Computational Intelligence for Sustainable Manufacturing Modelling: Building a Green Product Configurator

Abstract

This paper presents a framework for computational intelligence in sustainable manufacturing modelling, focusing on the development of a green product configurator. Leveraging the Product Variant Master (PVM) structure and aligned with EN15804 standards, the framework integrates modular lifecycle stages: raw materials, manufacturing, transportation, use, and end-of-life into a causality-driven rule engine for dynamic Environmental Product Declaration (EPD) calculations. By defining detailed back-end attributes and rulesets, the configurator enables high-level user decisions, such as selecting "sustainable materials" or "low-emission manufacturing," while transparently computing their lifecycle impacts in accordance with ISO 14025. This approach bridges the gap between user-friendly interfaces and the complexity of lifecycle sustainability assessments, providing manufacturers with a decision-support tool for balancing design flexibility with environmental accountability. Future research directions include enhancing real-time feedback systems and exploring interactive user interfaces to further align sustainability objectives with decision-making in product configuration.