Engineering Design Intelligence: A Multidisciplinary Systems Framework for Human-Centred, Systems-Led and Value-Driven Engineering Innovation

About the project

About the Project Engineering is undergoing fundamental transformation. Advances in artificial intelligence (AI), digital twins, advanced manufacturing, sustainable technologies and connected systems are reshaping how products are conceived, developed and delivered. Simultaneously, engineers must design solutions that balance technical performance, user experience, sustainability, manufacturability, commercial viability, regulatory expectations and societal value. Although significant progress has been made across these disciplines, existing engineering design methodologies typically address them independently, resulting in fragmented decision-making and limiting innovation within increasingly complex engineering systems. This project proposes Engineering Design Intelligence (EDI) as a novel engineering design paradigm that shifts engineering from optimising individual design attributes towards optimising whole engineering systems. Engineering Design Intelligence integrates systems thinking, engineering science, stakeholder value, human-centred design, sustainability, business strategy, lifecycle engineering, artificial intelligence, digital twins and Design for Excellence (DfX) within a unified evidence-based methodology. Rather than treating these disciplines in isolation, EDI provides engineers with a structured framework for making balanced, transparent and value-driven decisions throughout the engineering design process. Engineering Design Intelligence is proposed as an overarching engineering design paradigm. This research will develop the Engineering Design Intelligence Framework and Toolkit to translate the paradigm into practical engineering methodologies for industry and education. The central research question is: How can Engineering Design Intelligence be developed and validated as a systems-based methodology that enables balanced, evidence-based and value-driven engineering design decisions throughout the product lifecycle? At the heart of this research is systems thinking. Engineering products operate within interconnected socio-technical ecosystems involving users, manufacturers, suppliers, maintenance engineers, businesses, regulators and society. Every stakeholder has different priorities, creating competing technical, environmental, commercial and human requirements. Existing engineering methodologies provide valuable tools for optimising individual objectives but offer limited support for balancing interactions across the wider engineering system. This project addresses that gap by developing a systems framework capable of integrating these competing perspectives into a coherent engineering decision-making methodology. The research will combine engineering design, systems engineering, stakeholder analysis, human-centred design, business modelling and digital engineering methods. Working closely with industrial partners across healthcare, consumer products, manufacturing and industrial systems, the project will investigate current engineering design practices, identify decision gaps and establish the principles underpinning Engineering Design Intelligence. Insights from literature, industrial collaboration and iterative framework development will ensure that the methodology is both academically rigorous and industrially applicable. The primary deliverable of the project will be the Engineering Design Intelligence Framework, which translates the principles of Engineering Design Intelligence into a structured systems framework for engineering design decision-making. The framework will define the principles, design workflow, decision stages, stakeholder interactions and evaluation criteria required to support engineering decision-making throughout the product lifecycle. Supporting the framework, the project will develop an Engineering Design Intelligence Toolkit containing stakeholder mapping methods, decision-support models, engineering metrics, design evaluation criteria, implementation guidelines and practical templates to enable adoption by industry and engineering educators. Artificial intelligence and digital twins will be investigated as enabling technologies within the framework. Rather than replacing engineering judgement, AI will support engineers in analysing design trade-offs, exploring alternative concepts and evaluating multiple objectives simultaneously. Digital twins will enable predictive modelling, virtual validation and lifecycle assessment before physical implementation. The Engineering Design Intelligence Framework and Toolkit will be validated through multiple industrial case studies, demonstrating their applicability, robustness and transferability across different engineering sectors. The anticipated impact extends beyond individual product improvements. Academically, the project seeks to establish Engineering Design Intelligence as a new research field connecting engineering design, systems engineering, digital engineering and value-driven innovation. Industrially, it will provide organisations with a practical methodology for delivering technically robust, commercially successful, sustainable and human-centred engineering solutions. Educationally, it will support the evolution of engineering curricula by embedding systems thinking, stakeholder value and multidisciplinary decision-making into engineering education. Ultimately, this research seeks to redefine engineering design for the twenty-first century. Rather than optimising isolated product attributes, Engineering Design Intelligence provides a systems-based methodology for creating engineering solutions that simultaneously generate technical, human, environmental and commercial value. The long-term vision is to establish Engineering Design Intelligence as a recognised engineering paradigm that shapes research, education and industrial practice while enabling organisations to develop resilient, responsible and innovative engineering solutions that create lasting value across the entire engineering ecosystem; for people, industry and society.

Research areas