Digital technologies and solutions for food waste management and reduction

WP 2.3 addressed food waste from an informational and decision-making perspective. A significant share of product losses along food supply chains derives not from unavoidable technical failures, but from decisions taken under conditions of incomplete, fragmented or poorly integrated information. The Work Package therefore focused on digital technologies as enabling tools for improving visibility, measurement and adaptive control of complex production and logistics systems.

Research activities developed quantitative models, analytical indicators and digital platforms aimed at optimising production, packaging and distribution processes across the entire product–packaging life cycle. A multidisciplinary approach combined engineering expertise, data analytics and applied experimentation to design data-driven solutions capable of supporting actors across the supply chain.

A central component of the work was the development of predictive models and simulation tools tested through pilot activities and industrial case studies. Quantitative modelling and comparative scenario analysis enabled the evaluation of alternative logistical and production configurations in terms of cost, energy performance and environmental impact. Within this framework, packaging systems were analysed not only as protective elements, but as strategic components influencing product quality preservation and shelf-life extension.

Experimental validation activities were conducted at the Food Supply Chain Center of the University of Bologna, where a mechatronic system was implemented to simulate transport conditions for palletised load units. Controlled reproduction of thermo-hygrometric and mechanical stresses — including temperature, humidity and vibration — enabled integrated assessment of logistics impacts on product quality at the consumer stage.

Advanced digital tools, including digital twin and cyber-physical twin systems, were applied to support multi-objective decision-making in manufacturing, packaging and distribution contexts. By integrating heterogeneous datasets and aligning them temporally and geographically, WP 2.3 contributed to the development of adaptive and evidence-based strategies for waste reduction across agri-food systems.

WP 2.3 strengthened the digital infrastructure required for systematic food waste measurement, modelling and governance, supporting more transparent, efficient and resilient supply chain management.