March 2026

Mohammad Anas Wahaj | 26 mar 2026

Engineering design is an essential component of society's advancement and better future. Engineers utilize their expertise and knowledge to provide solutions. But, over the years the available knowledge has expanded enormously and being expert in all aspects is challenging and difficult for engineers and their teams. Design engineers can possess core knowledge in design process tasks such as design specification, ideation and design detail, but successful design implementation requires knowledge beyond it such as sustainability, materials, manufacturing, consumer behavior etc. According to the Concept-Knowledge (C-K) theory, creative design emerges when new concepts are matched with appropriate knowledge. Moreover, advancements in computational technologies has provided paradigm shift from computers as tools to computers as collaborators. Artificial intelligence (AI) is becoming a substantial contributor to this shift. The study, 'A framework of AI collaboration in engineering design (AICED)' [Authors: Chijioke C. Obieke of Queen's University (Belfast, UK); John Bridgeman of University of Liverpool (UK); Ji Han of University of Exeter (UK)], published by University of Cambridge Press in the journal Proceedings of the Design Society (August, 2025), introduces the AICED (AI Collaboration in Engineering Design) framework to bridge the knowledge space expansion gap in engineering design by creating a web tool Pro-Explora, that leverages advanced multi-agent LLM technology and retrieval-augmented generation (RAG) among others, to accelerate early-stage design tasks. Authors explain, 'Specifically, we examine large language models (LLMs), particularly multi-agent LLMs...LLMs' ability to mimic human cognitive behaviour is unprecedented, supporting complex activities across various fields...Many AI systems and tools are available but often segregated and not specifically adapted to support engineering design activities. Aggregating these tools to support engineering design practice specifically is explored in this study, highlighting its novelty and contribution...this study proposes an approach that minimises privacy risks when using multi-agent LLMs as collaborators in engineering design.' The theoretical framework for AICED facilitates effective collaboration between designers and AI during engineering design activities, primarily focusing on early-stage design (problem definition, design specification, and concept generation) while also considering later stages. The AICED framework benefits student design engineers, freelancers, and individual practitioners. It lets them quickly expand or enrich their conceptual knowledge of an idea or design problem, facilitating more informed discussions with other professionals. The AICED framework is designed as an adaptable, open framework that can be tailored to meet specific organisational needs. Read on...

Cambridge University Press: A framework of AI collaboration in engineering design (AICED)
Authors: Chijioke C. Obieke, John Bridgeman, Ji Han