Batching is a well-known cause of the bullwhip effect. Despite being very common in many industries to leverage economies of scale, it has been little explored due to its nonlinear complexity. This ...work examines how order-quantity batching affects the performance of closed-loop supply chains, which are gaining importance as a result of their environmental and economic value. Specifically, we analyse a hybrid system with both manufacturing and remanufacturing operations. We observe that, when an order-up-to policy is used in the serviceable inventory, bullwhip is always an increasing function of the batch size. Nevertheless, when a smoothing replenishment rule is used, the closed-loop supply chain behaves differently for low and high volumes of returns due to the different degrees of uncertainty they convey. In the high-volume case, batches should also be as small as possible. In contrast, in the low-volume case, bullwhip can be mitigated by setting the batch size to a divisor of the mean production rate. However, this may lower the customer service level achieved. We also find that reducing manufacturing batch sizes should be prioritised over remanufacturing ones when both are large. In the light of our results, we finally provide professionals with specific suggestions on how to better manage closed-loop supply chains where goods are produced and delivered in batches.
•We investigate the dynamic behavior of a closed-loop supply chain with capacity restrictions.•Capacity constraints improve the dynamic performance of the closed-loop supply chain.•Capacity ...constraints have to be properly reduced to fulfil customer demand in a cost-effective manner.
In this paper, we investigate the dynamic behavior of a closed-loop supply chain with capacity restrictions both in the manufacturing and remanufacturing lines. We assume it operates in a context of a twofold uncertainty by considering stochastic demand and return processes. From a bullwhip perspective, we evaluate how the four relevant factors (specifically, two capacities and two sources of uncertainty) interact and determine the operational performance of the system by measuring the variability of the manufacturing and remanufacturing lines and the net stock. Interestingly, while the manufacturing capacity only impacts on the forward flow of materials, the remanufacturing capacity affects the dynamics of the whole system. From a managerial viewpoint, this work suggests that capacity constraints in both remanufacturing and manufacturing lines can be adopted as a fruitful bullwhip-dampening method, even if they need to be properly regulated for avoiding a reduction in the system capacity to fulfill customer demand in a cost-effective manner.
Increasing the understanding of the management of closed-loop supply chains (CLSCs) is fundamental to accelerate the much-desired transition towards the circular economy. From this perspective, we ...investigate the value of proportional order-up-to policies (POUT) policies and the adjustment of their inventory controllers in these systems. These policies are often used to improve the performance of traditional supply chains due to their ability to cope with the damaging bullwhip effect; however, they have not been sufficiently studied in CLSCs. Through a difference equation modelling approach, we show that POUT policies are also a valuable instrument for enhancing the CLSC dynamics. Specifically, we find that the POUT model outperforms the traditional order-up-to policy in a hybrid manufacturing/remanufacturing system, yielding significant cost savings. To optimise the key trade-off between order and inventory variability, the tuning of the inventory controllers needs to consider not only the cost structure of the CLSC but also the average return rate. Specifically, managers should react to increasing levels of circularity by lowering the setting of the controllers' time constant. In the light of our findings, we suggest two strategies for aligning the calibration of the POUT controllers and the forecasting methods to increase the economic performance of CLSCs.
We consider a hybrid manufacturing/remanufacturing system where the returned products (cores) are classified into different quality grades. Each grade requires different remanufacturing operations ...and thus lead times. We examine the implications of the quality-grading scheme on the dynamic behavior of closed-loop supply chains, benchmarking this against a typical system where all the returns undergo the same remanufacturing process. Through control engineering techniques, we evaluate the Bullwhip and inventory performance of the supply chain by observing the step response of the orders and net stocks (the shock lens), analyzing the frequency behavior of these signals (the filter lens), and measuring their dynamics due to stochastic demand (the variance lens). Subsequently, we discuss the operational savings and additional costs derived from quality grading. We find that the pre-sorting mechanism allows for smoothing the supply chain operations; however, its impact on customer satisfaction is ambivalent. Indeed, we observe that the documented ‘lead-time paradox’ of the remanufacturing process in hybrid systems results here in a ‘quality paradox’: lower quality returns may increase the performance of inventories. This affects particularly low-frequency demands. Importantly, we analytically derive the optimal setting of the closed-loop pipeline estimation in order-up-to policies for avoiding long-term inventory drifts. This analysis reveals key potential benefits of information transparency for improving the operational performance, and thus the environmental and economic sustainability, of closed-loop supply chains.
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.
While most supply chain models assume linearity, real production and distribution systems often operate in constrained contexts. This article aims to analyse the consequences of capacity limits in ...the order-up-to replenishment policy with minimum mean squared error forecasting under independently and identically distributed random demand. Our study shows that the impact of this nonlinearity is often significant and should not be ignored. In this regard, we introduce the concept of a settling capacity, which informs when our knowledge from a linear analysis is a reasonable approximation in a nonlinear context. If the available capacity is less than the settling capacity, the nonlinear effects can have a significant impact. We compare the Bullwhip Effect and Fill Rate in constrained contexts to well-established results for linear supply chains. We reveal the capacity limit acts as a production smoothing mechanism, at the expense of increasing inventory variability. We proceed to analyse the economic consequences of the capacity constraint and show that it can actually reduce costs. We provide an approximate solution for determining the optimal capacity depending on the demand, the unit costs and the lead time.
•This work compares the financial performance of Kanban and Drum-Buffer-Rope.•We evaluate supply chain performance under progressive compound noise conditions.•Agent-based techniques are shown to ...provide a powerful decision-support framework.•Due to its bottleneck orientation, DBR offers greater robustness against variability.•Kanban delivers similar performance at a lower cost in highly predictable scenarios.
Managing efficiently the flow of products throughout the supply chain is essential for succeeding in today's marketplace. We consider the Kanban (from Lean Management) and Drum-Buffer-Rope (DBR, from the Theory of Constraints) scheduling mechanisms and evaluate their performance in a four-echelon supply chain operating within a large noise scenario. Through an agent-based system, which is presented as a powerful model-driven decision support system for managers, we show the lower sensitivity against variability and the higher financial performance of DBR, which occurs as this mechanism improves the supply chain robustness due to its bottleneck orientation. Nonetheless, we prove the existence of regions in the decision space where Kanban offers similar performance. This is especially relevant taking into account that Kanban can be implemented at a lower cost, as DBR requires a higher degree of information transparency and a solid contract between partners to align incentives. In this sense, we offer decision makers a methodological approach to reach an agreement when the partners decide to move from Kanban to DBR in a bid to increase the overall net profit in supply chains operating in a challenging noise scenario.
The Bullwhip Effect, which refers to the increasing variability of orders traveling upstream the supply chain, has shown to be a severe problem for many industries. The inventory policy of the ...various nodes is an important contributory factor to this phenomenon, and hence it significantly impacts on their financial performance. This fact has led to a large amount of research on replenishment and forecasting methods aimed at exploring their suitability depending on a range of environmental factors, e.g. the demand pattern and the lead time. This research work approaches this issue by seeing the whole picture of the supply chain. We study the interaction between four widely used inventory models in five different contexts depending on the customer demand variability and the safety stock. We show that the concurrence of distinct inventory models in the supply chain, which is a common situation in practice, may alleviate the generation of inefficiencies derived from the Bullwhip Effect. In this sense, we demonstrate that the performance of each policy depends not only upon the external environment but also upon the position within the system and upon the decisions of the other nodes. The experiments have been carried out via an agent-based system whose agents simulate the behavior of the different supply chain actors. This technique proves to offer a powerful and risk-free approach for business exploration and transformation.
•We analyze different smoothing replenishment rules in the Beer Game scenario.•KAOS methodology is used to devise the agent-based simulation model.•The concurrence of distinct inventory models may mitigate the Bullwhip Effect.•Forecasting is a more robust solution than adding a proportional controller.•ABMS is a powerful approach for exploring and transforming the supply chain.
Digital platforms have grown rapidly by facilitating connections among users to exchange products, services, or information. However, very few platforms have a truly global footprint given that ...factors such as competition, imitation, innovation, and cultural and political barriers hamper a digital platform's international growth path. The geographical scope of network effects plays a crucial role in this process, impacting users at various levels from the local to the global. We model the dynamics of international platform competition and predict its outcomes in terms of global potential market percentage through a simulation of the international growth of a two-sided platform in competition with two follower platforms in different locations (home/abroad) and different internationalization strategies (gradual/accelerated), and operating under different network effects (local/global). The model contemplates different delays in the launching of the rival platforms and different degrees of innovation (improvement) in comparison with the original platform.
Our findings highlight the crucial role of network effects, with global effects benefiting first movers and local effects favoring followers, especially if they start in a market different from the first mover's. Moreover, domestic followers must innovate, while followers in less competitive markets with local network effects have more options to increase potential market percentage, including launching a clone. These insights offer valuable suggestions for strategy development and regulatory considerations related to market share, market power, and international expansion.
•A simulation for the internationalization of a two-sided platform, amid diverse network effects and competition scenarios.•Local (global) network effects lead to gradual (accelerated) internationalization.•Imitation and innovation by domestic and international followers can impede the global leadership of the first mover.•Foreign followers can establish a strong position even without innovation, particularly in the presence of local network effects.
•TOC versus order-up-to inventory policy comparison using the ‘Beer Game’ scenario.•KAOS methodology used to devise the multi-agent simulation model.•Robust SW engineering and TDD techniques used to ...build the model.•Bottleneck managed through DBR methodology, placing the drum at the shop retailer.•TOC philosophy leads the supply chain to a significant decrease of Bullwhip Effect.
In the current environment, Supply Chain Management (SCM) is a major concern for businesses. The Bullwhip Effect is a proven cause of significant inefficiencies in SCM. This paper applies Goldratt’s Theory of Constraints (TOC) to reduce it. KAOS methodology has been used to devise the conceptual model for a multi-agent system, which is used to experiment with the well known ‘Beer Game’ supply chain exercise. Our work brings evidence that TOC, with its bottleneck management strategy through the Drum–Buffer–Rope (DBR) methodology, induces significant improvements. Opposed to traditional management policies, linked to the mass production paradigm, TOC systemic approach generates large operational and financial advantages for each node in the supply chain, without any undesirable collateral effect.
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