Harnessing the Power of Statistics in Green Composite Modelling

This chapter explores the critical role of statistical modelling in the design, fabrication, and optimization of green composites, particularly those manufactured through fused deposition modelling. As industries transition towards sustainable and eco-efficient manufacturing, green composites, comprising bio-based matrices reinforced with natural fibres, offer viable alternatives to conventional synthetic materials. However, challenges such as fibre variability, non-linear process interactions, and inconsistent mechanical performance necessitate a scientific, data-driven approach to process development. This chapter presents a comprehensive overview of statistical tools, including design of experiments, response surface methodology, analysis of variance, regression analysis, Taguchi methods, and principal component analysis and illustrates their application in green composite research. Emphasis is placed on constructing and validating predictive models for mechanical and functional properties and integrating these models into sustainable design frameworks and decision-support systems. Through case studies and practical examples, this chapter highlights how statistical techniques can uncover hidden interactions, support multi-objective optimization, and facilitate robust product development. The integration of statistical models with sustainability-driven decision-making tools is presented as a pathway to more resilient, efficient, and environmentally responsible engineering practices.