Skip to content
#data science #generative ai Review Open access

Integrating Sustainability and Life Cycle Assessment into CAD-Driven Product Design: A Systematic Review of Frameworks, Additive Manufacturing Trade-offs and Industry 4.0 Enablers

Oct 2026 · Open Access Research Journal of Science and Technology · 0 citations

Abstract

With decarbonisation goals and new ecodesign regulations, life cycle assessment (LCA) is increasingly becoming a function of computer-aided design (CAD). This paper undertakes a systematic review following PRISMA 2020 statement of research related to integrating sustainability and LCA into CAD driven product design. Peer-reviewed journal articles and conference papers published from 2016 to 2026 were retrieved from the databases Scopus, Web of Science, IEEE Xplore and ScienceDirect (Google Scholar was used as a supporting database) and synthesized in a thematic synthesis. The evidence is presented in six streams: CAD–LCA integration frameworks; sustainable and generative optimisation; design for additive manufacturing (DfAM) and topology optimisation; process-parameter optimisation as a source for life cycle inventory (LCI) data; Industry 4.0 and digital twin (DT) based assessment; and social and organisational enablers of adoption. The review concludes that most of the life cycle impact occurs at the conceptual stage, and that tools for environmental assessment at the conceptual level are not sufficiently mature at the detailed design stage, when geometry and material are fixed. There is a constant dilemma between the material savings possible with topology optimisation and AM, and the extra energy needed to produce structures using these routes does not necessarily mean they have a smaller footprint. Experimental process-optimisation studies demonstrate that the choice of process parameters has a significant effect on the energy used, scrap produced and the consumption of tools, in the cases of machining, moulding, finishing and material-extrusion printing, but the results from these studies are generally not transferred to inventories to use in design tools. The social aspect and the conditions of organisation and skills for adoption, especially in developing economies are under-represented. There are six research priorities identified: uncertainty-aware early-stage LCA, joint material–energy optimisation in DfAM, process-parameter-linked inventory models, interoperability of CAD, LCA, product lifecycle management, and digital twin platforms, AI purpose-built for ecodesign, integration of social and circularity indicators. A closed-loop system which integrates design, assessment, process and operation data is suggested to inform future work, which can be layered.

Read PDF

Similar papers

#computer vision Review Sep 2017

Agile Software Development Methods: Review and Analysis

This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.

P. Abrahamsson, O. Salo, Jussi Ronkainen et al. · 727 citations · ⚡54
#computer vision Jun 2008

The impact of agile practices on communication in software development

The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.

M. Pikkarainen, Jukka Haikara, O. Salo et al. · 401 citations · ⚡48
#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

Trajectory Balance: Improved Credit Assignment in GFlowNets

It is proved that any global minimizer of the trajectory balance objective can define a policy that samples exactly from the target distribution, and empirically demonstrate the benefits of the trajectories balance objective for GFlowNet convergence, diversity of generated samples, and robustness to long action sequenc...

Esmeralda S. Whitammer, Moksh Jain, Emmanuel Bengio et al. · 302 citations · ⚡60

Related blog posts

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.