Industrial packaging design involves selecting packaging materials and logistics configurations that protect products while controlling environmental impacts and costs. This decision is operationally complex because packaging alternatives differ in mass, volume, production requirements, transport modes, distribution routes, and end-of-life options. Existing packaging assessment tools often focus primarily on environmental indicators, when economic aspects are included, the modelling of key supply-chain stages such as distribution is frequently simplified. This limits their applicability for integrated industrial decision-making. This paper proposes a scenario-based tool for the joint environmental and economic assessment of industrial packaging alternatives. The tool combines scenario-based life cycle assessment with cost evaluation to support comparison of packaging configurations across supply-chain scenarios. Environmental impacts are calculated using a lifecycle graph, a hierarchical packaging composition structure, and a calculation engine linked to ecoinvent background data. Economic performance is evaluated through material, production, and distribution costs, with distribution costs estimated using a supervised machine-learning module trained on historical logistics data. The tool is demonstrated through a simplified industrial case study inspired by GE HealthCare, comparing one-way cardboard and wood packaging for transporting a medical device. Under the considered single-use scenario, cardboard packaging shows lower production and transportation costs and a lower carbon footprint than wood packaging. The tool supports reproducible and data-driven comparison of packaging alternatives for sustainable supply-chain and packaging design decisions.

Keywords

Industrial packaging, Scenario analysis, Life cycle assessment, Machine learning, and Sustainability.