Empowering integrated design of a product and its downstream supply chain with smart technologies: a decision-making framework

Abstract

This work builds on research in integrated product and supply chain design, with a particular focus on the simultaneous optimization of the product and its related downstream supply chain operations. It focuses on the downstream supply chain, which encompasses distribution, warehousing, and transportation operations, and explores the role of advanced technologies in optimizing these processes. The research highlights the impact of IoT, machine learning, big data analytics, blockchain, and digital twins in improving visibility, demand forecasting, inventory management, and distribution planning. A conceptual framework is proposed, emphasizing the need for strategic, tactical and operational decision-making to align product design with logistics constraints at the different phases of decision horizon. A UML sequence diagram is proposed to illustrate the approach adopted for integrated design of the product and its related downstream supply chain. It models the interactions between key stakeholders, including product designers, producers, distribution centers, and customers, with machine learning algorithms that plays a central role in optimizing demand forecasting, production planning, and inventory allocation.