Internationalization of markets and climate change introduce multifaceted challenges for modern supply chain (SC) management in the today's digitalisation era. On the other hand, Automated Guided Vehicle (AGV) systems have reached an age of maturity that allows for their utilization towards tackling dynamic market conditions and aligning SC management focus with sustainability considerations. However, extant research only myopically tackles the sustainability potential of AGVs, focusing more on addressing network optimization problems and less on developing integrated and systematic methodological approaches for promoting economic, environmental and social sustainability. To that end, the present study provides a critical taxonomy of key decisions for facilitating the adoption of AGV systems into SC design and * Corresponding author. Tel: +30 2310 995896; fax: +30 2310 996018. E-mail address: dimbec@autom.teithe.gr (D. Bechtsis).2 planning, as these are mapped on the relevant strategic, tactical and operational levels of the natural hierarchy. We then propose the Sustainable Supply Chain Cube (S2C2), a conceptual tool that integrates sustainable SC management with the proposed hierarchical decision-making framework for AGVs'. Market opportunities and the potential of integrating AGVs into a SC context with the use of the S2C2 tool are further discussed.
P roduct recovery operations in reverse supply chains face rapidly changing demand due to the increasing number of product offerings with reduced lifecycles. Therefore, capacity planning becomes a strategic issue of major importance for the profitability of closed-loop supply chains. This work studies a closed-loop supply chain with remanufacturing and presents dynamic capacity planning policies developed through the methodology of System Dynamics. The key issue of the paper is how the lifecycles and return patterns of various products affect the optimal policies regarding expansion and contraction of collection and remanufacturing capacities. The model can be used to identify effective policies, to conduct various "what-if" analyses, and to answer questions about the long-term profitability of reverse supply chains with remanufacturing. The results of numerical examples with quite different lifecycle and return patterns show how the optimal collection expansion/contraction and remanufacturing contraction policies depend on the lifecycle type and the average usage time of the product, while the remanufacturing capacity expansion policy is not significantly affected by these factors. The results also show that the collection and remanufacturing capacity policies are insensitive to the total product demand. The insensitivity of the optimal policies to total demand is a particularly appealing feature of the proposed model, given the difficulty in obtaining accurate demand forecasts.
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