model to represent an assignment and location-routing IFRL network. Afterwards, this model is decomposed into a number of sub-models that represent different IFRL networks. For each network we develop a solution methodology to solve practical size problems. Two sub-models based on the comprehensive model are presented to design two IFRL location-routing networks. The first network considers decision on the location to establish a disassembly plant. The second network considers decisions on the location to establish a manufacturing facility. For both networks, routing decisions are assigning customers to vehicles, and establishing vehicles’ routes. We develop two heuristic methods to solve the models. The heuristics are able to reach optimal or near optimal solutions in reasonable computational times. The vehicle routing problem with simultaneous pickup and delivery and time windows (VRPSPD-TW) is studied in this work. We use a sub-model of the comprehensive model to represent the problem. Classic heuristics and intelligent optimization or metaheuristics are widely used to solve similar problems. Therefore, we develop a heuristic method to solve the VRPSPD-TW. Results of the heuristic serve as initial solutions for a simulated annealing (SA) approach. For most tested problems, the SA approach is able to improve the heuristic solutions, and reach optimal solutions. Computational times are reasonable for the heuristic and SA. We also study the multi-depot vehicle routing problem with simultaneous pickup and delivery and time windows (MDVRPSPS-TW). A sub-model of the comprehensive model represents the problem. The network considers assignment of customers and vehicles to depots, assignment of customers to vehicles and routing of vehicles within customers’ time windows. We develop a 2-phase heuristic and a SA approach to solve the problem. Heuristic solutions serve as initial solutions for the SA approach. SA is able to reach optimum or near optimum solutions. Computational times are reasonable for the heuristic and S

Gestion des stocks et de la production intégrant des retours de produits

De nombreux retours de produits dus au recyclage et à la réutilisation des déchets se développent dans le but de préserver les ressources naturelles limitées de notre planète. Ces nouveaux flux interagissant avec les flux de production traditionnels, il est important de les piloter de façon à satisfaire au mieux les demandes des clients et minimiser l'encours dans la chaîne logistique. Nos travaux s'inscrivent dans cette démarche. Nous nous plaçons dans un contexte où la capacité de production est limitée et nous considérons un problème opérationnel de gestion des stocks et de la production intégrant des flux de retours. Nous modélisons trois problèmes de production et de stockage à temps continu, avec des capacités de production limitées, des délais aléatoires et des coûts linéaires. Le premier prenant en compte la probabilité qu'un produit puisse être réutilisé comme produit fini ou seulement comme produit semi-fini (par partie), le deuxième présentant un problème où la réutilisation d'un retour comme produit fini nécessite une étape de remise à neuf et le troisième modélisant un système où les clients préviennent à l'avance du renvoi potentiel de leurs produits. Outre la caractérisation des politiques optimales de gestion, une part importante de nos contributions réside dans l'évaluation des performances de différentes politiques heuristiques et l'étude de l'impact de la capacité de production sur celles-ci. Enfin, nous nous servons dans tout ce document d'outils permettant la caractérisation des politiques optimales. La dernière partie de ce document vise à développer ces outils et à permettre l'étude de l'effet des paramètres d'un système formulé en processus de décision Markovien sur la politique optimale de celui-ci.Flows of returns due to recycling and reusing waste are developing in order to preserve the limited natural resources of our planet. These new flows interact with the traditional production flows. Therefore, in order to provide customers with the best service level and minimize the stock in the supply chain, the control of the return flows appears to be of highest importance. We address this problem by modeling a situation with a limited porduction capacity and we consider an operational production/inventory problem that incorporates flows of returns. We model three continuous-time production/inventory problems with limited produc- tion capacities, random lead times, and linear costs. In the first problem we take into account the probability that a product can be reused as a finished product or only as semi-finished product (by parts), in the second problem we include a step of remanufac- turing before reusing the returned product, and in the third problem we consider a system with product returns that are announced in advance by the customers. Apart from the caracterization of the optimal policies for these cases, the performance assessments of some heuristic policies and the study of the poduction capacity effect on these heuristic policies stand as main contributions. Throughout this work we have used existing tools to characterize optimal policies for different Markov decision processes. The last chapter aims to improve these tools and enable us to study the influence of several system parameters on its optimal policy.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF