Optimal and predefined policies for the static lot sizing problem in a two stage recovery system

Analyzing static lot sizing problems has always attracted a considerable interest in scientific literature. A commonly applied methodology to solve the trade-off between setup and holding costs is to order the Economic Order Quantity (EOQ) whenever the corresponding inventory is depleted. Yet, this simple proceeding can only be applied as long as there is only a single source of supply. Recovery systems, however, obtain in general two sources of supply, remanufacturing product returns and fabricating new products. Therefore, a more sophisticated approach needs to be taken into account for this kind of problem setting. This contribution focusses on extending the current knowledge in this field of research by showing that non-equal remanufacturing batches propose a significant cost reduction for some parameter classes. Furthermore, a more general optimization approach is introduced that allows to evaluate the solution quality of the preset policy structures

Production planning and control of closed-loop supply chains

More and more supply chains emerge that include a return flow of materials. Many original equipment manufacturers are nowadays engaged in the remanufacturing business. In many process industries, production defectives and by-products are reworked. These closed-loop supply chains deserve special attention. Production planning and control in such hybrid systems is a real challenge, especially due to increased uncertainties. Even companies that are engaged in remanufacturing operations only, face more complicated planning situations than traditional manufacturing companies.We point out the main complicating characteristics in closed-loop systems with both remanufacturing and rework, and indicated the need for new or modified/extended production planning and control approaches. An overview of the existing scientific contributions is given. It appears that we only stand at the beginning of this line of research, and that many more contributions are needed and expected in the future.closed-loop supply chains;Production planning and control

Performance evaluation of the remanufacturing system prone to random failure and repair

Implementation of new environmental legislation and public awareness has increased the responsibility of manufacturers. Remanufacturing has been applied in many industries and sectors since its introduction. However, only 10% to 20% of the returned products pass through the remanufacturing process, and the remaining products are disposed in the landfills. Uncertainties like high failure rates of the servers, buffer capacities, and inappropriate preventive maintenance policies would be responsible for most of the delays in remanufacturing operations. In this paper, a simulation-based experimental methodology is used to determine the optimal preventive maintenance frequency and buffer allocation in a remanufacturing line. Moreover, an estimated relationship between preventive maintenance frequency and Mean Time Between Failure (MTBF), is presented to determine the best preventive maintenance frequency. The solution approach is applied to computer remanufacturing industry. Analysis of variance (ANOVA), and regression analysis are performed to denote the most influential factors to remanufacturing cycle time (performance measures). A case study is used to show the applicability of the modelling approach in assessing and improving the cycle time, and the profit of a remanufacturing line . Managerial insights are highlighted to support managers and decision-makers in their quest for more efficient and smooth operation of the remanufacturing system

Production planning and control of closed-loop supply chains

More and more supply chains emerge that include a return flow of materials. Many original equipment manufacturers are nowadays engaged in the remanufacturing business. In many process industries, production defectives and by-products are reworked. These closed-loop supply chains deserve special attention. Production planning and control in such hybrid systems is a real challenge, especially due to increased uncertainties. Even companies that are engaged in remanufacturing operations only, face more complicated planning situations than traditional manufacturing companies. We point out the main complicating characteristics in closed-loop systems with both remanufacturing and rework, and indicated the need for new or modified/extended production planning and control approaches. An overview of the existing scientific contributions is given. It appears that we only stand at the beginning of this line of research, and that many more contributions are needed and expected in the future

A systematic review of decision-making in remanufacturing

Potential benefits have made remanufacturing attractive over the last decade. Nevertheless, the complexity and uncertainties associated with the process of managing returned products make remanufacturing challenging. Since this process involves enormous decision-making practices, various methods/techniques have been developed. This review is to specify the current challenges and opportunities for decision-making in remanufacturing. To achieve this, we perform a systematic review over decision-making in remanufacturing by classifying decisions into different managerial levels and areas. Adopting a systematic approach which provides a repeatable, transparent and scientific process, 241 key articles have been identified following a multi-stage review process. Our review indicates that most studies focuses on strategic-level(48%) and tactical-level (34%)with only 5% focusing on operational-level and the rest on two levels(13%). Regarding decision-making methods, most studies propose mathematical models (60%) followed by analytical models (31%). Furthermore, only 36% of the studies address uncertainties in which stochastic approach is mostly applied. A total of 21 knowledge gaps are highlighted to direct future research work

Inventory management in a manufacturing/remanufacturing hybrid system with condition monitoring

Traditional supply chains consist of manufacturers, who process, assemble and sell products to customers. Once the product has been sold, the ownership of the product is transferred on to the customer. Typically after a possible warranty period, the repair, maintenance and eventual disposal of the product is then the responsibility of the customer. The reverse processing activities of inspection, parts remanufacturing, and materials recycling can substantially reduce the material and energy consumed by producing goods. Although these activities have a beneficial environmental impact, customers fail to participate in the remanufacturing efforts by producers or third parties because they often lack incentives. To overcome this drawback, several environmental and economic thinkers have proposed a concept called servicizing . In this paradigm, producers become service providers who provide the use and maintenance of products while retaining ownership; customers become clients who pay fees to receive the benefits the products provide. Instead of extensive buying and disposing of products, servicizing includes the obligation to dispose of used products responsibly, while reusing them and their constituent parts and materials as much as possible. However, because the provider retains responsibility for the product while it is in use by different client firms, the service paradigm also creates the need for better information and communication technology to increase the provider\u27s knowledge of the product condition. Monitoring the condition of the equipment enhances the ability of the service provider to make better replacement decisions (when to replace the product in the fleet to avoid failures) and better inventory management decisions (how much remanufactured stock to maintain so the customer is ensured a working product at all times). This thesis aims at optimizing the replacement and inventory decisions of the service provider in order to minimize the long-run overall cost per unit time

Used product acquisition, sorting and disposition for circular supply chains: Literature review and research directions

The vision of a circular economy (CE) inspires firms, governments, and scholars alike. The transition is underway in both practice and the literature, but success depends on the effective implementation of circular supply chains (CSCs), which encompass acquiring used products, sorting them by type and quality, and deciding which to dispose to various processing options. We review 131 high-impact journal articles on returns acquisition, sorting, and disposition (ASD) over the decade 2012-2021 to assess the current status of ASD research for CSCs and to discuss important research directions for supporting the transition to a CE. Uniquely synthesising the state of the art on all these three overarching decision areas, we find aspects of CSCs prominent in the decade's research agenda, such as closed loop supply chain coordination and ASD for remanufacturing, and highlight growing coverage of behavioural considerations. Research applicability has been constrained by a lack of empirical studies, limited practical validation of mathematical models, a focus on economic objectives, and restrictive modelling assumptions about behaviour and uncertainty in returns. We recommend further research in each part of ASD to facilitate a CSC, and as a whole, for transitioning to a CE. CE concepts such as joint decision-making between product design and returns management, cross-sector collaboration, and product-service systems should inform the agenda for CSC research

Sustainable Inventory Management Model for High-Volume Material with Limited Storage Space under Stochastic Demand and Supply

Inventory management and control has become an important management function, which is vital in ensuring the efficiency and profitability of a company’s operations. Hence, several research studies attempted to develop models to be used to minimise the quantities of excess inventory, in order to reduce their associated costs without compromising both operational efficiency and customers’ needs. The Economic Order Quantity (EOQ) model is one of the most used of these models; however, this model has a number of limiting assumptions, which led to the development of a number of extensions for this model to increase its applicability to the modern-day business environment. Therefore, in this research study, a sustainable inventory management model is developed based on the EOQ concept to optimise the ordering and storage of large-volume inventory, which deteriorates over time, with limited storage space, such as steel, under stochastic demand, supply and backorders. Two control systems were developed and tested in this research study in order to select the most robust system: an open-loop system, based on direct control through which five different time series for each stochastic variable were generated, before an attempt to optimise the average profit was conducted; and a closed-loop system, which uses a neural network, depicting the different business and economic conditions associated with the steel manufacturing industry, to generate the optimal control parameters for each week across the entire planning horizon. A sensitivity analysis proved that the closed-loop neural network control system was more accurate in depicting real-life business conditions, and more robust in optimising the inventory management process for a large-volume, deteriorating item. Moreover, due to its advantages over other techniques, a meta-heuristic Particle Swarm Optimisation (PSO) algorithm was used to solve this model. This model is implemented throughout the research in the case of a steel manufacturing factory under different operational and extreme economic scenarios. As a result of the case study, the developed model proved its robustness and accuracy in managing the inventory of such a unique industry