A Data Architecture to aid Life Cycle Assessment in closed-loop Reusable Plastic Container networks

Returnable container networks have caught the eye of those companies that aim to reduce waste generation and environmental impact. The literature already includes studies on the environmental impact (i.e. Life Cycle Assessment, LCA) of these networks. However, the major part is based on secondary data, since the collection of primary data results complex and time-intensive. This paper proposes an object-relational database dedicated to the storage of data from closed-loop reusable plastic crates (RPC) networks for fruits and vegetables. The goal is supporting scholars and managers during the LCA through a user-friendly data architecture, while suggesting structured guidelines for the primary data collection. Each node of the RPC network is characterized by a similar set of entity types, such as machines, that allows to process the RPCs with respect to specific cycles. Each entity, process and cycle is therefore reflected in the database by objects that are connected with relations.