Efficient inventory control for imperfect quality items

In this paper, we present a general EOQ model for items that are subject to inspection for imperfect quality. Each lot that is delivered to the sorting facility undertakes a 100 per cent screening and the percentage of defective items per lot reduces according to a learning curve. The generality of the model is viewed as important both from an academic and practitioner perspective. The mathematical formulation considers arbitrary functions of time that allow the decision maker to assess the consequences of a diverse range of strategies by employing a single inventory model. A rigorous methodology is utilised to show that the solution is a unique and global optimal and a general step-by-step solution procedure is presented for continuous intra-cycle periodic review applications. The value of the temperature history and flow time through the supply chain is also used to determine an efficient policy. Furthermore, coordination mechanisms that may affect the supplier and the retailer are explored to improve inventory control at both echelons. The paper provides illustrative examples that demonstrate the application of the theoretical model in different settings and lead to the generation of interesting managerial insights

OPTIMAL INBOUND/OUTBOUND PRICING MODEL FOR REMANUFACTURING IN A CLOSED-LOOP SUPPLY CHAIN

The paper presents a model for optimizing inbound and outbound pricing for closed-loop supply chains that remanufacture reusable products. Remanufacturers create reusable products from returned used products and sell the products “as new” to manufacturers or consumers. By implementing a return subsidy, remanufacturers can encourage the consumer to return used products. Demand for the as-new components often depends on the selling price and inventory. The available inventory increases as the subsidy increases and as the price decreases. Our model can determine the optimal subsidy and selling price for used and remanufactured products, respectively. Our model uses the Karush–Kuhn–Tucker conditions to solve its nonlinear problem. Sensitivity analysis reveals how different parameters affect profit under model-optimized conditions

Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model

The classical formulation of a two-warehouse inventory model is often based on the Last-In-First-Out (LIFO) or First-In-First-Out (FIFO) dispatching policy. The LIFO policy relies upon inventory stored in a rented warehouse (RW), with an ample capacity, being consumed first, before depleting inventory of an owned warehouse (OW) that has a limited capacity. Consumption works the other way around for the FIFO policy. In this paper, a new policy entitled “Allocation-In-Fraction-Out (AIFO)” is proposed. Unlike LIFO and FIFO, AIFO implies simultaneous consumption fractions associated with RW and OW. That said, the goods at both warehouses are depleted by the end of the same cycle. This necessitates the introduction of a key performance indicator to trade-off the costs associated with AIFO, LIFO and FIFO. Consequently, three general two-warehouse inventory models for items that are subject to inspection for imperfect quality are developed and compared – each underlying one of the dispatching policies considered. Each sub-replenishment that is delivered to OW and RW incurs a distinct transportation cost and undertakes a 100 per cent screening. The mathematical formulation reflects a diverse range of time-varying forms. The paper provides illustrative examples that analyse the behaviour of deterioration, value of information and perishability in different settings. For perishable products, we demonstrate that LIFO and FIFO may not be the right dispatching policies. Further, relaxing the inherent determinism of the maximum capacity associated with OW, not only produces better results and implies comprehensive learning, but may also suggest outsourcing the inventory holding through vendor managed inventory

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

Supply chain finance for ameliorating and deteriorating products: a systematic literature review

Ameliorating and deteriorating products, or, more generally, items that change value over time, present a high sensitiveness to the surrounding environment (e.g., temperature, humidity, and light intensity). For this reason, they should be properly stored along the supply chain to guarantee the desired quality to the consumers. Specifically, ameliorating items face an increase in value if there are stored for longer periods, which can lead to higher selling price. At the same time, the costumers’ demand is sensitive to the price (i.e., the higher the selling price the lower the final demand), sensitiveness that is related to the quality of the products (i.e., lower sensitiveness for high-quality products). On the contrary, deteriorating items lose quality and value over time which result in revenue losses due to lost sales or reduced selling price. Since these products need to be properly stored (i.e., usually in temperature- and humidity-controlled warehouses) the holding costs, which comprise also the energy costs, may be particularly relevant impacting on the economic, environmental, and social sustainability of the supply chain. Furthermore, due to the recent economic crisis, companies (especially, small and medium enterprises) face payment difficulties of customers and high volatility of resources prices. This increases the risk of insolvency and on the other hand the financing needs. In this context, supply chain finance emerged as a mean for efficiency by coordinating the financial flow and providing a set of financial schemes aiming at optimizing accounts payable and receivable along the supply chain. The aim of the present study is thus to investigate through a systematic literature review the two main themes presented (i.e., inventory management models for products that change value over time, and financial techniques and strategies to support companies in inventory management) to understand if any financial technique has been studied for supporting the management of this class of products and to verify the existing literature gap

A Modified Reverse Supply Chain with Remanufacturing for Sustainable Product Cycle

This paper deals with a new model, in which the stationary demand for a product can be fulfilled by remanufactured products along with newly procured product leading to minimum consumption of virgin raw materials. The remanufactured products are assumed to be as good as new ones and the returned items from the customers can be remanufactured at a fixed rate. The model helps in maintaining the goodwill of the customers by not allowing frequent stock outs by providing safety stock. A model is proposed and analyzed depending on the relationship between different parameters. An interpretive modelling based approach has been employed to model the reverse logistics variables typically found in reverse supply chains. A methodology is used for the calculation of optimum level for the newly manufactured items and the optimum level of the returned items for remanufacturing simultaneously. The major objective is to minimize the waste and gain the competitive advantage of cost of conversion. Moreover the company can sustain in the same line of business for a longer period of time. Keywords Product recovery, remanufacturing, reverse supply chain, sustainable product

A centralized reverse channel structure with flexible manufacturing under the stock out situation

Keeping in view the concern about environmental protection, the study investigates effects of remanufacturing in an integrated production inventory model consisting of forward and reverse supply chain over infinite planning horizon. This article is developed for the deteriorating products with stock dependent demand under shortages. To make the model more realistic, flexibility of production system has been incorporated during forward manufacturing. We derive total cost function and using the results of calculus, optimum production policy is derived, which minimizes the total cost incurred. The results are discussed with a numerical example to illustrate the theory

Responsible Inventory Models for Operation and Logistics Management

The industrialization and the subsequent economic development occurred in the last century have led industrialized societies to pursue increasingly higher economic and financial goals, laying temporarily aside the safeguard of the environment and the defense of human health. However, over the last decade, modern societies have begun to reconsider the importance of social and environmental issues nearby the economic and financial goals. In the real industrial environment as well as in today research activities, new concepts have been introduced, such as sustainable development (SD), green supply chain and ergonomics of the workplace. The notion of “triple bottom line” (3BL) accounting has become increasingly important in industrial management over the last few years (Norman and MacDonald, 2004). The main idea behind the 3BL paradigm is that companies’ ultimate success should not be measured only by the traditional financial results, but also by their ethical and environmental performances. Social and environmental responsibility is essential because a healthy society cannot be achieved and maintained if the population is in poor health. The increasing interest in sustainable development spurs companies and researchers to treat operations management and logistics decisions as a whole by integrating economic, environmental, and social goals (Bouchery et al., 2012). Because of the wideness of the field under consideration, this Ph.D. thesis focuses on a restricted selection of topics, that is Inventory Management and in particular the Lot Sizing problem. The lot sizing problem is undoubtedly one of the most traditional operations management interests, so much so that the first research about lot sizing has been faced more than one century ago (Harris, 1913). The main objectives of this thesis are listed below: 1) The study and the detailed analysis of the existing literature concerning Inventory Management and Lot Sizing, supporting the management of production and logistics activities. In particular, this thesis aims to highlight the different factors and decision-making approaches behind the existing models in the literature. Moreover, it develops a conceptual framework identifying the associated sub-problems, the decision variables and the sources of sustainable achievement in the logistics decisions. The last part of the literature analysis outlines the requirements for future researches. 2) The development of new computational models supporting the Inventory Management and Sustainable Lot Sizing. As a result, an integrated methodological procedure has been developed by making a complete mathematical modeling of the Sustainable Lot Sizing problem. Such a method has been properly validated with data derived from real cases. 3) Understanding and applying the multi-objective optimization techniques, in order to analyze the economic, environmental and social impacts derived from choices concerning the supply, transport and management of incoming materials to a production system. 4) The analysis of the feasibility and convenience of governmental systems of incentives to promote the reduction of emissions owing to the procurement and storage of purchasing materials. A new method based on the multi-objective theory is presented by applying the models developed and by conducting a sensitivity analysis. This method is able to quantify the effectiveness of carbon reduction incentives on varying the input parameters of the problem. 5) Extending the method developed in the first part of the research for the “Single-buyer” case in a "multi-buyer" optics, by introducing the possibility of Horizontal Cooperation. A kind of cooperation among companies in different stages of the purchasing and transportation of raw materials and components on a global scale is the Haulage Sharing approach which is here taken into consideration in depth. This research was supported by a fruitful collaboration with Prof. Robert W. Grubbström (University of Linkoping, Sweden) and its aim has been from the beginning to make a breakthrough both in the theoretical basis concerning sustainable Lot Sizing, and in the subsequent practical application in today industrial contexts

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

An economic order quantity model for imperfect and deteriorating items with freshness and inventory level-dependent demand

Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2023.Consumer purchasing behaviour is influenced by many factors. Depending on the circumstances, these factors may become relevant drivers of important supply chain decisions. Expiration dates have an influence on the purchasing decision of consumers for perishable goods. Another behavioural influence that stimulates demand is the volume of goods that are available on display as part of the purchase transaction. Furthermore, the fact that certain goods deteriorate over time must also be evaluated within the context of the study of perishable goods. The market is increasingly seeking goods that have no inherent defects or imperfections. This investigation seeks to determine the impact of imperfect quality, deterioration, freshness and inventory level and also, how those issues can be improved upon in workable situations. This paper proposes an inventory model that stipulates the demand as a function of freshness and the inventory level. In addition, the inventory depletes through both deterioration and demand, and the product quality is not always perfect. The objective of the inventory model is to maximise the system’s profit, hence the study has developed a theoretical mathematical model for imperfect and deteriorating items with freshness and inventory level-dependent demand. A numerical example was used to illustrate the practical application of the model in a real life environment. Sensitivity studies were conducted to determine the impact of changes or variations to the inputs that are used in the model. The findings were that the date of expiry, the elasticity of demand and the selling price of the perfect products are the main constituents that affect the profitability.Industrial and Systems EngineeringMEng (Industrial Engineering)Unrestricte