Introduction
Artificial Intelligence (AI) is transforming the packaging sector by reshaping the way products are designed, manufactured, and customized. Through advanced machine learning systems and data analytics, AI enables the development of packaging solutions that are more sustainable, efficient, and tailored to consumer needs. A particularly relevant application concerns packaging configurators: intelligent tools capable of analysing parameters such as dimensions, materials, and product characteristics in order to automatically generate optimal packaging solutions. These configurators allow for the rapid exploration of multiple design alternatives based on customised parameters.
AI also enables the assessment of material sustainability and environmental impact, optimising packaging quantity and geometry. This approach not only enhances the customer experience—through better-fitting and more appealing packaging—but also contributes to reducing waste and logistics-related emissions. In summary, the integration of artificial intelligence into packaging configurators represents a significant technological advancement that combines sustainability, customization, and efficiency, thereby reshaping a key sector of modern industry.
In-depth Analysis
Although the literature has produced a wide range of digital methodologies and decision-support tools addressing circular economy (CE) principles in packaging—particularly in the domain of end-of-life management—a gap remains in the integration of these principles into early-stage packaging design processes. A notable contribution in this area is the Reverse Logistics Support Tool (RLST), recently proposed by Mallick et al. [Mallick et al., 2024], which supports companies in assessing strategic drivers, product-specific contextual characteristics, regulatory conditions, and system design variables in alignment with community-level policy frameworks.
The RLST framework operates by incorporating variables such as stakeholder involvement, digital technologies, consumer behaviour, and policy instruments. While a tool such as RLST provides substantial guidance for downstream operations—particularly in post-consumer packaging recovery, sorting, and processing—its ability to inform upstream decision-making remains limited. Specifically, the RLST does not embed lifecycle-aware intelligence within the design phase, where up to 80% of a product’s environmental footprint is determined. Furthermore, it lacks the capability to support modular design thinking, traceability integration, and user co-design, all of which are increasingly recognised as critical enablers of circularity in packaging systems.
In this context, there is a pressing need for digital tools implemented with systems capable of embedding regulatory-compliant logic directly into product development workflows. Several conceptual studies suggest that such systems could extend beyond conventional rule-based configurators used in mass customization, evolving into intelligent and interactive platforms capable of simulating end-of-life pathways, assessing regulatory compatibility, and supporting sustainable material selection at the very moment of packaging design. Such an evolution would enable the alignment of design processes with environmental compliance requirements, consumer expectations, and circular material flows from the earliest stages of product development.
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Towards a circular economy: Development of a support tool for designing reverse logistics systems
Reverse Logistics (RL) of end-of-use/end-of-life products is a key approach for supporting the transition to a circular economy. However, lack of knowledge and experience in designing RL is one of the barriers for companies in implementing successful RL. This research proposes an RL support tool (RLST) for designing RL systems, developed through iterative cycles of theoretical development and empirical testing/feedback from potential users. The RLST builds upon the principles of configuration systems to adapt the various aspects of RL design into a knowledge base and, subsequently, into an Excel-based support tool – in addition to allowing companies to assess their motivation/driver and set the context (e.g., product characteristics, the existence and nature of Extended Producer Responsibility (EPR) legislation), it supports the design of the RL network/channel and other aspects such as stakeholder collaboration, legislation, consumer behaviour and incentives, use of digital technologies, key performance indicators and factors around governance/programme management. Such a tool can be helpful for practitioners in addressing the knowledge gaps, stimulating discussions among stakeholders for scenario building and for analysing how different scenarios might work. The research advances the knowledge on RL systems design for the circular economy along with, for the first time, building knowledge and application of configuration systems in the field of RL
Increasing the consumer-perceived benefits of a mass- customization experience through sales-configurator capabilities
The consumer’s experience of self-customizing a product with a sales configurator can be a source of experience-related benefits for the consumer, above and beyond the traditionally considered utility of possessing a product that better fits his/her idiosyncratic needs. Although such experience-related benefits have been found by previous studies as increasing consumers’ willingness to pay for mass-customized products, research on what characteristics sales configurators should have to increase such benefits is still in its infancy. In this paper, we argue that two such benefits (i.e., hedonic and creative-achievement benefits) increase as a sales configurator deploys, to a greater extent, the following capabilities: focused navigation, flexible navigation, user-friendly product space description, easy comparison and benefit-cost communication. Subsequently, by analyzing 675 self-customization experiences made by 75 engineering students on 30 real Web-based configurators of consumer goods, we find empirical support for all the hypothesized relationships. We conclude discussing the contribution of the study to relevant debates, its managerial implications as well as its limitations and the related opportunities for further research.
https://doi.org/10.1016/j.compind.2014.02.004
An Integrated Business Strategy for the Twin Transition: Leveraging Digital Product Passports and Circular Economy Models
Companies face significant challenges in implementing digital transformation, often because of the use of fragmented strategies and limited cross-¬ functional coordination. Furthermore, not all digital innovations align with sustainability objectives. In response to this complexity, recent European Union directives have introduced digital product passports (DPPs) as strategic instruments to bridge the gap between digitalization and sustainability. Although promising, DPP implementation remains in its infancy and requires robust data governance to mitigate the risk of information overload. The present study integrates business perspectives into the design of DPPs, with a particular focus on the textile industry. It explores how DPPs can enhance competitiveness, facilitate sustainability monitoring, and promote circularity. Drawing on insights from textile firms and consulting support, this research employs multicriteria decision making methodologies specifically, the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS). The findings reveal a strong alignment between
these methodologies and a shared recognition of the strategic value of DPPs, particularly in facilitating access to information on product reuse, repair, and recycling. Additionally, the analysis highlights consultants’ emphasis on the “Made in Italy” designation as a key differentiator. Overall, DPPs are shown to advance the development of circular business models in the textile sector
by supporting three strategic priorities: material traceability, repair guidance, and optimized recycling pathways.
https://doi.org/10.1002/bse.70065
Generative design and its role in developing the design of cans and packaging
In the current study (generative design and its role in developing the design of cans and packaging), the researcher studied generative design and its role in developing the field of can and packaging design, which saves the effort and time needed to develop it, by using the designer’s scientific abilities in directing those models and applications and using appropriate standards according to the scientific foundations studied from the inputs. Which contributes to enriching the design of these boxes and covers. To demonstrate this, the researcher experimented with working on the Midjournal generative intelligence design program, which is considered one of the most important generative design programs in designing packaging for perfumes from well-known brands. The researcher relied on the statistical approach in extracting sample results through. A questionnaire form through which the experience was evaluated.
https://doi.org/10.35560/jcofarts1437
Designing for circularity: exploring configurator-based decision support for Eco-design in food packaging
The packaging industry occupies a central position in the sustainability transition, particularly as
regulatory frameworks increasingly mandate alignment with circular economy (CE) principles. In the European Union, the upcoming Packaging and Packaging Waste Regulation (PPWR), effective from January 2025, requires all packaging to be either reusable or recyclable in a technically and economically feasible manner. Since the majority of a product’s environmental burden is determined during its early design phase, digital tools must evolve beyond conventional parametric modeling to incorporate environmental metrics, material recovery pathways, and lifecycle intelligence. While sustainable packaging design has received growing academic attention, the deployment of AI-based configurators to support eco-design and end-of-life strategies remains underdeveloped. This study investigates the potential of product configurators as intelligent, rule- based decision-support systems capable of embedding CE-aligned design logic in the food packaging sector. Adopting a multi-method empirical approach, combining Multi-Criteria Decision Analysis, Analytical Hierarchy Process, and expert evaluation, the research assesses the relative suitability of reuse, mechanical recycling, chemical recycling, and organic recycling against criteria defined by industry specialists. Furthermore, the study develops a conceptual framework for a next-generation configurator, designed to integrate eco-design principles, modular product architecture, and traceability data within packaging systems. Findings indicate that configurators can be re-engineered to function as intelligent interfaces for operationalizing CE principles
in product development workflows. The study highlights modularity, material knowledge, and traceability as critical enablers, providing a roadmap for engineers and practitioners developing CE-compliant packaging configurators.
ConfWS 2025
27th International Workshop on Configuration Bologna, Italy, October 25-26, 2025
Proceedings : https://ceur-ws.org/Vol-4149/
